Create app.py

app.py

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+import gradio as gr
+import cv2
+import torch
+
+def detect_objects(frame):
+    results = model(frame)
+
+    for *box, conf, cls in results.xyxy[0]:
+        label = f'{model.names[int(cls)]} {conf:.2f}'
+        frame = cv2.rectangle(frame, (int(box[0]), int(box[1])), (int(box[2]), int(box[3])), (255, 0, 0), 2)
+        frame = cv2.putText(frame, label, (int(box[0]), int(box[1]) - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (255, 0, 0), 2)
+
+    return cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+
+model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)
+video = gr.inputs.Video(type='opencv', label="输入视频")
+output = gr.outputs.Image(type='pil',label="检测结果")
+
+iface = gr.Interface(fn=detect_objects, inputs=video, outputs=output, title="目标检测")
+iface.launch(share=True)