Create app.py

app.py

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+import gradio.inputs
+import torch
+import gradio as gr
+from PIL import Image
+import tempfile
+import detect
+import os
+import shutil
+
+
+# result = detect.run(source=img, data="VOCdevkit/FLIR.yaml", weights="./best.pt")
+
+def de(image):
+    # 创建临时文件夹
+    temp_path = tempfile.TemporaryDirectory(dir="./")
+    temp_dir = temp_path.name
+    # 临时图片的路径
+    temp_image_path = os.path.join(temp_dir, f"temp.jpg")
+    # 存储临时图片
+    img = Image.fromarray(image)
+    img.save(temp_image_path)
+    # 结果图片的存储目录
+    temp_result_path = os.path.join(temp_dir, "tempresult")
+    # 对临时图片进行检测
+    detect.run(source=temp_image_path, data="OCdevkit/FLIR.yaml", weights="./runs/train/exp/weights/best.pt", project=f'./{temp_dir}',name = 'tempresult', hide_conf=True)
+    # 结果图片的路径
+    temp_result_path = os.path.join(temp_result_path, os.listdir(temp_result_path)[0])
+    # 读取结果图片
+    result_image = Image.open(temp_result_path).copy()
+    # 删除临时文件夹
+    temp_path.cleanup()
+
+    return result_image
+
+example_image= [
+    ["./VOCdevkit/images/train/video-2SReBn5LtAkL5HMj2-frame-005072-MA7NCLQGoqq9aHaiL.jpg"],
+    ["./VOCdevkit/images/train/video-2rsjnZFyGQGeynfbv-frame-003708-6fPQbB7jtibwaYAE7.jpg"],
+    ["./VOCdevkit/images/train/video-2SReBn5LtAkL5HMj2-frame-000317-HTgPBFgZyPdwQnNvE.jpg"],
+    ["./VOCdevkit/images/val/video-jNQtRj6NGycZDEXpe-frame-002515-J3YntG8ntvZheKK3P.jpg"],
+    ["./VOCdevkit/images/val/video-kDDWXrnLSoSdHCZ7S-frame-003063-eaKjPvPskDPjenZ8S.jpg"],
+    ["./VOCdevkit/images/val/video-r68Yr9RPWEp5fW2ZF-frame-000333-X6K5iopqbmjKEsSqN.jpg"]
+    ]
+
+iface = gr.Interface(fn=de, inputs=gr.Image(label="上传一张红外图像,仅支持jpg格式"), outputs="image", examples=example_image, share=True)
+iface.launch(share=True)
+
+
+
+
+