images listlengths 2 2 | data_source large_stringclasses 4
values | prompt listlengths 2 2 | ability large_stringclasses 4
values | reward_model dict | metadata dict |
|---|---|---|---|---|---|
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAgIDAQEAAAAAAAAAAAAAAQIAAwUGBwQI/8QASBAAAQMCBAMGAwQIBAQE... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many fork and kettle are there in this space?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a fork located at [192, 66, 224, 70]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a fork located at [110, 143, 142, 146]\\n- There's a kettle positioned at coordinates [120, 120, 138, 142]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The fork_0 at [110, 143, 142, 146] in auxiliary perspective is not visible in main perspective\\n- The fork_1 at [192, 66, 224, 70] in main perspective is not visible in auxiliary perspective\\n- The kettle_0 at [120, 120, 138, 142] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_4",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 1,
"noise_objects": [
"cardboardbox_noise0",
"cup_noise1"
],
"objects": [
"fork_0",
"fork_1",
"kettle_0",
"cardboardbox_noise0",
"cup_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c",
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7817_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAwADAQEAAAAAAAAAAAAAAAECAwUHBgT/xABJEAABAwIEAwYDBAgDBgQH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you assess how many apple are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a apple located at [39, 14, 41, 17]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a apple located at [22, 25, 24, 27]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The apple_0 at [22, 25, 24, 27] in auxiliary perspective is not visible in main perspective\\n- The apple_1 at [39, 14, 41, 17] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 1,
"noise_objects": [
"green_peas_noise0",
"cardboardbox_noise1"
],
"objects": [
"apple_0",
"apple_1",
"green_peas_noise0",
"cardboardbox_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c",
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9381_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAgMBAQEBAAAAAAAAAAAAAAECAwQFBgcI/8QAQxAAAQMCBAMFBgQEBQMD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Could you tell me how many banana and hammer exist?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first banana at [65, 84, 73, 90]\\n- I also see a second banana at [144, 174, 173, 215]\\n- I notice a hammer at [198, 67, 210, 75]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first banana at [247, 76, 251, 82]\\n- I also notice a second banana located at [225, 173, 240, 211]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The banana_0 visible in main perspective at [65, 84, 73, 90] corresponds to the same object visible in auxiliary perspective at [247, 76, 251, 82]\\n- The banana_1 visible in main perspective at [144, 174, 173, 215] corresponds to the same object visible in auxiliary perspective at [225, 173, 240, 211]\\n- The hammer_0 at [198, 67, 210, 75] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"shoe_noise0",
"kettle_noise1"
],
"objects": [
"banana_0",
"banana_1",
"hammer_0",
"shoe_noise0",
"kettle_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "6805_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAIBAwYFBAf/xABJEAABAwIDBAUJBQUFBwUA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many pizza do you need to move?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first pizza at [0, 27, 5, 30]\\n- I also see a second pizza at [24, 28, 30, 33]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a pizza located at [49, 27, 55, 30]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pizza_0 visible in main perspective at [0, 27, 5, 30] corresponds to the same object visible in auxiliary perspective at [49, 27, 55, 30]\\n- The pizza_1 at [24, 28, 30, 33] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"peach_noise0",
"spoon_noise1"
],
"objects": [
"pizza_0",
"pizza_1",
"peach_noise0",
"spoon_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8319_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAEDBAUGAgcI/8QAShAAAQMDAwEFBQUFBAgD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many pizza and hammer are located here?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a pizza located at [36, 22, 39, 25]\\n- There's a hammer positioned at coordinates [45, 20, 48, 22]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a hammer located at [10, 25, 11, 26]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pizza_0 at [36, 22, 39, 25] in main perspective is not visible in auxiliary perspective\\n- The hammer_0 visible in main perspective at [45, 20, 48, 22] corresponds to the same object visible in auxiliary perspective at [10, 25, 11, 26]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"wine_noise0",
"green_peas_noise1"
],
"objects": [
"pizza_0",
"hammer_0",
"wine_noise0",
"green_peas_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9761_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECBAUDBgf/xABGEAABAwIDBAUJBAgFBQEB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you list how many wine are available?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first wine at [23, 21, 27, 28]\\n- I also see a second wine at [25, 10, 28, 19]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first wine at [39, 22, 41, 29]\\n- I also notice a second wine located at [74, 25, 76, 28]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wine_0 at [39, 22, 41, 29] in auxiliary perspective is not visible in main perspective\\n- The wine_1 visible in main perspective at [23, 21, 27, 28] corresponds to the same object visible in auxiliary perspective at [74, 25, 76, 28]\\n- The wine_2 at [25, 10, 28, 19] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"apple_noise0",
"cardboardbox_noise1"
],
"objects": [
"wine_0",
"wine_1",
"wine_2",
"apple_noise0",
"cardboardbox_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9466_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABHEAABAwMCAwUFBgMFBgUF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Could you specify how many hammer there are?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a hammer located at [334, 87, 352, 96]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a hammer located at [145, 90, 158, 97]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The hammer_0 visible in main perspective at [334, 87, 352, 96] corresponds to the same object visible in auxiliary perspective at [145, 90, 158, 97]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_4",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 8,
"noise_objects": [
"meat_noise0",
"tomato_noise1",
"knife_noise2"
],
"objects": [
"hammer_0",
"meat_noise0",
"tomato_noise1",
"knife_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7909_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABFEAACAQMBBQYDBwIEBQQA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the total number of pizza and peach?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first pizza at [232, 119, 260, 137]\\n- I also see a second pizza at [12, 125, 58, 145]\\n- I can see the first peach at [197, 68, 205, 75]\\n- I also see a second peach at [0, 128, 3, 138]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a pizza located at [200, 85, 219, 97]\\n- There's a peach positioned at coordinates [186, 74, 195, 84]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pizza_0 at [232, 119, 260, 137] in main perspective is not visible in auxiliary perspective\\n- The pizza_1 visible in main perspective at [12, 125, 58, 145] corresponds to the same object visible in auxiliary perspective at [200, 85, 219, 97]\\n- The peach_0 at [197, 68, 205, 75] in main perspective is not visible in auxiliary perspective\\n- The peach_1 visible in main perspective at [0, 128, 3, 138] corresponds to the same object visible in auxiliary perspective at [186, 74, 195, 84]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 3,
"noise_objects": [],
"objects": [
"pizza_0",
"pizza_1",
"peach_0",
"peach_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2",
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9385_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwUEBgf/xABBEAABAwIEAwYDBgQFBAID... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many instances of kettle are in the area?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a kettle located at [239, 88, 253, 103]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first kettle at [60, 95, 86, 114]\\n- I also notice a second kettle located at [227, 102, 243, 123]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The kettle_0 visible in main perspective at [239, 88, 253, 103] corresponds to the same object visible in auxiliary perspective at [60, 95, 86, 114]\\n- The kettle_1 at [227, 102, 243, 123] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_4",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"banana_noise0",
"knife_noise1"
],
"objects": [
"kettle_0",
"kettle_1",
"banana_noise0",
"knife_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c",
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7535_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAgABAwQFBgf/xABJEAABAwIEAwUFBQUFBgUF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many shoe are there in this space?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a shoe located at [278, 81, 292, 90]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a shoe located at [111, 82, 123, 89]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The shoe_0 visible in main perspective at [278, 81, 292, 90] corresponds to the same object visible in auxiliary perspective at [111, 82, 123, 89]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"pizza_noise0",
"green_peas_noise1",
"scissors_noise2"
],
"objects": [
"shoe_0",
"pizza_noise0",
"green_peas_noise1",
"scissors_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy",
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7482_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQGBQf/xABKEAACAQIDBAYGCAQDBgUF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you identify all the pizza and shoe?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a pizza located at [122, 136, 150, 155]\\n- There's a shoe positioned at coordinates [152, 134, 168, 160]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first pizza at [143, 142, 171, 163]\\n- I also notice a second pizza located at [371, 136, 383, 147]\\n- I notice a shoe at [215, 132, 226, 155]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pizza_0 at [143, 142, 171, 163] in auxiliary perspective is not visible in main perspective\\n- The pizza_1 visible in main perspective at [122, 136, 150, 155] corresponds to the same object visible in auxiliary perspective at [371, 136, 383, 147]\\n- The shoe_0 at [215, 132, 226, 155] in auxiliary perspective is not visible in main perspective\\n- The shoe_1 at [152, 134, 168, 160] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [],
"objects": [
"pizza_0",
"pizza_1",
"shoe_0",
"shoe_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9398_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABCEAABAwIEAgcGBQIFAwQD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many fork and bread do you need to move?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first fork at [295, 79, 304, 82]\\n- I also see a second fork at [160, 117, 163, 120]\\n- I can see the first bread at [277, 73, 296, 80]\\n- I also see a second bread at [151, 101, 166, 119]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a fork located at [104, 100, 120, 105]\\n- There's a bread positioned at coordinates [102, 103, 105, 107]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The fork_0 visible in main perspective at [295, 79, 304, 82] corresponds to the same object visible in auxiliary perspective at [104, 100, 120, 105]\\n- The fork_1 at [160, 117, 163, 120] in main perspective is not visible in auxiliary perspective\\n- The bread_0 visible in main perspective at [277, 73, 296, 80] corresponds to the same object visible in auxiliary perspective at [102, 103, 105, 107]\\n- The bread_1 at [151, 101, 166, 119] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 8,
"noise_objects": [],
"objects": [
"fork_0",
"fork_1",
"bread_0",
"bread_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch",
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "6857_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABLEAABAwIEAwQGBQkFBwQD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many banana can be seen in this task?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a banana located at [190, 86, 199, 92]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first banana at [0, 147, 8, 152]\\n- I also notice a second banana located at [234, 123, 257, 131]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The banana_0 visible in main perspective at [190, 86, 199, 92] corresponds to the same object visible in auxiliary perspective at [0, 147, 8, 152]\\n- The banana_1 at [234, 123, 257, 131] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"cardboardbox_noise0",
"bowl_noise1"
],
"objects": [
"banana_0",
"banana_1",
"cardboardbox_noise0",
"bowl_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy",
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7370_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QASBAAAgEDAwEGBAMGAwYE... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many cup are visible in this location?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first cup at [222, 68, 231, 75]\\n- I also see a second cup at [177, 16, 190, 26]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a cup located at [138, 116, 151, 130]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The cup_0 at [222, 68, 231, 75] in main perspective is not visible in auxiliary perspective\\n- The cup_1 at [138, 116, 151, 130] in auxiliary perspective is not visible in main perspective\\n- The cup_2 at [177, 16, 190, 26] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"clothes_iron_noise0",
"apple_noise1"
],
"objects": [
"cup_0",
"cup_1",
"cup_2",
"clothes_iron_noise0",
"apple_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9925_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQFBgf/xABCEAABAwIFAQYCCQMDAgUF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you identify all the pizza and pear?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first pizza at [76, 23, 77, 24]\\n- I also see a second pizza at [27, 24, 35, 28]\\n- There's also a third pizza positioned at [34, 3, 38, 6]\\n- A pear is visible at [32, 18, 35, 24]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a pizza located at [32, 19, 36, 21]\\n- There's a pear positioned at coordinates [37, 17, 40, 21]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pizza_0 visible in main perspective at [76, 23, 77, 24] corresponds to the same object visible in auxiliary perspective at [32, 19, 36, 21]\\n- The pizza_1 at [27, 24, 35, 28] in main perspective is not visible in auxiliary perspective\\n- The pizza_2 at [34, 3, 38, 6] in main perspective is not visible in auxiliary perspective\\n- The pear_0 at [37, 17, 40, 21] in auxiliary perspective is not visible in main perspective\\n- The pear_1 at [32, 18, 35, 24] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 5.\\n</think>\\n\\n\\\\boxed{5}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 4,
"noise_objects": [],
"objects": [
"pizza_0",
"pizza_1",
"pizza_2",
"pear_0",
"pear_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9877_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABJEAACAQIEAwUEBwcBBgMJ... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you determine the number of scissors and bowl?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a scissors located at [186, 69, 195, 76]\\n- There's a bowl positioned at coordinates [41, 87, 56, 95]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a scissors located at [157, 209, 168, 215]\\n- There's a bowl positioned at coordinates [238, 74, 244, 79]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The scissors_0 at [186, 69, 195, 76] in main perspective is not visible in auxiliary perspective\\n- The scissors_1 at [157, 209, 168, 215] in auxiliary perspective is not visible in main perspective\\n- The bowl_0 visible in main perspective at [41, 87, 56, 95] corresponds to the same object visible in auxiliary perspective at [238, 74, 244, 79]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [],
"objects": [
"scissors_0",
"scissors_1",
"bowl_0",
"bowl_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9540_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQFBgf/xABCEAACAQMCAwYDBgQDBwQD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many scissors are located here?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first scissors at [64, 22, 75, 26]\\n- I also see a second scissors at [45, 18, 46, 19]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first scissors at [29, 24, 35, 26]\\n- I also notice a second scissors located at [11, 23, 15, 24]\\n- Additionally, there's a third scissors at [42, 11, 46, 12]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The scissors_0 visible in main perspective at [64, 22, 75, 26] corresponds to the same object visible in auxiliary perspective at [29, 24, 35, 26]\\n- The scissors_1 visible in main perspective at [45, 18, 46, 19] corresponds to the same object visible in auxiliary perspective at [11, 23, 15, 24]\\n- The scissors_2 at [42, 11, 46, 12] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 2,
"noise_objects": [
"pear_noise0",
"pot_noise1"
],
"objects": [
"scissors_0",
"scissors_1",
"scissors_2",
"pear_noise0",
"pot_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2",
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "10020_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAEDBAUGAgf/xABEEAACAQMCAwUFBgQFAwME... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you list how many wine and kettle are available?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 0.\\n</think>\\n\\n\\\\boxed{0}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 4,
"noise_objects": [
"bowl_noise0",
"cooling_fan_noise1",
"bowl_noise2"
],
"objects": [
"bowl_noise0",
"cooling_fan_noise1",
"bowl_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9342_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQFBgf/xABBEAABAwIEAwYEBAYBAwIH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you identify all the banana and tomato?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a banana located at [147, 119, 162, 129]\\n- There's a tomato positioned at coordinates [228, 98, 236, 105]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a tomato located at [33, 113, 52, 123]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The banana_0 at [147, 119, 162, 129] in main perspective is not visible in auxiliary perspective\\n- The tomato_0 visible in main perspective at [228, 98, 236, 105] corresponds to the same object visible in auxiliary perspective at [33, 113, 52, 123]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"bowl_noise0",
"fork_noise1"
],
"objects": [
"banana_0",
"tomato_0",
"bowl_noise0",
"fork_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1",
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9511_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAIDBAUGAQcI/8QASxAAAQMCBAMFBAcFBAcI... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you assess how many clothes_iron are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a clothes located at [229, 78, 239, 97]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first clothes at [58, 99, 89, 116]\\n- I also notice a second clothes located at [242, 113, 283, 134]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The clothes_iron_0 visible in main perspective at [229, 78, 239, 97] corresponds to the same object visible in auxiliary perspective at [58, 99, 89, 116]\\n- The clothes_iron_1 at [242, 113, 283, 134] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"green_peas_noise0",
"bread_noise1"
],
"objects": [
"clothes_iron_0",
"clothes_iron_1",
"green_peas_noise0",
"bread_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c",
"stompy"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8828_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQFBgf/xAA/EAABAwMCAwUFBgQFBAMA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the count of wine in the scene?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first wine at [220, 87, 229, 111]\\n- I also see a second wine at [269, 17, 286, 50]\\n- There's also a third wine positioned at [151, 104, 163, 129]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first wine at [0, 114, 16, 136]\\n- I also notice a second wine located at [215, 81, 222, 107]\\n- Additionally, there's a third wine at [59, 17, 80, 51]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wine_0 visible in main perspective at [220, 87, 229, 111] corresponds to the same object visible in auxiliary perspective at [0, 114, 16, 136]\\n- The wine_1 at [215, 81, 222, 107] in auxiliary perspective is not visible in main perspective\\n- The wine_2 visible in main perspective at [269, 17, 286, 50] corresponds to the same object visible in auxiliary perspective at [59, 17, 80, 51]\\n- The wine_3 at [151, 104, 163, 129] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [],
"objects": [
"wine_0",
"wine_1",
"wine_2",
"wine_3"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9986_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAQACAwQFBgf/xABBEAABAwIEAwYDBwMBCAID... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many cup and clothes_iron can you find?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a cup located at [43, 22, 48, 25]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The cup_0 at [43, 22, 48, 25] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_0",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 4,
"noise_objects": [
"wooden_cutting_board_noise0",
"spoon_noise1",
"bowl_noise2"
],
"objects": [
"cup_0",
"wooden_cutting_board_noise0",
"spoon_noise1",
"bowl_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c",
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "4649_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAQIAAwQFBgf/xABBEAABBAAEAwUFBgQFBAID... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you assess how many fork are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a fork located at [212, 99, 228, 106]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first fork at [201, 123, 210, 143]\\n- I also notice a second fork located at [0, 130, 35, 144]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The fork_0 at [201, 123, 210, 143] in auxiliary perspective is not visible in main perspective\\n- The fork_1 visible in main perspective at [212, 99, 228, 106] corresponds to the same object visible in auxiliary perspective at [0, 130, 35, 144]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 2,
"noise_objects": [
"pizza_noise0",
"scissors_noise1"
],
"objects": [
"fork_0",
"fork_1",
"pizza_noise0",
"scissors_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9834_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAIDBAUGAQcI/8QATRAAAQMDAgMEBggBCAcI... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many pear can you find?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a pear located at [255, 76, 264, 89]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first pear at [91, 85, 102, 98]\\n- I also notice a second pear located at [267, 136, 293, 159]\\n- Additionally, there's a third pear at [193, 32, 199, 46]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pear_0 visible in main perspective at [255, 76, 264, 89] corresponds to the same object visible in auxiliary perspective at [91, 85, 102, 98]\\n- The pear_1 at [267, 136, 293, 159] in auxiliary perspective is not visible in main perspective\\n- The pear_2 at [193, 32, 199, 46] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"shoe_noise0",
"tomato_noise1"
],
"objects": [
"pear_0",
"pear_1",
"pear_2",
"shoe_noise0",
"tomato_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8055_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwUEBgf/xABAEAABAwIEAwYEBAMIAgID... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the number of bowl to be counted?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a bowl located at [250, 97, 258, 103]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first bowl at [80, 104, 93, 111]\\n- I also notice a second bowl located at [218, 98, 226, 104]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The bowl_0 visible in main perspective at [250, 97, 258, 103] corresponds to the same object visible in auxiliary perspective at [80, 104, 93, 111]\\n- The bowl_1 at [218, 98, 226, 104] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"scissors_noise0",
"pot_noise1"
],
"objects": [
"bowl_0",
"bowl_1",
"scissors_noise0",
"pot_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8119_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwUEBgf/xABBEAABAwMCAwYCCAUDAwQD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you calculate how many fork are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a fork located at [181, 97, 206, 100]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a fork located at [280, 124, 286, 160]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The fork_0 at [280, 124, 286, 160] in auxiliary perspective is not visible in main perspective\\n- The fork_1 at [181, 97, 206, 100] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 4,
"noise_objects": [
"clothes_iron_noise0",
"wine_noise1"
],
"objects": [
"fork_0",
"fork_1",
"clothes_iron_noise0",
"wine_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8595_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECBAUDBgf/xABGEAABAwMCBAMFBgMGAwcF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you count the clothes_iron?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first clothes at [317, 78, 335, 93]\\n- I also see a second clothes at [123, 90, 153, 108]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first clothes at [137, 89, 148, 106]\\n- I also notice a second clothes located at [163, 36, 177, 51]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The clothes_iron_0 visible in main perspective at [317, 78, 335, 93] corresponds to the same object visible in auxiliary perspective at [137, 89, 148, 106]\\n- The clothes_iron_1 at [123, 90, 153, 108] in main perspective is not visible in auxiliary perspective\\n- The clothes_iron_2 at [163, 36, 177, 51] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 8,
"noise_objects": [
"scissors_noise0",
"pumpkin_noise1"
],
"objects": [
"clothes_iron_0",
"clothes_iron_1",
"clothes_iron_2",
"scissors_noise0",
"pumpkin_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch",
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9614_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAwADAQEAAAAAAAAAAAAAAAECAwQFBgf/xABFEAABAwIDBAYHBgQEBQUA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many banana are located here?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first banana at [17, 135, 31, 148]\\n- I also see a second banana at [142, 138, 154, 158]\\n- There's also a third banana positioned at [136, 94, 147, 103]\\n- Another banana is located at [46, 126, 56, 137]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first banana at [253, 135, 277, 148]\\n- I also notice a second banana located at [378, 138, 383, 142]\\n- Additionally, there's a third banana at [259, 128, 277, 137]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The banana_0 visible in main perspective at [17, 135, 31, 148] corresponds to the same object visible in auxiliary perspective at [253, 135, 277, 148]\\n- The banana_1 visible in main perspective at [142, 138, 154, 158] corresponds to the same object visible in auxiliary perspective at [378, 138, 383, 142]\\n- The banana_2 at [136, 94, 147, 103] in main perspective is not visible in auxiliary perspective\\n- The banana_3 visible in main perspective at [46, 126, 56, 137] corresponds to the same object visible in auxiliary perspective at [259, 128, 277, 137]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_4",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [],
"objects": [
"banana_0",
"banana_1",
"banana_2",
"banana_3"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1",
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "6727_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QARxAAAQMCBAIHBQUECAYC... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the exact number of meat and kettle?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first meat at [284, 100, 290, 104]\\n- I also see a second meat at [227, 100, 234, 104]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a meat located at [126, 115, 131, 117]\\n- There's a kettle positioned at coordinates [213, 112, 232, 140]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The meat_0 visible in main perspective at [284, 100, 290, 104] corresponds to the same object visible in auxiliary perspective at [126, 115, 131, 117]\\n- The meat_1 at [227, 100, 234, 104] in main perspective is not visible in auxiliary perspective\\n- The kettle_0 at [213, 112, 232, 140] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 2,
"noise_objects": [
"pot_noise0",
"fork_noise1"
],
"objects": [
"meat_0",
"meat_1",
"kettle_0",
"pot_noise0",
"fork_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch",
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9379_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QARBAAAQMCBAMFBQYEBAYB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you list how many scissors and kettle are available?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first scissors at [366, 103, 383, 110]\\n- I also see a second scissors at [142, 119, 177, 135]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a scissors located at [168, 92, 179, 97]\\n- There's a kettle positioned at coordinates [167, 84, 175, 92]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The scissors_0 visible in main perspective at [366, 103, 383, 110] corresponds to the same object visible in auxiliary perspective at [168, 92, 179, 97]\\n- The scissors_1 at [142, 119, 177, 135] in main perspective is not visible in auxiliary perspective\\n- The kettle_0 at [167, 84, 175, 92] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 8,
"noise_objects": [
"clothes_iron_noise0",
"pumpkin_noise1"
],
"objects": [
"scissors_0",
"scissors_1",
"kettle_0",
"clothes_iron_noise0",
"pumpkin_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c",
"stompy"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9890_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAAcBAQAAAAAAAAAAAAAAAAECAwQFBgcI/8QAShAAAQMCBAQDBAkBBgMF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wine and shoe are there?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wine located at [34, 10, 35, 15]\\n- There's a shoe positioned at coordinates [22, 15, 24, 17]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first wine at [70, 25, 76, 29]\\n- I also notice a second wine located at [7, 30, 16, 35]\\n- I notice a shoe at [55, 18, 58, 20]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wine_0 visible in main perspective at [34, 10, 35, 15] corresponds to the same object visible in auxiliary perspective at [70, 25, 76, 29]\\n- The wine_1 at [7, 30, 16, 35] in auxiliary perspective is not visible in main perspective\\n- The shoe_0 visible in main perspective at [22, 15, 24, 17] corresponds to the same object visible in auxiliary perspective at [55, 18, 58, 20]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"clothes_iron_noise0",
"pumpkin_noise1"
],
"objects": [
"wine_0",
"wine_1",
"shoe_0",
"clothes_iron_noise0",
"pumpkin_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9565_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QAQhAAAQMCBAMFBQYEBgIB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wooden_cutting_board and kettle do you need to move?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wooden located at [51, 84, 79, 95]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wooden located at [239, 75, 256, 83]\\n- There's a kettle positioned at coordinates [210, 51, 216, 61]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wooden_cutting_board_0 visible in main perspective at [51, 84, 79, 95] corresponds to the same object visible in auxiliary perspective at [239, 75, 256, 83]\\n- The kettle_0 at [210, 51, 216, 61] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"clothes_iron_noise0",
"cup_noise1"
],
"objects": [
"wooden_cutting_board_0",
"kettle_0",
"clothes_iron_noise0",
"cup_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch",
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7177_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAAcBAQAAAAAAAAAAAAAAAAECAwQFBgcI/8QASBAAAQMCBAMFBQYDBgUB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Could you tell me how many wine and apple exist?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wine located at [213, 71, 224, 102]\\n- There's a apple positioned at coordinates [193, 62, 198, 69]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wine located at [162, 107, 180, 158]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wine_0 at [213, 71, 224, 102] in main perspective is not visible in auxiliary perspective\\n- The wine_1 at [162, 107, 180, 158] in auxiliary perspective is not visible in main perspective\\n- The apple_0 at [193, 62, 198, 69] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 3,
"noise_objects": [
"scissors_noise0",
"green_peas_noise1"
],
"objects": [
"wine_0",
"wine_1",
"apple_0",
"scissors_noise0",
"green_peas_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch",
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9342_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABFEAABAwIEAwUFBgMGBgEF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you assess how many fork and shoe are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a fork located at [243, 121, 274, 151]\\n- There's a shoe positioned at coordinates [184, 60, 198, 67]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a shoe located at [370, 83, 383, 94]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The fork_0 at [243, 121, 274, 151] in main perspective is not visible in auxiliary perspective\\n- The shoe_0 visible in main perspective at [184, 60, 198, 67] corresponds to the same object visible in auxiliary perspective at [370, 83, 383, 94]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 3,
"noise_objects": [
"bowl_noise0",
"rock_noise1"
],
"objects": [
"fork_0",
"shoe_0",
"bowl_noise0",
"rock_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8740_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAgMBAQEBAAAAAAAAAAAAAAECBAUDBgcI/8QAQBAAAQMCBAMGBAQEBgEE... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Please identify the number of kettle.'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first kettle at [196, 94, 211, 108]\\n- I also see a second kettle at [275, 42, 279, 49]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first kettle at [239, 100, 254, 120]\\n- I also notice a second kettle located at [99, 49, 104, 55]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The kettle_0 at [196, 94, 211, 108] in main perspective is not visible in auxiliary perspective\\n- The kettle_1 at [239, 100, 254, 120] in auxiliary perspective is not visible in main perspective\\n- The kettle_2 visible in main perspective at [275, 42, 279, 49] corresponds to the same object visible in auxiliary perspective at [99, 49, 104, 55]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"spoon_noise0",
"fork_noise1"
],
"objects": [
"kettle_0",
"kettle_1",
"kettle_2",
"spoon_noise0",
"fork_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8657_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAEDBAUGAgf/xABGEAABAwIEBAQCBwYEBQIH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many bowl are needed for this operation?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first bowl at [126, 77, 136, 84]\\n- I also see a second bowl at [206, 16, 215, 23]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first bowl at [290, 101, 302, 108]\\n- I also notice a second bowl located at [200, 165, 215, 182]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The bowl_0 visible in main perspective at [126, 77, 136, 84] corresponds to the same object visible in auxiliary perspective at [290, 101, 302, 108]\\n- The bowl_1 at [200, 165, 215, 182] in auxiliary perspective is not visible in main perspective\\n- The bowl_2 at [206, 16, 215, 23] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"peach_noise0",
"wooden_cutting_board_noise1"
],
"objects": [
"bowl_0",
"bowl_1",
"bowl_2",
"peach_noise0",
"wooden_cutting_board_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c",
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8383_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAgABAwQFBgf/xABFEAACAQMCBAIHBgUCBAMJ... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many pumpkin and hammer are available for use?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first pumpkin at [342, 130, 383, 158]\\n- I also see a second pumpkin at [137, 105, 161, 124]\\n- There's also a third pumpkin positioned at [102, 21, 142, 50]\\n- I can see the first hammer at [330, 112, 360, 127]\\n- I also see a second hammer at [200, 83, 206, 93]\\n- There's also a third hammer positioned at [153, 25, 161, 47]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a pumpkin located at [139, 100, 159, 114]\\n- There's a hammer positioned at coordinates [131, 97, 144, 105]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pumpkin_0 visible in main perspective at [342, 130, 383, 158] corresponds to the same object visible in auxiliary perspective at [139, 100, 159, 114]\\n- The pumpkin_1 at [137, 105, 161, 124] in main perspective is not visible in auxiliary perspective\\n- The pumpkin_2 at [102, 21, 142, 50] in main perspective is not visible in auxiliary perspective\\n- The hammer_0 visible in main perspective at [330, 112, 360, 127] corresponds to the same object visible in auxiliary perspective at [131, 97, 144, 105]\\n- The hammer_1 at [200, 83, 206, 93] in main perspective is not visible in auxiliary perspective\\n- The hammer_2 at [153, 25, 161, 47] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 6.\\n</think>\\n\\n\\\\boxed{6}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_4",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 5,
"noise_objects": [],
"objects": [
"pumpkin_0",
"pumpkin_1",
"pumpkin_2",
"hammer_0",
"hammer_1",
"hammer_2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "6814_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAwADAQEAAAAAAAAAAAAAAAECAwQFBgf/xABFEAABAwIDBQUFBQUHBAID... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the total number of peach?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first peach at [251, 89, 260, 96]\\n- I also see a second peach at [267, 40, 272, 48]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first peach at [90, 96, 101, 104]\\n- I also notice a second peach located at [203, 122, 212, 135]\\n- Additionally, there's a third peach at [80, 45, 89, 54]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The peach_0 visible in main perspective at [251, 89, 260, 96] corresponds to the same object visible in auxiliary perspective at [90, 96, 101, 104]\\n- The peach_1 at [203, 122, 212, 135] in auxiliary perspective is not visible in main perspective\\n- The peach_2 visible in main perspective at [267, 40, 272, 48] corresponds to the same object visible in auxiliary perspective at [80, 45, 89, 54]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"pear_noise0",
"scissors_noise1"
],
"objects": [
"peach_0",
"peach_1",
"peach_2",
"pear_noise0",
"scissors_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7243_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
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{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many tomato are visible in this location?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 0.\\n</think>\\n\\n\\\\boxed{0}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"hammer_noise0",
"clothes_iron_noise1",
"kettle_noise2"
],
"objects": [
"hammer_noise0",
"clothes_iron_noise1",
"kettle_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy",
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8346_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECBAUGAwcI/8QARBAAAQMCBAMFBQYEBQMD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many scissors and bread can you find?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a scissors located at [189, 68, 198, 76]\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The scissors_0 at [189, 68, 198, 76] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"banana_noise0",
"pumpkin_noise1",
"hammer_noise2"
],
"objects": [
"scissors_0",
"banana_noise0",
"pumpkin_noise1",
"hammer_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8105_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgIDAQAAAAAAAAAAAAAAAAECBgMEBQf/xABHEAABAwIEAgcGAwYFAgQH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you list how many clothes_iron are available?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a clothes located at [234, 51, 251, 92]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a clothes located at [120, 129, 143, 170]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The clothes_iron_0 at [120, 129, 143, 170] in auxiliary perspective is not visible in main perspective\\n- The clothes_iron_1 at [234, 51, 251, 92] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 1,
"noise_objects": [
"pumpkin_noise0",
"pizza_noise1"
],
"objects": [
"clothes_iron_0",
"clothes_iron_1",
"pumpkin_noise0",
"pizza_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2",
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8091_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABMEAABAwIEAgYJAQQFCwIH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you identify all the plate?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a plate located at [215, 87, 236, 95]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first plate at [41, 110, 80, 127]\\n- I also notice a second plate located at [253, 110, 285, 126]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The plate_0 visible in main perspective at [215, 87, 236, 95] corresponds to the same object visible in auxiliary perspective at [41, 110, 80, 127]\\n- The plate_1 at [253, 110, 285, 126] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"green_peas_noise0",
"pot_noise1"
],
"objects": [
"plate_0",
"plate_1",
"green_peas_noise0",
"pot_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "10067_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABOEAACAAQEAgYFCQQGCQQD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Please estimate the total number of pizza and clothes_iron.'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first pizza at [0, 133, 35, 150]\\n- I also see a second pizza at [130, 136, 156, 153]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first pizza at [246, 133, 274, 150]\\n- I also notice a second pizza located at [374, 135, 383, 144]\\n- I notice a clothes at [163, 134, 179, 184]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pizza_0 visible in main perspective at [0, 133, 35, 150] corresponds to the same object visible in auxiliary perspective at [246, 133, 274, 150]\\n- The pizza_1 visible in main perspective at [130, 136, 156, 153] corresponds to the same object visible in auxiliary perspective at [374, 135, 383, 144]\\n- The clothes_iron_0 at [163, 134, 179, 184] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"bread_noise0",
"tomato_noise1"
],
"objects": [
"pizza_0",
"pizza_1",
"clothes_iron_0",
"bread_noise0",
"tomato_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9801_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QAQRAAAQMCAwQIBAUCBQQC... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the quantity of pumpkin and bread in this area?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first pumpkin at [337, 88, 367, 101]\\n- I also see a second pumpkin at [136, 112, 163, 134]\\n- I can see the first bread at [328, 87, 349, 93]\\n- I also see a second bread at [137, 78, 147, 87]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first pumpkin at [152, 89, 168, 100]\\n- I also notice a second pumpkin located at [160, 39, 178, 52]\\n- I notice a bread at [141, 92, 154, 99]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pumpkin_0 visible in main perspective at [337, 88, 367, 101] corresponds to the same object visible in auxiliary perspective at [152, 89, 168, 100]\\n- The pumpkin_1 at [136, 112, 163, 134] in main perspective is not visible in auxiliary perspective\\n- The pumpkin_2 at [160, 39, 178, 52] in auxiliary perspective is not visible in main perspective\\n- The bread_0 visible in main perspective at [328, 87, 349, 93] corresponds to the same object visible in auxiliary perspective at [141, 92, 154, 99]\\n- The bread_1 at [137, 78, 147, 87] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 5.\\n</think>\\n\\n\\\\boxed{5}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 8,
"noise_objects": [],
"objects": [
"pumpkin_0",
"pumpkin_1",
"pumpkin_2",
"bread_0",
"bread_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9004_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECBAUGAwf/xABIEAABAwIEAggDBQYCCQMF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many bread are needed for this operation?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a bread located at [155, 85, 178, 92]\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The bread_0 at [155, 85, 178, 92] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_4",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"hammer_noise0",
"apple_noise1",
"bowl_noise2"
],
"objects": [
"bread_0",
"hammer_noise0",
"apple_noise1",
"bowl_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2",
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "6949_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAIBAwQFBgf/xABAEAACAQIEAwUECQMDBAID... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many scissors and green_peas are needed for this operation?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a scissors located at [160, 110, 185, 131]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a scissors located at [198, 115, 242, 136]\\n- There's a green positioned at coordinates [183, 104, 201, 111]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The scissors_0 at [198, 115, 242, 136] in auxiliary perspective is not visible in main perspective\\n- The scissors_1 at [160, 110, 185, 131] in main perspective is not visible in auxiliary perspective\\n- The green_peas_0 at [183, 104, 201, 111] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 4,
"noise_objects": [
"shoe_noise0",
"hammer_noise1"
],
"objects": [
"scissors_0",
"scissors_1",
"green_peas_0",
"shoe_noise0",
"hammer_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch",
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8934_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAIBAwYFBAf/xABJEAABAwIEAgYGBwQHCAMB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many fork and shoe can you find?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a fork located at [141, 138, 172, 142]\\n- There's a shoe positioned at coordinates [0, 135, 17, 147]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first fork at [156, 145, 190, 149]\\n- I also notice a second fork located at [377, 140, 383, 142]\\n- I notice a shoe at [254, 135, 275, 160]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The fork_0 at [156, 145, 190, 149] in auxiliary perspective is not visible in main perspective\\n- The fork_1 visible in main perspective at [141, 138, 172, 142] corresponds to the same object visible in auxiliary perspective at [377, 140, 383, 142]\\n- The shoe_0 visible in main perspective at [0, 135, 17, 147] corresponds to the same object visible in auxiliary perspective at [254, 135, 275, 160]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"pizza_noise0",
"bread_noise1"
],
"objects": [
"fork_0",
"fork_1",
"shoe_0",
"pizza_noise0",
"bread_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch",
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9553_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAgMBAQEBAAAAAAAAAAAAAQIAAwYEBwUI/8QARxAAAQMCBAMFBgIGCAUE... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the number of wooden_cutting_board and apple to be counted?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wooden located at [202, 87, 228, 111]\\n- There's a apple positioned at coordinates [107, 87, 122, 99]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first wooden at [112, 136, 145, 155]\\n- I also notice a second wooden located at [246, 73, 289, 80]\\n- I notice a apple at [93, 132, 107, 143]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wooden_cutting_board_0 at [112, 136, 145, 155] in auxiliary perspective is not visible in main perspective\\n- The wooden_cutting_board_1 at [202, 87, 228, 111] in main perspective is not visible in auxiliary perspective\\n- The wooden_cutting_board_2 at [246, 73, 289, 80] in auxiliary perspective is not visible in main perspective\\n- The apple_0 at [93, 132, 107, 143] in auxiliary perspective is not visible in main perspective\\n- The apple_1 at [107, 87, 122, 99] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 5.\\n</think>\\n\\n\\\\boxed{5}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 1,
"noise_objects": [],
"objects": [
"wooden_cutting_board_0",
"wooden_cutting_board_1",
"wooden_cutting_board_2",
"apple_0",
"apple_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7453_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABMEAABAwIEAgcHAQQFCgQH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Please estimate the total number of tomato.'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first tomato at [187, 81, 195, 88]\\n- I also see a second tomato at [240, 82, 249, 90]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first tomato at [250, 133, 268, 149]\\n- I also notice a second tomato located at [190, 39, 197, 46]\\n- Additionally, there's a third tomato at [76, 97, 89, 106]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The tomato_0 at [187, 81, 195, 88] in main perspective is not visible in auxiliary perspective\\n- The tomato_1 at [250, 133, 268, 149] in auxiliary perspective is not visible in main perspective\\n- The tomato_2 at [190, 39, 197, 46] in auxiliary perspective is not visible in main perspective\\n- The tomato_3 visible in main perspective at [240, 82, 249, 90] corresponds to the same object visible in auxiliary perspective at [76, 97, 89, 106]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [],
"objects": [
"tomato_0",
"tomato_1",
"tomato_2",
"tomato_3"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda",
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9776_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAEDBAUGAgcI/8QARBAAAQMDAwIEAwYEBAUE... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many hammer are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first hammer at [67, 23, 73, 26]\\n- I also see a second hammer at [27, 23, 28, 26]\\n- There's also a third hammer positioned at [33, 4, 34, 8]\\n- Another hammer is located at [68, 24, 75, 28]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first hammer at [26, 19, 29, 21]\\n- I also notice a second hammer located at [27, 19, 30, 21]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The hammer_0 visible in main perspective at [67, 23, 73, 26] corresponds to the same object visible in auxiliary perspective at [26, 19, 29, 21]\\n- The hammer_1 at [27, 23, 28, 26] in main perspective is not visible in auxiliary perspective\\n- The hammer_2 at [33, 4, 34, 8] in main perspective is not visible in auxiliary perspective\\n- The hammer_3 visible in main perspective at [68, 24, 75, 28] corresponds to the same object visible in auxiliary perspective at [27, 19, 30, 21]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 5,
"noise_objects": [],
"objects": [
"hammer_0",
"hammer_1",
"hammer_2",
"hammer_3"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9066_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQFBgf/xABBEAABAwIEAwYDBgQEBQUA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many cup are needed for this operation?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a cup located at [164, 99, 179, 111]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a cup located at [178, 96, 196, 109]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The cup_0 at [178, 96, 196, 109] in auxiliary perspective is not visible in main perspective\\n- The cup_1 at [164, 99, 179, 111] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 4,
"noise_objects": [
"bread_noise0",
"pumpkin_noise1"
],
"objects": [
"cup_0",
"cup_1",
"bread_noise0",
"pumpkin_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "6660_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAgABAwQFBgf/xABFEAACAQMCBAIHBwIEBQMD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wooden_cutting_board and apple can you find?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wooden located at [333, 122, 372, 150]\\n- There's a apple positioned at coordinates [345, 118, 365, 128]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wooden located at [134, 104, 155, 114]\\n- There's a apple positioned at coordinates [138, 98, 147, 106]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wooden_cutting_board_0 visible in main perspective at [333, 122, 372, 150] corresponds to the same object visible in auxiliary perspective at [134, 104, 155, 114]\\n- The apple_0 visible in main perspective at [345, 118, 365, 128] corresponds to the same object visible in auxiliary perspective at [138, 98, 147, 106]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 5,
"noise_objects": [
"pear_noise0",
"cooling_fan_noise1"
],
"objects": [
"wooden_cutting_board_0",
"apple_0",
"pear_noise0",
"cooling_fan_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7344_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABGEAACAQMCAwYDBQYFBAAE... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you calculate how many plate are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a plate located at [339, 123, 383, 150]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a plate located at [135, 102, 158, 111]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The plate_0 visible in main perspective at [339, 123, 383, 150] corresponds to the same object visible in auxiliary perspective at [135, 102, 158, 111]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 5,
"noise_objects": [
"banana_noise0",
"cardboardbox_noise1",
"green_peas_noise2"
],
"objects": [
"plate_0",
"banana_noise0",
"cardboardbox_noise1",
"green_peas_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch",
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9647_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAIDBAUGAQcI/8QAShAAAQMCBAMFBAcFBQUI... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wine and apple can be seen in this task?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wine located at [199, 67, 204, 86]\\n- There's a apple positioned at coordinates [204, 82, 211, 90]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first wine at [0, 133, 1, 135]\\n- I also notice a second wine located at [232, 89, 246, 125]\\n- In this view, I can see the first apple at [3, 125, 28, 138]\\n- I also notice a second apple located at [228, 89, 235, 96]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wine_0 visible in main perspective at [199, 67, 204, 86] corresponds to the same object visible in auxiliary perspective at [0, 133, 1, 135]\\n- The wine_1 at [232, 89, 246, 125] in auxiliary perspective is not visible in main perspective\\n- The apple_0 visible in main perspective at [204, 82, 211, 90] corresponds to the same object visible in auxiliary perspective at [3, 125, 28, 138]\\n- The apple_1 at [228, 89, 235, 96] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [],
"objects": [
"wine_0",
"wine_1",
"apple_0",
"apple_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy",
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8161_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAAcBAQAAAAAAAAAAAAAAAAECAwQFBgcI/8QAShAAAQMCBAQDBAgDBQUG... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many fork do you observe?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first fork at [124, 78, 145, 83]\\n- I also see a second fork at [175, 20, 198, 24]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first fork at [286, 101, 312, 113]\\n- I also notice a second fork located at [169, 111, 181, 127]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The fork_0 visible in main perspective at [124, 78, 145, 83] corresponds to the same object visible in auxiliary perspective at [286, 101, 312, 113]\\n- The fork_1 at [169, 111, 181, 127] in auxiliary perspective is not visible in main perspective\\n- The fork_2 at [175, 20, 198, 24] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"hammer_noise0",
"kettle_noise1"
],
"objects": [
"fork_0",
"fork_1",
"fork_2",
"hammer_noise0",
"kettle_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8288_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QAShAAAQMCBAIGCAIIAwcC... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many fork and green_peas are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 0.\\n</think>\\n\\n\\\\boxed{0}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"bowl_noise0",
"banana_noise1",
"clothes_iron_noise2"
],
"objects": [
"bowl_noise0",
"banana_noise1",
"clothes_iron_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1",
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8672_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QAShAAAQMDAwEFBQUFBAgD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you calculate how many wine and kettle are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 0.\\n</think>\\n\\n\\\\boxed{0}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_4",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"hammer_noise0",
"peach_noise1",
"bowl_noise2"
],
"objects": [
"hammer_noise0",
"peach_noise1",
"bowl_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2",
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "6944_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABLEAABAwIDBQQGBgYGCQUA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the number of pizza and bread to be counted?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a pizza located at [172, 84, 186, 88]\\n- There's a bread positioned at coordinates [210, 84, 233, 91]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a pizza located at [229, 95, 242, 102]\\n- There's a bread positioned at coordinates [23, 110, 72, 131]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pizza_0 at [172, 84, 186, 88] in main perspective is not visible in auxiliary perspective\\n- The pizza_1 at [229, 95, 242, 102] in auxiliary perspective is not visible in main perspective\\n- The bread_0 visible in main perspective at [210, 84, 233, 91] corresponds to the same object visible in auxiliary perspective at [23, 110, 72, 131]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"cardboardbox_noise0",
"cooling_fan_noise1"
],
"objects": [
"pizza_0",
"pizza_1",
"bread_0",
"cardboardbox_noise0",
"cooling_fan_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda",
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "10036_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQFBgf/xABBEAABAwIEBAQDBgUBBgcA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you determine the number of wine and bowl?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wine located at [183, 67, 193, 107]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wine located at [219, 74, 234, 113]\\n- There's a bowl positioned at coordinates [250, 124, 277, 144]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wine_0 at [219, 74, 234, 113] in auxiliary perspective is not visible in main perspective\\n- The wine_1 at [183, 67, 193, 107] in main perspective is not visible in auxiliary perspective\\n- The bowl_0 at [250, 124, 277, 144] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 4,
"noise_objects": [
"pizza_noise0",
"cooling_fan_noise1"
],
"objects": [
"wine_0",
"wine_1",
"bowl_0",
"pizza_noise0",
"cooling_fan_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda",
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9308_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgIDAQAAAAAAAAAAAAAAAAECBgQFBwP/xABGEAABAwIEAwUFBQYDBgcB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wooden_cutting_board and bread can be seen in this task?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wooden located at [182, 45, 204, 65]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wooden located at [99, 138, 134, 157]\\n- There's a bread positioned at coordinates [84, 128, 117, 141]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wooden_cutting_board_0 at [99, 138, 134, 157] in auxiliary perspective is not visible in main perspective\\n- The wooden_cutting_board_1 at [182, 45, 204, 65] in main perspective is not visible in auxiliary perspective\\n- The bread_0 at [84, 128, 117, 141] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 1,
"noise_objects": [
"knife_noise0",
"pizza_noise1"
],
"objects": [
"wooden_cutting_board_0",
"wooden_cutting_board_1",
"bread_0",
"knife_noise0",
"pizza_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9947_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAwEBAQEBAAAAAAAAAAAAAAECAwUEBgf/xABEEAABAwMDAQUEBwUFBwUA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wine and green_peas are needed for this operation?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wine located at [113, 119, 129, 140]\\n- There's a green positioned at coordinates [115, 134, 137, 140]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wine_0 at [113, 119, 129, 140] in auxiliary perspective is not visible in main perspective\\n- The green_peas_0 at [115, 134, 137, 140] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 1,
"noise_objects": [
"plate_noise0",
"pizza_noise1"
],
"objects": [
"wine_0",
"green_peas_0",
"plate_noise0",
"pizza_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8571_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGgAAAgMBAQAAAAAAAAAAAAAAAAECAwQFBv/EAEMQAAEEAAQCBgYHBgQHAQAA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the exact number of wooden_cutting_board and pear?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wooden located at [249, 95, 269, 106]\\n- There's a pear positioned at coordinates [205, 95, 213, 107]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first wooden at [85, 102, 111, 111]\\n- I also notice a second wooden located at [198, 114, 213, 127]\\n- I notice a pear at [202, 118, 213, 138]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wooden_cutting_board_0 visible in main perspective at [249, 95, 269, 106] corresponds to the same object visible in auxiliary perspective at [85, 102, 111, 111]\\n- The wooden_cutting_board_1 at [198, 114, 213, 127] in auxiliary perspective is not visible in main perspective\\n- The pear_0 at [205, 95, 213, 107] in main perspective is not visible in auxiliary perspective\\n- The pear_1 at [202, 118, 213, 138] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [],
"objects": [
"wooden_cutting_board_0",
"wooden_cutting_board_1",
"pear_0",
"pear_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8706_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QAQhAAAQMCBAIHBQYFAwMF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Please estimate the total number of apple.'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a apple located at [205, 109, 213, 117]\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The apple_0 at [205, 109, 213, 117] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"plate_noise0",
"wine_noise1",
"pumpkin_noise2"
],
"objects": [
"apple_0",
"plate_noise0",
"wine_noise1",
"pumpkin_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9189_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABHEAACAQIDBAUJBQYFAwQD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you determine the number of hammer?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a hammer located at [30, 28, 34, 31]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a hammer located at [49, 28, 54, 31]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The hammer_0 at [49, 28, 54, 31] in auxiliary perspective is not visible in main perspective\\n- The hammer_1 at [30, 28, 34, 31] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_0",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"bread_noise0",
"bowl_noise1"
],
"objects": [
"hammer_0",
"hammer_1",
"bread_noise0",
"bowl_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "5366_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgIDAQAAAAAAAAAAAAAAAQIAAwQFBgf/xABJEAACAQIEAwUEBggEBAQH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many cup and hammer do you need to move?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a cup located at [0, 137, 10, 151]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a cup located at [252, 137, 271, 154]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The cup_0 visible in main perspective at [0, 137, 10, 151] corresponds to the same object visible in auxiliary perspective at [252, 137, 271, 154]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"pear_noise0",
"bowl_noise1",
"scissors_noise2"
],
"objects": [
"cup_0",
"pear_noise0",
"bowl_noise1",
"scissors_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9086_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABEEAABAwMCAwUGBAMHAgUF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you calculate how many banana and bread are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first banana at [364, 97, 380, 106]\\n- I also see a second banana at [137, 82, 151, 87]\\n- I can see the first bread at [303, 84, 332, 94]\\n- I also see a second bread at [134, 115, 153, 143]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first banana at [161, 92, 173, 95]\\n- I also notice a second banana located at [166, 50, 172, 52]\\n- In this view, I can see the first bread at [124, 98, 151, 107]\\n- I also notice a second bread located at [154, 46, 167, 56]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The banana_0 visible in main perspective at [364, 97, 380, 106] corresponds to the same object visible in auxiliary perspective at [161, 92, 173, 95]\\n- The banana_1 at [137, 82, 151, 87] in main perspective is not visible in auxiliary perspective\\n- The banana_2 at [166, 50, 172, 52] in auxiliary perspective is not visible in main perspective\\n- The bread_0 visible in main perspective at [303, 84, 332, 94] corresponds to the same object visible in auxiliary perspective at [124, 98, 151, 107]\\n- The bread_1 at [134, 115, 153, 143] in main perspective is not visible in auxiliary perspective\\n- The bread_2 at [154, 46, 167, 56] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 6.\\n</think>\\n\\n\\\\boxed{6}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 8,
"noise_objects": [],
"objects": [
"banana_0",
"banana_1",
"banana_2",
"bread_0",
"bread_1",
"bread_2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "10000_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgIDAQAAAAAAAAAAAAAAAQIAAwQFBgf/xABKEAACAQIEAwUFBQUGAwUJ... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many plate are there in this space?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a plate located at [217, 145, 254, 175]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The plate_0 at [217, 145, 254, 175] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"wooden_cutting_board_noise0",
"shoe_noise1",
"pumpkin_noise2"
],
"objects": [
"plate_0",
"wooden_cutting_board_noise0",
"shoe_noise1",
"pumpkin_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8750_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
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{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wine can be seen in this task?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first wine at [69, 14, 73, 18]\\n- I also see a second wine at [29, 24, 33, 34]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wine located at [29, 15, 31, 18]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wine_0 visible in main perspective at [69, 14, 73, 18] corresponds to the same object visible in auxiliary perspective at [29, 15, 31, 18]\\n- The wine_1 at [29, 24, 33, 34] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_0",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 8,
"noise_objects": [
"rock_noise0",
"meat_noise1"
],
"objects": [
"wine_0",
"wine_1",
"rock_noise0",
"meat_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "5193_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QAQBAAAQMCBAIIAwcDBAIB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Please estimate the total number of plate.'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a plate located at [46, 20, 50, 23]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first plate at [7, 23, 13, 25]\\n- I also notice a second plate located at [44, 19, 48, 20]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The plate_0 visible in main perspective at [46, 20, 50, 23] corresponds to the same object visible in auxiliary perspective at [7, 23, 13, 25]\\n- The plate_1 at [44, 19, 48, 20] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"bowl_noise0",
"cooling_fan_noise1"
],
"objects": [
"plate_0",
"plate_1",
"bowl_noise0",
"cooling_fan_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9844_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQFBgf/xABAEAABAwIEAwUGBAUDAgcA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Please identify the number of meat and kettle.'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a meat located at [193, 108, 201, 113]\\n- There's a kettle positioned at coordinates [252, 80, 265, 94]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a meat located at [220, 102, 224, 107]\\n- There's a kettle positioned at coordinates [94, 86, 111, 101]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The meat_0 at [193, 108, 201, 113] in main perspective is not visible in auxiliary perspective\\n- The meat_1 at [220, 102, 224, 107] in auxiliary perspective is not visible in main perspective\\n- The kettle_0 visible in main perspective at [252, 80, 265, 94] corresponds to the same object visible in auxiliary perspective at [94, 86, 111, 101]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"hammer_noise0",
"knife_noise1"
],
"objects": [
"meat_0",
"meat_1",
"kettle_0",
"hammer_noise0",
"knife_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7257_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAIBAwYFBAf/xABJEAABAwIDBAUIBgcGBgMA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Please identify the number of pot.'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"plate_noise0",
"hammer_noise1",
"shoe_noise2"
],
"objects": [
"pot_0",
"plate_noise0",
"hammer_noise1",
"shoe_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2",
"stompy"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "10073_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQFBgf/xABCEAABAwIEAwUGAwYFAwUB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you list how many meat are available?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first meat at [38, 14, 39, 15]\\n- I also see a second meat at [42, 3, 44, 4]\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The meat_0 at [38, 14, 39, 15] in main perspective is not visible in auxiliary perspective\\n- The meat_2 at [42, 3, 44, 4] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"cardboardbox_noise0",
"pot_noise1"
],
"objects": [
"meat_0",
"meat_1",
"meat_2",
"cardboardbox_noise0",
"pot_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8546_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABCEAABAwIEAwUFBgUDAgcB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Please estimate the total number of cup and shoe.'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first cup at [29, 22, 33, 26]\\n- I also see a second cup at [34, 2, 37, 5]\\n- I notice a shoe at [35, 19, 39, 22]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a cup located at [39, 21, 43, 24]\\n- There's a shoe positioned at coordinates [44, 20, 52, 25]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The cup_0 at [39, 21, 43, 24] in auxiliary perspective is not visible in main perspective\\n- The cup_1 at [29, 22, 33, 26] in main perspective is not visible in auxiliary perspective\\n- The cup_2 at [34, 2, 37, 5] in main perspective is not visible in auxiliary perspective\\n- The shoe_0 at [44, 20, 52, 25] in auxiliary perspective is not visible in main perspective\\n- The shoe_1 at [35, 19, 39, 22] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 5.\\n</think>\\n\\n\\\\boxed{5}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 4,
"noise_objects": [],
"objects": [
"cup_0",
"cup_1",
"cup_2",
"shoe_0",
"shoe_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8148_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABJEAACAQIEAwUEBwcBBgMJ... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Please identify the number of peach.'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first peach at [37, 14, 38, 15]\\n- I also see a second peach at [24, 41, 29, 43]\\n- There's also a third peach positioned at [36, 2, 38, 4]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a peach located at [41, 34, 44, 38]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The peach_0 at [37, 14, 38, 15] in main perspective is not visible in auxiliary perspective\\n- The peach_1 visible in main perspective at [24, 41, 29, 43] corresponds to the same object visible in auxiliary perspective at [41, 34, 44, 38]\\n- The peach_2 at [36, 2, 38, 4] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"bowl_noise0",
"green_peas_noise1"
],
"objects": [
"peach_0",
"peach_1",
"peach_2",
"bowl_noise0",
"green_peas_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "10113_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAAcBAQAAAAAAAAAAAAAAAAECAwQFBgcI/8QARxAAAQMCBAMFBQYEAwcC... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wooden_cutting_board are there in this space?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wooden located at [40, 16, 44, 18]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wooden located at [29, 26, 38, 34]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wooden_cutting_board_0 at [40, 16, 44, 18] in main perspective is not visible in auxiliary perspective\\n- The wooden_cutting_board_1 at [29, 26, 38, 34] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 3,
"noise_objects": [
"spoon_noise0",
"scissors_noise1"
],
"objects": [
"wooden_cutting_board_0",
"wooden_cutting_board_1",
"spoon_noise0",
"scissors_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8717_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QARBAAAQMCBAMGAwYEBAUD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Could you tell me how many wine and pear exist?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first wine at [54, 11, 56, 15]\\n- I also see a second wine at [28, 17, 31, 25]\\n- I can see the first pear at [62, 14, 63, 17]\\n- I also see a second pear at [28, 15, 30, 17]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wine located at [10, 16, 15, 23]\\n- There's a pear positioned at coordinates [24, 17, 26, 20]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wine_0 visible in main perspective at [54, 11, 56, 15] corresponds to the same object visible in auxiliary perspective at [10, 16, 15, 23]\\n- The wine_1 at [28, 17, 31, 25] in main perspective is not visible in auxiliary perspective\\n- The pear_0 visible in main perspective at [62, 14, 63, 17] corresponds to the same object visible in auxiliary perspective at [24, 17, 26, 20]\\n- The pear_1 at [28, 15, 30, 17] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_0",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 8,
"noise_objects": [],
"objects": [
"wine_0",
"wine_1",
"pear_0",
"pear_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "4521_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAQACAwQFBgf/xABIEAABAwIEAwUGBAIHBgUF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Could you tell me how many banana and hammer exist?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a banana located at [26, 117, 45, 122]\\n- There's a hammer positioned at coordinates [36, 110, 56, 122]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The banana_0 at [26, 117, 45, 122] in auxiliary perspective is not visible in main perspective\\n- The hammer_0 at [36, 110, 56, 122] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"clothes_iron_noise0",
"green_peas_noise1"
],
"objects": [
"banana_0",
"hammer_0",
"clothes_iron_noise0",
"green_peas_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch",
"stompy"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9197_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAgMBAQEBAAAAAAAAAAAAAQIAAwYEBQcI/8QARxAAAQMCBAMFBgMFBAkE... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wooden_cutting_board and clothes_iron are there?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wooden located at [15, 26, 23, 30]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wooden_cutting_board_0 at [15, 26, 23, 30] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_0",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 1,
"noise_objects": [
"peach_noise0",
"kettle_noise1",
"fork_noise2"
],
"objects": [
"wooden_cutting_board_0",
"peach_noise0",
"kettle_noise1",
"fork_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "5443_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAQACAwQFBgf/xABHEAABAwIDBQUFBgQFAgQH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many pizza are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first pizza at [37, 14, 39, 16]\\n- I also see a second pizza at [31, 31, 38, 40]\\n- There's also a third pizza positioned at [39, 3, 42, 4]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first pizza at [75, 31, 76, 33]\\n- I also notice a second pizza located at [46, 37, 53, 43]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pizza_0 visible in main perspective at [37, 14, 39, 16] corresponds to the same object visible in auxiliary perspective at [75, 31, 76, 33]\\n- The pizza_1 visible in main perspective at [31, 31, 38, 40] corresponds to the same object visible in auxiliary perspective at [46, 37, 53, 43]\\n- The pizza_2 at [39, 3, 42, 4] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"rock_noise0",
"wooden_cutting_board_noise1"
],
"objects": [
"pizza_0",
"pizza_1",
"pizza_2",
"rock_noise0",
"wooden_cutting_board_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "10002_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAgMBAQEBAAAAAAAAAAAAAQIAAwQFBgcI/8QAQhAAAgECBAMGAwYEBAUE... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you calculate how many kettle are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a kettle located at [242, 85, 256, 99]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first kettle at [72, 91, 94, 109]\\n- I also notice a second kettle located at [244, 101, 260, 122]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The kettle_0 visible in main perspective at [242, 85, 256, 99] corresponds to the same object visible in auxiliary perspective at [72, 91, 94, 109]\\n- The kettle_1 at [244, 101, 260, 122] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_4",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"spoon_noise0",
"spoon_noise1"
],
"objects": [
"kettle_0",
"kettle_1",
"spoon_noise0",
"spoon_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7990_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAwABAgQFBgf/xABDEAACAQMCBAMFBQcDAgUF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wine and pear are there in this space?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first wine at [133, 53, 145, 78]\\n- I also see a second wine at [179, 0, 187, 20]\\n- I notice a pear at [202, 62, 209, 74]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first wine at [307, 88, 335, 112]\\n- I also notice a second wine located at [196, 150, 209, 176]\\n- I notice a pear at [105, 139, 124, 155]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wine_0 visible in main perspective at [133, 53, 145, 78] corresponds to the same object visible in auxiliary perspective at [307, 88, 335, 112]\\n- The wine_1 at [196, 150, 209, 176] in auxiliary perspective is not visible in main perspective\\n- The wine_2 at [179, 0, 187, 20] in main perspective is not visible in auxiliary perspective\\n- The pear_0 at [202, 62, 209, 74] in main perspective is not visible in auxiliary perspective\\n- The pear_1 at [105, 139, 124, 155] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 5.\\n</think>\\n\\n\\\\boxed{5}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [],
"objects": [
"wine_0",
"wine_1",
"wine_2",
"pear_0",
"pear_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1",
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "6695_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECBAUGAwf/xABMEAABAwIEAgcGAwQFCwIH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Please estimate the total number of cup.'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a cup located at [57, 17, 61, 19]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first cup at [24, 17, 26, 18]\\n- I also notice a second cup located at [48, 19, 51, 20]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The cup_0 visible in main perspective at [57, 17, 61, 19] corresponds to the same object visible in auxiliary perspective at [24, 17, 26, 18]\\n- The cup_1 at [48, 19, 51, 20] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"bowl_noise0",
"wine_noise1"
],
"objects": [
"cup_0",
"cup_1",
"bowl_noise0",
"wine_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy",
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8841_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAABAAIDAQEBAAAAAAAAAAAAAAECAwUGBAcI/8QAQxAAAQMCBAIHBQUFBgcB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the number of apple to be counted?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first apple at [227, 93, 234, 99]\\n- I also see a second apple at [263, 45, 273, 54]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first apple at [42, 108, 56, 116]\\n- I also notice a second apple located at [57, 44, 72, 55]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The apple_0 visible in main perspective at [227, 93, 234, 99] corresponds to the same object visible in auxiliary perspective at [42, 108, 56, 116]\\n- The apple_2 visible in main perspective at [263, 45, 273, 54] corresponds to the same object visible in auxiliary perspective at [57, 44, 72, 55]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"bread_noise0",
"pot_noise1"
],
"objects": [
"apple_0",
"apple_1",
"apple_2",
"bread_noise0",
"pot_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8276_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAwABAgQFBgf/xABDEAABAwIEAwUFBgYBAwIH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you assess how many banana and clothes_iron are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first banana at [17, 16, 19, 18]\\n- I also see a second banana at [24, 30, 28, 36]\\n- I notice a clothes at [34, 13, 36, 17]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first banana at [51, 16, 52, 18]\\n- I also notice a second banana located at [46, 29, 48, 34]\\n- I notice a clothes at [71, 27, 76, 32]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The banana_0 visible in main perspective at [17, 16, 19, 18] corresponds to the same object visible in auxiliary perspective at [51, 16, 52, 18]\\n- The banana_1 visible in main perspective at [24, 30, 28, 36] corresponds to the same object visible in auxiliary perspective at [46, 29, 48, 34]\\n- The clothes_iron_0 visible in main perspective at [34, 13, 36, 17] corresponds to the same object visible in auxiliary perspective at [71, 27, 76, 32]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 3.\\n</think>\\n\\n\\\\boxed{3}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_0",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [
"kettle_noise0",
"pizza_noise1"
],
"objects": [
"banana_0",
"banana_1",
"clothes_iron_0",
"kettle_noise0",
"pizza_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "5475_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAIBAwQFBgf/xABHEAACAQIDBQQGBwYFAwMF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many meat and clothes_iron are available for use?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first meat at [149, 143, 162, 151]\\n- I also see a second meat at [153, 97, 165, 103]\\n- I notice a clothes at [121, 137, 147, 191]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a meat located at [227, 136, 232, 142]\\n- There's a clothes positioned at coordinates [215, 127, 231, 169]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The meat_0 at [227, 136, 232, 142] in auxiliary perspective is not visible in main perspective\\n- The meat_1 at [149, 143, 162, 151] in main perspective is not visible in auxiliary perspective\\n- The meat_2 at [153, 97, 165, 103] in main perspective is not visible in auxiliary perspective\\n- The clothes_iron_0 at [215, 127, 231, 169] in auxiliary perspective is not visible in main perspective\\n- The clothes_iron_1 at [121, 137, 147, 191] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 5.\\n</think>\\n\\n\\\\boxed{5}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_4",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [],
"objects": [
"meat_0",
"meat_1",
"meat_2",
"clothes_iron_0",
"clothes_iron_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7407_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGgAAAgMBAQAAAAAAAAAAAAAAAAIBAwQFBv/EAEQQAAIBAgQDBQQIBQMCBQUA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many meat and bowl are there?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first meat at [142, 136, 164, 149]\\n- I also see a second meat at [177, 22, 189, 28]\\n- I notice a bowl at [148, 113, 167, 126]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a meat located at [322, 141, 348, 161]\\n- There's a bowl positioned at coordinates [164, 93, 176, 101]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The meat_0 at [322, 141, 348, 161] in auxiliary perspective is not visible in main perspective\\n- The meat_1 at [142, 136, 164, 149] in main perspective is not visible in auxiliary perspective\\n- The meat_2 at [177, 22, 189, 28] in main perspective is not visible in auxiliary perspective\\n- The bowl_0 at [164, 93, 176, 101] in auxiliary perspective is not visible in main perspective\\n- The bowl_1 at [148, 113, 167, 126] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 5.\\n</think>\\n\\n\\\\boxed{5}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_4",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 4,
"noise_objects": [],
"objects": [
"meat_0",
"meat_1",
"meat_2",
"bowl_0",
"bowl_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda",
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7649_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAMBAgQFBgf/xABGEAACAQIEAwQIAwcDAgMJ... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you identify all the pumpkin and pear?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first pumpkin at [319, 113, 357, 135]\\n- I also see a second pumpkin at [195, 84, 212, 97]\\n- I can see the first pear at [353, 119, 377, 138]\\n- I also see a second pear at [188, 86, 198, 101]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a pumpkin located at [123, 99, 144, 113]\\n- There's a pear positioned at coordinates [141, 93, 150, 108]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pumpkin_0 visible in main perspective at [319, 113, 357, 135] corresponds to the same object visible in auxiliary perspective at [123, 99, 144, 113]\\n- The pumpkin_1 at [195, 84, 212, 97] in main perspective is not visible in auxiliary perspective\\n- The pear_0 visible in main perspective at [353, 119, 377, 138] corresponds to the same object visible in auxiliary perspective at [141, 93, 150, 108]\\n- The pear_1 at [188, 86, 198, 101] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 5,
"noise_objects": [],
"objects": [
"pumpkin_0",
"pumpkin_1",
"pear_0",
"pear_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1",
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "6581_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABLEAABAwIDBQQGBgcECQUB... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you assess how many tomato are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a tomato located at [247, 83, 257, 91]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first tomato at [85, 95, 98, 103]\\n- I also notice a second tomato located at [239, 121, 254, 134]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The tomato_0 visible in main perspective at [247, 83, 257, 91] corresponds to the same object visible in auxiliary perspective at [85, 95, 98, 103]\\n- The tomato_1 at [239, 121, 254, 134] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 7,
"noise_objects": [
"pot_noise0",
"scissors_noise1"
],
"objects": [
"tomato_0",
"tomato_1",
"pot_noise0",
"scissors_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8427_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QATRAAAQMCAwUEBggDBAgE... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the quantity of banana and bread in this area?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a banana located at [32, 25, 34, 28]\\n- There's a bread positioned at coordinates [34, 26, 41, 28]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The banana_0 at [32, 25, 34, 28] in auxiliary perspective is not visible in main perspective\\n- The bread_0 at [34, 26, 41, 28] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"hammer_noise0",
"cooling_fan_noise1"
],
"objects": [
"banana_0",
"bread_0",
"hammer_noise0",
"cooling_fan_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"fetch",
"stompy"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8285_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAAECAwQFBgcI/8QARxAAAQMCBAQEAwYDBgMG... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you count the cup and apple?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first cup at [64, 22, 69, 25]\\n- I also see a second cup at [32, 20, 35, 23]\\n- There's also a third cup positioned at [25, 5, 29, 8]\\n- I can see the first apple at [66, 23, 70, 25]\\n- I also see a second apple at [29, 23, 31, 25]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a cup located at [24, 20, 27, 22]\\n- There's a apple positioned at coordinates [26, 20, 28, 21]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The cup_0 visible in main perspective at [64, 22, 69, 25] corresponds to the same object visible in auxiliary perspective at [24, 20, 27, 22]\\n- The cup_1 at [32, 20, 35, 23] in main perspective is not visible in auxiliary perspective\\n- The cup_2 at [25, 5, 29, 8] in main perspective is not visible in auxiliary perspective\\n- The apple_0 visible in main perspective at [66, 23, 70, 25] corresponds to the same object visible in auxiliary perspective at [26, 20, 28, 21]\\n- The apple_1 at [29, 23, 31, 25] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 5.\\n</think>\\n\\n\\\\boxed{5}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_1",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 5,
"noise_objects": [],
"objects": [
"cup_0",
"cup_1",
"cup_2",
"apple_0",
"apple_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"stompy"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9905_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAEDBAUGAgf/xABHEAABAwIDBQQIAwYDBwQD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wooden_cutting_board and pear are there?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a wooden located at [138, 77, 154, 87]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a wooden located at [294, 108, 323, 126]\\n- In this view, I can see the first pear at [220, 56, 225, 66]\\n- I also notice a second pear located at [117, 165, 138, 184]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The wooden_cutting_board_0 visible in main perspective at [138, 77, 154, 87] corresponds to the same object visible in auxiliary perspective at [294, 108, 323, 126]\\n- The pear_0 at [220, 56, 225, 66] in auxiliary perspective is not visible in main perspective\\n- The pear_1 at [117, 165, 138, 184] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 6,
"noise_objects": [],
"objects": [
"wooden_cutting_board_0",
"wooden_cutting_board_1",
"pear_0",
"pear_1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "9608_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABEEAABAwIEAwYDBgQEBAYD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the exact number of pumpkin and shoe?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a pumpkin located at [182, 71, 198, 83]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a pumpkin located at [369, 100, 383, 116]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pumpkin_0 visible in main perspective at [182, 71, 198, 83] corresponds to the same object visible in auxiliary perspective at [369, 100, 383, 116]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 3,
"noise_objects": [
"bread_noise0",
"bread_noise1",
"wine_noise2"
],
"objects": [
"pumpkin_0",
"bread_noise0",
"bread_noise1",
"wine_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8508_2-1",
"task_name": "count_objects_TWO_TYPES",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABGEAABAwIEAwUEBwUGBgID... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many instances of meat are in the area?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a meat located at [233, 113, 244, 121]\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The meat_0 at [233, 113, 244, 121] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 3,
"noise_objects": [
"green_peas_noise0",
"hammer_noise1",
"fork_noise2"
],
"objects": [
"meat_0",
"green_peas_noise0",
"hammer_noise1",
"fork_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8235_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABHEAACAQIDBAYIAwcDAgQH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many fork can you find?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a fork located at [8, 139, 30, 142]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a fork located at [238, 139, 271, 143]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The fork_0 visible in main perspective at [8, 139, 30, 142] corresponds to the same object visible in auxiliary perspective at [238, 139, 271, 143]\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_3",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"scissors_noise0",
"green_peas_noise1",
"peach_noise2"
],
"objects": [
"fork_0",
"scissors_noise0",
"green_peas_noise1",
"peach_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1",
"fetch"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8594_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAQUBAQAAAAAAAAAAAAAAAAECAwQFBgf/xABOEAACAAQEAgYFCAUJBwQD... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many wooden_cutting_board are there?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 0.\\n</think>\\n\\n\\\\boxed{0}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_0",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 0,
"noise_objects": [
"cup_noise0",
"bread_noise1",
"pot_noise2"
],
"objects": [
"cup_noise0",
"bread_noise1",
"pot_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1",
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "5393_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAAAQACAwQFBgcI/8QARRAAAQMCBAMFBQUFBwME... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'What is the exact number of meat?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a meat located at [200, 75, 205, 79]\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The meat_0 at [200, 75, 205, 79] in main perspective is not visible in auxiliary perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 1.\\n</think>\\n\\n\\\\boxed{1}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 3,
"noise_objects": [
"apple_noise0",
"scissors_noise1",
"bowl_noise2"
],
"objects": [
"meat_0",
"apple_noise0",
"scissors_noise1",
"bowl_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7538_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQFBgf/xAA+EAABAwIDBgMFBQgCAgMA... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many peach are visible in this location?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see a peach located at [164, 122, 174, 133]\\n\\nNow examining the auxiliary perspective (Image B):\\n- I can see a peach located at [212, 109, 223, 120]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The peach_0 at [164, 122, 174, 133] in main perspective is not visible in auxiliary perspective\\n- The peach_1 at [212, 109, 223, 120] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 2.\\n</think>\\n\\n\\\\boxed{2}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 9,
"noise_objects": [
"kettle_noise0",
"green_peas_noise1"
],
"objects": [
"peach_0",
"peach_1",
"kettle_noise0",
"green_peas_noise1"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"anymal_c",
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8349_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAQBAgMFBgf/xABBEAABAwIDBAcFBwQBBAID... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'Can you list how many apple are available?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 0.\\n</think>\\n\\n\\\\boxed{0}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_0",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 8,
"noise_objects": [
"apple_noise0",
"wooden_cutting_board_noise1",
"green_peas_noise2"
],
"objects": [
"apple_noise0",
"wooden_cutting_board_noise1",
"green_peas_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1",
"unitree_go2"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "4995_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAQIAAwQFBgf/xABBEAABBAAEBAQDBwMDAgQH... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many pizza are present?'.\\n\\nLet me first examine the main perspective (Image A):\\n- I can see the first pizza at [185, 95, 205, 101]\\n- I also see a second pizza at [170, 18, 193, 31]\\n\\nNow examining the auxiliary perspective (Image B):\\n- In this view, I can see the first pizza at [162, 100, 187, 110]\\n- I also notice a second pizza located at [185, 103, 212, 115]\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n- The pizza_0 at [162, 100, 187, 110] in auxiliary perspective is not visible in main perspective\\n- The pizza_1 at [185, 95, 205, 101] in main perspective is not visible in auxiliary perspective\\n- The pizza_2 at [170, 18, 193, 31] in main perspective is not visible in auxiliary perspective\\n- The pizza_3 at [185, 103, 212, 115] in auxiliary perspective is not visible in main perspective\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 4.\\n</think>\\n\\n\\\\boxed{4}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_2",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 4,
"noise_objects": [],
"objects": [
"pizza_0",
"pizza_1",
"pizza_2",
"pizza_3"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"panda"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "8482_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
[
{
"bytes": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9Pjv/2wBDAQoLCw4NDhwQEBw7KCIoOzs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozv/wAARCADYAYADASIAAhEBAxEB/8QAGwAAAgMBAQEAAAAAAAAAAAAAAAECAwQFBgf/xABBEAACAQMCAwYEBAMGBgEF... | corl_l1_sim_val | [
{
"content": "You are analyzing two images from different robot perspectives viewing the same environment. These images represent two distinct robot viewpoints that may show overlapping or complementary parts of the scene. IMPORTANT FORMAT REQUIREMENTS:\n1. ALL reasoning must be enclosed within <think> </think>... | spatial_reasoning_object_counting | {
"ground_truth": "<think>\\nI need to analyze images from two robot perspectives to answer the question about 'How many pot are visible in this location?'.\\n\\nLet me first examine the main perspective (Image A):\\n\\nNow examining the auxiliary perspective (Image B):\\n\\nAnalyzing spatial correspondence between the two perspectives:\\n\\nCombining observations from both perspectives, the total number of objects you asked me to count is 0.\\n</think>\\n\\n\\\\boxed{0}",
"style": "rule"
} | {
"category": null,
"dataset_name": "ObjectCount_5",
"grasping_instruction": null,
"image_name": null,
"init_pos": null,
"layout_id": 2,
"noise_objects": [
"knife_noise0",
"rock_noise1",
"bowl_noise2"
],
"objects": [
"knife_noise0",
"rock_noise1",
"bowl_noise2"
],
"original_answer": null,
"original_question": null,
"question_id": null,
"robots": [
"unitree_h1"
],
"source_dataset": null,
"target_center": null,
"target_coordinates": null,
"target_image": null,
"target_object": null,
"task_id": "7972_1-1",
"task_name": "count_objects_EASY",
"task_type": null
} |
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