Add README with dataset generation details

README.md

@@ -1,41 +1,76 @@
----
-dataset_info:
-  features:
-  - name: image_path
-    dtype: string
-  - name: abs_image_path
-    dtype: string
-  - name: prompt
-    dtype: string
-  - name: normalized_bbox
-    list: float64
-  - name: images
-    list: image
-  - name: easyr1_prompt
-    dtype: string
-  - name: bbox
-    list: int64
-  - name: messages
-    list:
-    - name: content
-      dtype: string
-    - name: role
-      dtype: string
-  - name: original_image_width
-    dtype: int64
-  - name: image_width
-    dtype: int64
-  - name: image_height
-    dtype: int64
-  splits:
-  - name: train
-    num_bytes: 821376461.13
-    num_examples: 5790
-  download_size: 597395315
-  dataset_size: 821376461.13
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+# ui-vision-grounding-4MP
+
+This dataset was generated from UI-Vision annotations using the conversion pipeline.
+
+## Generation Details
+
+- **Generated on**: 2025-09-10 12:58:39 UTC
+- **Script**: `convert_ui_vision_to_hf.py`
+- **Images directory**: `ui-vision/images`
+
+## Parameters Used
+
+- **Maximum samples**: None
+- **Image resize (max megapixels)**: 4.0 MP
+- **Minimum native image resolution**: 0.0 MP
+- **Prompt format**: `gta1`
+- **Output format**: `coordinates`
+- **Random seed**: 42
+- **Debug images enabled**: False
+
+## Annotation Files
+
+The following annotation files were used to create this dataset:
+
+- ui-vision/annotations/layout_grounding/layout_grounding.json
+- ui-vision/annotations/element_grounding/element_grounding_spatial.json
+- ui-vision/annotations/element_grounding/element_grounding_basic.json
+- ui-vision/annotations/element_grounding/element_grounding_functional.json
+
+## Dataset Statistics
+
+- **Total training samples**: 5790
+- **Columns**: image_path, abs_image_path, prompt, normalized_bbox, images, easyr1_prompt, bbox, messages, original_image_width, image_width, image_height
+
+## System Prompt
+
+```
+You are an expert UI element locator. Given a GUI image and a user's element description, provide the coordinates of the specified element as a single (x,y) point. For elements with area, return the center point.
+
+Output the coordinate pair exactly:
+(x,y)
+```
+
+## Sample Entry
+
+
+- **User prompt**: <image>
+Locate the specified region.
+- **Assistant response**: (107,33)
+- **Bounding box**: [80, 6, 134, 60]
+- **Image path**: element_grounding/f8ce11340042f598b0c6f1ae49e75f4a.png
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("mlfoundations-cua-dev/ui-vision-grounding-4MP")
+
+train = dataset['train']
+sample = train[0]
+images = sample['images']
+messages = sample['messages']
+bbox = sample['bbox']
+
+```
+
+## Prompt Formats
+
+### gta1
+
+Standard GTA1 format without resolution information. Outputs coordinates in (x,y) format.
+
+## License
+
+Please refer to the original dataset licenses for usage restrictions.