# easyr1-v2-pro-apps-manually-labeled-icon-data-from-yt-4MP

This dataset was generated using the EasyR1 grounding dataset pipeline.

## Generation Details

- **Generated on**: 2025-09-06 00:30:03 UTC
- **Script**: `push_easyr1_to_hf.py`
- **Data directory**: `datasets`

## Parameters Used

- **Maximum samples**: 2000
- **Image resize (max megapixels)**: 4.0 MP
- **Minimum native image resolution**: 0.0 MP
- **Prompt format**: `gta1`
- **Output format**: `coordinates`
- **Random seed**: 42
- **Resampling enabled**: False
- **Icon upsampling ratio**: Disabled (random sampling)
- **pc-agent-e deduplication**: False
- **Debug images enabled**: True (annotated images with red bounding boxes included)

## Dataset Groups

The following JSON/JSONL files were used to create this dataset:


### Dataset Group 1
- datasets/grounding_annotations.json

## Dataset Statistics

- **Total training samples**: 230
- **Image dimensions**: Variable
- **Columns**: image_path, prompt, normalized_bbox, images, easyr1_prompt, bbox, messages, original_image_width, image_width, image_height, annotated_images

## System Prompt

The following system prompt is used for this dataset:

```
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>open terminal
- **Assistant response**: (216,670)
- **Bounding box**: [189, 664, 243, 676]
- **Image path**: images/Android App Development Tutorial 15： OnClickListener_scene0012_t000211.750.jpg

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("mlfoundations-cua-dev/easyr1-v2-pro-apps-manually-labeled-icon-data-from-yt-4MP")

# Access the training data
train_data = dataset['train']

# Example: Get the first sample
sample = train_data[0]
images = sample['images']
messages = sample['messages']
bbox = sample['bbox']
annotated_images = sample['annotated_images']  # Available when debug images are enabled```

## 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.