easyr1-10k-hard-qwen7b-easy-gta1-4MP-random-resize

# easyr1-10k-hard-qwen7b-easy-gta1-4MP-random-resize This dataset was generated using the EasyR1 grounding dataset pipeline. ## Generation Details - **Generated on**: 2025-08-24 22:45:01 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 ## Dataset Groups The following JSON/JSONL files were used to create this dataset: ### Dataset Group 1 Files (intersection of kept samples across all files): - grounding-data-filters/pixmo-points-qwen_tool_call-not_grounded-Qwen_Qwen2.5-VL-7B-Instruct-qwen_tool_call.jsonl - grounding-data-filters/pixmo-points-gta1-correctly_grounded-HelloKKMe_GTA1-7B-gta1.jsonl ### Dataset Group 2 Files (intersection of kept samples across all files): - grounding-data-filters/autogui-grounding-only-qwen_tool_call-not_grounded-Qwen_Qwen2.5-VL-7B-Instruct-qwen_tool_call.jsonl - grounding-data-filters/autogui-grounding-only-gta1-correctly_grounded-HelloKKMe_GTA1-7B-gta1.jsonl ### Dataset Group 3 Files (intersection of kept samples across all files): - grounding-data-filters/seeclick-qwen_tool_call-not_grounded-Qwen_Qwen2.5-VL-7B-Instruct-qwen_tool_call.jsonl - grounding-data-filters/seeclick-gta1-correctly_grounded-HelloKKMe_GTA1-7B-gta1.jsonl ### Dataset Group 4 Files (intersection of kept samples across all files): - grounding-data-filters/pc-e-grounding-only-claude-instructions-qwen_tool_call-not_grounded-Qwen_Qwen2.5-VL-7B-Instruct-qwen_tool_call.jsonl - grounding-data-filters/pc-e-grounding-only-claude-instructions-gta1-correctly_grounded-HelloKKMe_GTA1-7B-gta1.jsonl ### Dataset Group 5 Files (intersection of kept samples across all files): - grounding-data-filters/omniact-grounding-only-qwen_tool_call-not_grounded-Qwen_Qwen2.5-VL-7B-Instruct-qwen_tool_call.jsonl - grounding-data-filters/omniact-grounding-only-gta1-correctly_grounded-HelloKKMe_GTA1-7B-gta1.jsonl ### Dataset Group 6 Files (intersection of kept samples across all files): - grounding-data-filters/showui-desktop-qwen_tool_call-not_grounded-Qwen_Qwen2.5-VL-7B-Instruct-qwen_tool_call.jsonl - grounding-data-filters/showui-desktop-gta1-correctly_grounded-HelloKKMe_GTA1-7B-gta1.jsonl ### Dataset Group 7 Files (intersection of kept samples across all files): - grounding-data-filters/showui-web-qwen_tool_call-not_grounded-Qwen_Qwen2.5-VL-7B-Instruct-qwen_tool_call.jsonl - grounding-data-filters/showui-web-gta1-correctly_grounded-HelloKKMe_GTA1-7B-gta1.jsonl ### Dataset Group 8 Files (intersection of kept samples across all files): - grounding-data-filters/uground-qwen_tool_call-not_grounded-Qwen_Qwen2.5-VL-7B-Instruct-qwen_tool_call.jsonl - grounding-data-filters/uground-gta1-correctly_grounded-HelloKKMe_GTA1-7B-gta1.jsonl ### Dataset Group 9 Files (intersection of kept samples across all files): - grounding-data-filters/waveui-qwen_tool_call-not_grounded-Qwen_Qwen2.5-VL-7B-Instruct-qwen_tool_call.jsonl - grounding-data-filters/waveui-gta1-correctly_grounded-HelloKKMe_GTA1-7B-gta1.jsonl ## Dataset Statistics - **Total training samples**: 10000 - **Image dimensions**: Variable - **Columns**: image_path, prompt, normalized_bbox, images, easyr1_prompt, bbox, messages, original_image_width, original_image_height, image_width, image_height ## 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> Click the Find Next button - **Assistant response**: (161,452) - **Bounding box**: [140, 440, 182, 465] - **Image path**: pc-agent-e-images/data/events/screenshot/eba0_8155418e_10.png ## Usage ```python from datasets import load_dataset dataset = load_dataset("mlfoundations-cua-dev/easyr1-10k-hard-qwen7b-easy-gta1-4MP-random-resize") # 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'] ``` ## 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.