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import torch |
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from PIL import Image |
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import gradio as gr |
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model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt', force_reload=True) |
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model.conf = 0.6 |
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model.iou = 0.2 |
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def predict(image): |
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results = model(image, size=1088) |
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annotated_image = results.render() |
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labeled_image = Image.fromarray(annotated_image[0]) if annotated_image else Image.fromarray(np.array(image)) |
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num_objects = len(results.xyxy[0]) |
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return labeled_image, num_objects |
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iface = gr.Interface( |
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fn=predict, |
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inputs=gr.components.Image(type='pil', label="上传mwr~~的图片"), |
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outputs=[gr.components.Image(type='pil', label="含标记的图片结果"), gr.components.Label(label="总币数")], |
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title="数金币", |
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description="只能识别个数" |
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) |
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iface.launch(debug=True) |
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