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Browse files- .gitattributes +8 -0
- cmu_stretch-train.tfrecord-00000-of-00008 +3 -0
- cmu_stretch-train.tfrecord-00001-of-00008 +3 -0
- cmu_stretch-train.tfrecord-00002-of-00008 +3 -0
- cmu_stretch-train.tfrecord-00003-of-00008 +3 -0
- cmu_stretch-train.tfrecord-00004-of-00008 +3 -0
- cmu_stretch-train.tfrecord-00005-of-00008 +3 -0
- cmu_stretch-train.tfrecord-00006-of-00008 +3 -0
- cmu_stretch-train.tfrecord-00007-of-00008 +3 -0
- dataset_info.json +33 -0
- features.json +140 -0
.gitattributes
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dataset_info.json
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{
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"citation": "@inproceedings{bahl2023affordances,\n title={Affordances from Human Videos as a Versatile Representation for Robotics},\n author={Bahl, Shikhar and Mendonca, Russell and Chen, Lili and Jain, Unnat and Pathak, Deepak},\n booktitle={CVPR},\n year={2023}\n}\n@article{mendonca2023structured,\n title={Structured World Models from Human Videos},\n author={Mendonca, Russell and Bahl, Shikhar and Pathak, Deepak},\n journal={CoRL},\n year={2023}\n}",
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"description": "Hello stretch robot kitchen interactions",
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"fileFormat": "tfrecord",
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"location": {
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"urls": [
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"https://robo-affordances.github.io/"
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]
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},
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"moduleName": "tensorflow_datasets.robotics.rtx.rtx",
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"name": "cmu_stretch",
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"releaseNotes": {
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"0.1.0": "Initial release."
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},
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"splits": [
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{
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"filepathTemplate": "{DATASET}-{SPLIT}.{FILEFORMAT}-{SHARD_X_OF_Y}",
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"name": "train",
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"numBytes": "763427877",
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"shardLengths": [
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"20",
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}
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],
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"version": "0.1.0"
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}
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features.json
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@@ -0,0 +1,140 @@
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{
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"featuresDict": {
|
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"features": {
|
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"episode_metadata": {
|
| 5 |
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"featuresDict": {
|
| 6 |
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"features": {
|
| 7 |
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"file_path": {
|
| 8 |
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"description": "Path to the original data file.",
|
| 9 |
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"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
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"text": {}
|
| 11 |
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}
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},
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"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict"
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},
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"steps": {
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"pythonClassName": "tensorflow_datasets.core.features.dataset_feature.Dataset",
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"sequence": {
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"feature": {
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"featuresDict": {
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"features": {
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| 22 |
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"action": {
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| 23 |
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"description": "Robot action, consists of [3x ee pos, 3x ee rot 1x gripper binary action, 1x terminate episode].",
|
| 24 |
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"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
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"tensor": {
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"dtype": "float32",
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"encoding": "none",
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"shape": {
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"dimensions": [
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"8"
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}
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}
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},
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"discount": {
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| 36 |
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"description": "Discount if provided, default to 1.",
|
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"pythonClassName": "tensorflow_datasets.core.features.scalar.Scalar",
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"tensor": {
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"dtype": "float32",
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"encoding": "none",
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"shape": {}
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"is_first": {
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"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
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"tensor": {
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"dtype": "bool",
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"encoding": "none",
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"shape": {}
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"is_last": {
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"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
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"tensor": {
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"dtype": "bool",
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"encoding": "none",
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"shape": {}
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}
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| 59 |
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},
|
| 60 |
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"is_terminal": {
|
| 61 |
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"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
|
| 62 |
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"tensor": {
|
| 63 |
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"dtype": "bool",
|
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"encoding": "none",
|
| 65 |
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"shape": {}
|
| 66 |
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}
|
| 67 |
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},
|
| 68 |
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"language_embedding": {
|
| 69 |
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"description": "Kona language embedding. See https://tfhub.dev/google/universal-sentence-encoder-large/5",
|
| 70 |
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"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
|
| 71 |
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"tensor": {
|
| 72 |
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"dtype": "float32",
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"encoding": "none",
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"shape": {
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"dimensions": [
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"512"
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]
|
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}
|
| 79 |
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}
|
| 80 |
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},
|
| 81 |
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"language_instruction": {
|
| 82 |
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"description": "Language Instruction.",
|
| 83 |
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"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
|
| 84 |
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"text": {}
|
| 85 |
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},
|
| 86 |
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"observation": {
|
| 87 |
+
"featuresDict": {
|
| 88 |
+
"features": {
|
| 89 |
+
"image": {
|
| 90 |
+
"description": "Main camera RGB observation.",
|
| 91 |
+
"image": {
|
| 92 |
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"dtype": "uint8",
|
| 93 |
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"encodingFormat": "png",
|
| 94 |
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"shape": {
|
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"dimensions": [
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"128",
|
| 97 |
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"128",
|
| 98 |
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"3"
|
| 99 |
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]
|
| 100 |
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}
|
| 101 |
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},
|
| 102 |
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"pythonClassName": "tensorflow_datasets.core.features.image_feature.Image"
|
| 103 |
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},
|
| 104 |
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"state": {
|
| 105 |
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"description": "Robot state, consists of [3x robot joint angles/ee pos, 1x gripper position].",
|
| 106 |
+
"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
|
| 107 |
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"tensor": {
|
| 108 |
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"dtype": "float32",
|
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"encoding": "none",
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|
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"4"
|
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|
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|
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|
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|
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|
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},
|
| 119 |
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"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict"
|
| 120 |
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},
|
| 121 |
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"reward": {
|
| 122 |
+
"description": "Reward if provided, 1 on final step for demos.",
|
| 123 |
+
"pythonClassName": "tensorflow_datasets.core.features.scalar.Scalar",
|
| 124 |
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"tensor": {
|
| 125 |
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"dtype": "float32",
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"encoding": "none",
|
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"shape": {}
|
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|
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|
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|
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"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict"
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"length": "-1"
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"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict"
|
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}
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