29 lines
1.1 KiB
Python
29 lines
1.1 KiB
Python
import torch
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import gradio as gr
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model = torch.hub.load("./", "custom", path="best_ffc_11663.pt", source="local")
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title = "鸟类视频检测Yolov5模型测试"
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desc = "这是一个基于Gradio的Yolov5演示项目，非常方便!"
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base_conf, base_iou = 0.5, 0.7
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def det_image(img, conf_thres, iou_thres):
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model.conf = conf_thres
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model.iou = iou_thres
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return model(img).render()[0]
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# examples中的参数要和inputs中对应
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# 获取摄像头拍照检测，修改inputs中的：inputs=[gr.Webcam(),...]就可以了，动态的更新添加属性：live=True
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# 如果将launch()更改为launch(share=True)则会将这个代码放在公网进行访问。
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gr.Interface(
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# inputs=["image", gr.Slider(minimum=0, maximum=1, value=base_conf), gr.Slider(minimum=0, maximum=1, value=base_iou)],
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inputs=[gr.Webcam(),...],
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outputs=["image"],
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fn=det_image,
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title=title,
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description=desc,
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live=True,
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examples=[["./mydata/test/image/Black_Footed_Albatross_0001_796111.jpg", base_conf, base_iou],
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["./mydata/test/image/Gadwall_0001_31235.jpg", 0.3, base_iou]]
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).launch(share=True) |