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| import gradio as gr | |
| from FootDetection import FootDetection | |
| # Initialize model (first run will auto-download weights) | |
| foot_detection = FootDetection("cpu") # "cuda" for GPU or "mps" for App | |
| def detect(img, threshold): | |
| results = foot_detection.detect(img, threshold=threshold) | |
| img_with_boxes = foot_detection.draw_boxes(img) | |
| return img_with_boxes | |
| demo = gr.Interface(fn=detect, | |
| title='Foot Detection', | |
| description="""by [Tony Assi](https://www.tonyassi.com/) | |
| [Model](https://huggingface.co/tonyassi/foot-detection) [Github](https://github.com/TonyAssi/foot-detection) | |
| A lightweight Python module for detecting feet or shoes in images using a fine-tuned Faster R-CNN model (PyTorch + Torchvision). tony.assi.media@gmail.com for inquiries. """, | |
| inputs=[gr.Image(label='Input', type='pil'), gr.Slider(label='Threshold', minimum=0.0, maximum=1.0, value=0.3)], | |
| outputs=gr.Image(label='Result', type='pil'), | |
| cache_examples=True, | |
| examples=[['examples/1.jpg', 0.3], ['examples/2.jpg', 0.3], ['examples/3.jpg', 0.3], ['examples/4.jpg', 0.3], ['examples/5.jpg', 0.3], ['examples/6.jpg', 0.3]]) | |
| demo.launch() | |