# `gradio_box_promptable_image`
A webcam-compatible Gradio input image component enabling prompting with bounding boxes.
## Installation
```bash
pip install gradio_box_promptable_image
```
## Usage
```python
import gradio as gr
from gradio_box_promptable_image import BoxPromptableImage
import cv2
YELLOW = (255, 244, 79)
examples = [{"image": "images/cat.png", "points": []}]
def get_box_inputs(prompts):
box_inputs = []
for prompt in prompts:
if prompt[2] == 2.0 and prompt[5] == 3.0:
box_inputs.append((prompt[0], prompt[1], prompt[3], prompt[4]))
return box_inputs
def process_input(input_dict):
img, points = input_dict['image'], input_dict['points']
box_inputs = get_box_inputs(points)
for box in box_inputs:
x1, y1, x2, y2 = int(box[0]), int(box[1]), int(box[2]), int(box[3])
cv2.rectangle(img, (x1, y1), (x2, y2), YELLOW, 2)
return img
demo = gr.Interface(
process_input,
BoxPromptableImage(),
gr.Image(),
examples=examples,
)
if __name__ == "__main__":
demo.launch()
```
## Acknowledgements
Special thanks to the creators of [gradio-image-prompter](https://github.com/PhyscalX/gradio-image-prompter/tree/main?tab=readme-ov-file) - this custom component is heavily adapted from their work.
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"description": "\n# `gradio_box_promptable_image`\n\nA webcam-compatible Gradio input image component enabling prompting with bounding boxes.\n\n## Installation\n\n```bash\npip install gradio_box_promptable_image\n```\n\n## Usage\n\n```python\n\nimport gradio as gr\nfrom gradio_box_promptable_image import BoxPromptableImage\nimport cv2\n\nYELLOW = (255, 244, 79)\n\nexamples = [{\"image\": \"images/cat.png\", \"points\": []}]\n\ndef get_box_inputs(prompts):\n box_inputs = []\n for prompt in prompts:\n if prompt[2] == 2.0 and prompt[5] == 3.0:\n box_inputs.append((prompt[0], prompt[1], prompt[3], prompt[4]))\n\n return box_inputs\n\ndef process_input(input_dict):\n img, points = input_dict['image'], input_dict['points']\n box_inputs = get_box_inputs(points)\n\n for box in box_inputs:\n x1, y1, x2, y2 = int(box[0]), int(box[1]), int(box[2]), int(box[3])\n cv2.rectangle(img, (x1, y1), (x2, y2), YELLOW, 2)\n\n return img\n\ndemo = gr.Interface(\n process_input,\n BoxPromptableImage(),\n gr.Image(),\n examples=examples,\n)\n\nif __name__ == \"__main__\":\n demo.launch()\n\n```\n\n## Acknowledgements\n\nSpecial thanks to the creators of [gradio-image-prompter](https://github.com/PhyscalX/gradio-image-prompter/tree/main?tab=readme-ov-file) - this custom component is heavily adapted from their work.\n\n\n\n",
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