image
image | mapped_denorm_bboxes
list | source
string |
---|---|---|
[
{
"bbox": [
18,
706,
18,
28
],
"texts": [
"open terminal",
"click terminal icon",
"open console"
]
}
] |
original
|
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 formatmapped_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 systemtexts
: List of textual descriptions associated with the bounding box (e.g.,"click on my profile"
)
Data Fields
image
: Image file in PNG formatmapped_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): 174 exampleswindows
(train): 166 exampleslinux-ubuntu
(train): 1 exampleslinux-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
If you can help with annotations or support the dataset financially, please send a direct message. The dataset is updated in my spare time.
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