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mlfoundations-cua-dev/easyr1-10k-hard-qwen7b-easy-gta1-4MP-add-jedi-grounding-with-no-filtering

easyr1-10k-hard-qwen7b-easy-gta1-4MP-add-jedi-grounding-with-no-filtering This dataset was generated using the EasyR1 grounding dataset pipeline. Generation Details Generated on: 2025-08-27 00:53:16 UTC Script: push_easyr1_to_hf.py Data directory: /lustre/fsw/portfolios/nvr/users/aawadalla/LLaMA-Factory/data Parameters Used Maximum samples: 10000 Image resize (max megapixels): 4.0 MP Minimum native image resolution: 0.0 MP Prompt format:… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-cua-dev/easyr1-10k-hard-qwen7b-easy-gta1-4MP-add-jedi-grounding-with-no-filtering.

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Dataset Card

easyr1-10k-hard-qwen7b-easy-gta1-4MP-add-jedi-grounding-with-no-filtering

This dataset was generated using the EasyR1 grounding dataset pipeline.

Generation Details

  • —Generated on: 2025-08-27 00:53:16 UTC
  • —Script: push_easyr1_to_hf.py
  • —Data directory: /lustre/fsw/portfolios/nvr/users/aawadalla/LLaMA-Factory/data

Parameters Used

  • —Maximum samples: 10000
  • —Image resize (max megapixels): 4.0 MP
  • —Minimum native image resolution: 0.0 MP
  • —Prompt format: gta1_with_resolution
  • —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

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/jedi-all-grounding-left_click-10px.jsonl

Dataset Group 2

Files (intersection of kept samples across all files):

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/pixmo-points-qwentoolcall-notgrounded-QwenQwen2.5-VL-7B-Instruct-qwentoolcall.jsonl
  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/pixmo-points-gta1-correctlygrounded-HelloKKMeGTA1-7B-gta1.jsonl

Dataset Group 3

Files (intersection of kept samples across all files):

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/autogui-grounding-only-qwentoolcall-notgrounded-QwenQwen2.5-VL-7B-Instruct-qwentoolcall.jsonl
  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/autogui-grounding-only-gta1-correctlygrounded-HelloKKMeGTA1-7B-gta1.jsonl

Dataset Group 4

Files (intersection of kept samples across all files):

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/seeclick-qwentoolcall-notgrounded-QwenQwen2.5-VL-7B-Instruct-qwentoolcall.jsonl
  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/seeclick-gta1-correctlygrounded-HelloKKMeGTA1-7B-gta1.jsonl

Dataset Group 5

Files (intersection of kept samples across all files):

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/pc-e-grounding-only-claude-instructions-qwentoolcall-notgrounded-QwenQwen2.5-VL-7B-Instruct-qwentoolcall.jsonl
  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/pc-e-grounding-only-claude-instructions-gta1-correctlygrounded-HelloKKMeGTA1-7B-gta1.jsonl

Dataset Group 6

Files (intersection of kept samples across all files):

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/omniact-grounding-only-qwentoolcall-notgrounded-QwenQwen2.5-VL-7B-Instruct-qwentoolcall.jsonl
  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/omniact-grounding-only-gta1-correctlygrounded-HelloKKMeGTA1-7B-gta1.jsonl

Dataset Group 7

Files (intersection of kept samples across all files):

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/showui-desktop-qwentoolcall-notgrounded-QwenQwen2.5-VL-7B-Instruct-qwentoolcall.jsonl
  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/showui-desktop-gta1-correctlygrounded-HelloKKMeGTA1-7B-gta1.jsonl

Dataset Group 8

Files (intersection of kept samples across all files):

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/showui-web-qwentoolcall-notgrounded-QwenQwen2.5-VL-7B-Instruct-qwentoolcall.jsonl
  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/showui-web-gta1-correctlygrounded-HelloKKMeGTA1-7B-gta1.jsonl

Dataset Group 9

Files (intersection of kept samples across all files):

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/uground-qwentoolcall-notgrounded-QwenQwen2.5-VL-7B-Instruct-qwentoolcall.jsonl
  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/uground-gta1-correctlygrounded-HelloKKMeGTA1-7B-gta1.jsonl

Dataset Group 10

Files (intersection of kept samples across all files):

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/waveui-qwentoolcall-notgrounded-QwenQwen2.5-VL-7B-Instruct-qwentoolcall.jsonl
  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/waveui-gta1-correctlygrounded-HelloKKMeGTA1-7B-gta1.jsonl

Dataset Group 11

  • —/lustre/fs12/portfolios/nvr/projects/nvrlacrllm/users/aawadalla/grounding-data-filters/professional-apps-grounding-filtered-gta1-7b-converted-notgrounded-qwen25vl7b-QwenQwen2.5-VL-7B-Instruct-qwentoolcall.jsonl

Dataset Statistics

  • —Total training samples: 10000
  • —Image dimensions: Variable
  • —Columns: imagepath, prompt, normalizedbbox, images, easyr1prompt, bbox, messages, originalimagewidth, imagewidth, imageheight, annotatedimages

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. The image resolution is height 2048 and width 2048. For elements with area, return the center point.

Output the coordinate pair exactly:
(x,y)

Sample Entry

  • —User prompt: <image> Given the following text: "This process is then continued to find the second largest and place it and so on until the data is sorted." , find the text in the document and click the 4th character "s" in the text.
  • —Assistant response: (592,158)
  • —Bounding box: [589, 155, 596, 162]
  • —Image path: docimages/AmHHgw-Nep9dwAGw6RIF-nxGslWg3840x2160CHAR7_14.png

Usage

python
from datasets import load_dataset

dataset = load_dataset("mlfoundations-cua-dev/easyr1-10k-hard-qwen7b-easy-gta1-4MP-add-jedi-grounding-with-no-filtering")

# 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_with_resolution

GTA1 format with image resolution included in the system prompt. Outputs coordinates in (x,y) format.

## License

Please refer to the original dataset licenses for usage restrictions.