Upload README.md with huggingface_hub

README.md

@@ -30,600 +30,600 @@ configs:
   - path: linux-mint/data-00000-of-00001.arrow
     split: train
 ---
-# Screen2Coord_denorm Dataset
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-**Screen2Coord** is a dataset for training models that take a **screenshot, screen dimensions, and a textual action description** as input and output the **coordinates of the target bounding box** on the screen. This dataset is intended for image-text-to-text LLMs applied to user interface interactions.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-## Dataset Structure
-
-
-
-
-
-
-
-
-
-### New feature! Windows, MacOS, Linux-Ubuntu subsets!
-
-
-
-
-
-
-
-
-
-
-
-### Data Instances
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-A typical data instance in Screen2Coord consists of:
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-- `image`: A screenshot image in PNG format
-- `mapped_denorm_bboxes`: List of bounding box objects containing:
-  - `bbox`: List of integers `[x, y, width, height]` specifying the bounding box coordinates in denormalized 0-1000 system
-  - `texts`: List of textual descriptions associated with the bounding box (e.g., `"click on my profile"`)
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-### Data Fields
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-- `image`: Image file in PNG format
-- `mapped_denorm_bboxes`: Sequence of dictionaries with bounding box information (coordinates in denormalized 0-1000 system)
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+# Screen2Coord_denorm_extend Dataset
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+**Screen2Coord** is a dataset for training models that take a **screenshot, screen dimensions, and a textual action description** as input and output the **coordinates of the target bounding box** on the screen. This dataset is intended for image-text-to-text LLMs applied to user interface interactions.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+## Dataset Structure
+
+
+
+
+
+
+
+
+
+### New feature! Windows, MacOS, Linux-Ubuntu subsets!
+
+
+
+
+
+
+
+
+
+
+
+### Data Instances
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+A typical data instance in Screen2Coord consists of:
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+- `image`: A screenshot image in PNG format
+- `mapped_denorm_bboxes`: List of bounding box objects containing:
+  - `bbox`: List of integers `[x, y, width, height]` specifying the bounding box coordinates in denormalized 0-1000 system
+  - `texts`: List of textual descriptions associated with the bounding box (e.g., `"click on my profile"`)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+### Data Fields
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+- `image`: Image file in PNG format
+- `mapped_denorm_bboxes`: Sequence of dictionaries with bounding box information (coordinates in denormalized 0-1000 system)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
 ### Data Splits
 
 The dataset contains the following splits:
 
-- `macos` (train): 2 examples
-- `windows` (train): 5 examples
+- `macos` (train): 174 examples
+- `windows` (train): 166 examples
 - `linux-ubuntu` (train): 1 examples
 - `linux-mint` (train): 1 examples
-## Purpose / How to Use
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-The main idea of this dataset is to train **image-text-to-text LLMs** that can interpret a screenshot and textual prompt **along with screen dimensions and instructions**, e.g., `"open the browser"`.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-The model receives:
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-- **Screenshot of the screen**
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-- **Screen size** `[width, height]`
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-- **Textual instruction** (prompt)
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-And outputs:
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-- **Bounding box coordinates** corresponding to where the action should be performed.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-  For example, clicking in the middle of the predicted bounding box executes the instructed action.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-This enables models to perform **UI actions** based on visual context and natural language instructions.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-For example, during training, you can provide the model with a full prompt from an agent system and also add a click tool, supplying the labeled bounding boxes from this dataset in the tool call.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-## Contributions
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+## Purpose / How to Use
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+The main idea of this dataset is to train **image-text-to-text LLMs** that can interpret a screenshot and textual prompt **along with screen dimensions and instructions**, e.g., `"open the browser"`.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+The model receives:
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+- **Screenshot of the screen**
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+- **Screen size** `[width, height]`
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+- **Textual instruction** (prompt)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+And outputs:
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+- **Bounding box coordinates** corresponding to where the action should be performed.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+  For example, clicking in the middle of the predicted bounding box executes the instructed action.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+This enables models to perform **UI actions** based on visual context and natural language instructions.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+For example, during training, you can provide the model with a full prompt from an agent system and also add a click tool, supplying the labeled bounding boxes from this dataset in the tool call.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+## Contributions
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
 If you can help with **annotations** or support the dataset **financially**, please send a direct message. The dataset is updated in my spare time.