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| """ | |
| Source: https://github.com/AK391/yolov5/blob/master/utils/gradio/demo.py | |
| """ | |
| import gradio as gr | |
| import torch | |
| from PIL import Image | |
| model = torch.hub.load('ultralytics/yolov5', 'custom', 'best.pt') # force_reload=True to update | |
| def yolo(im, size=640): | |
| g = (size / max(im.size)) # gain | |
| im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS) # resize | |
| results = model(im) # inference | |
| results.render() # updates results.ims with boxes and labels | |
| return Image.fromarray(results.ims[0]) | |
| inputs = gr.inputs.Image(type='pil', label="Original Image") | |
| outputs = gr.outputs.Image(type="pil", label="Output Image") | |
| title = "YOLOv5" | |
| description = "YOLOv5 demo for fire detection. Upload an image or click an example image to use." | |
| article = "See https://github.com/robmarkcole/fire-detection-from-images" | |
| examples = [['pan-fire.jpg'], ['fire-basket.jpg']] | |
| gr.Interface(yolo, inputs, outputs, title=title, description=description, article=article, examples=examples).launch( | |
| debug=True) |