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pig-model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2a5a3df8e9773340edd13cc3fa09b349de350f1cb7fb986bb9af1a44787e7a27
+size 87818949

requirements.txt

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+torch==2.0.0+cpu
+fastai==2.7.12

same-pig.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[4]:
+
+
+import gradio as gr
+from fastai.vision.all import *
+import PIL
+import torchvision.transforms as T
+
+
+def get_y(f):
+    return int(f.parent.name)-1
+
+# 加载模型
+learn = load_learner('pig-model.pkl')
+
+def predict_image(img1, img2):
+    
+    # 将图像转换为 PIL Image 类型
+    img1 = Image.fromarray(img1)  
+    img2 = Image.fromarray(img2) 
+    
+
+    pred1, _, _ = learn.predict(img1)
+    pred2, _, _ = learn.predict(img2)
+    
+    #print("pred1:",pred1,"pred2:",pred2)
+
+    if pred1 == pred2:
+        # 返回预测结果
+        return {"是否是同一头猪": "这是同一头猪"}
+    else:
+        # 返回预测结果
+        return {"是否是同一头猪": "这不是同一头猪"}
+    
+
+
+# 创建 Gradio 接口
+iface = gr.Interface(
+    fn=predict_image,
+    inputs=[
+        gr.inputs.Image(label="Image 1"),
+        gr.inputs.Image(label="Image 2")
+    ],
+    outputs="text",
+    title="猪照片识别模型",
+    description="检测两张图片是否是同一只猪。"
+)
+
+# 启动 Gradio 接口
+iface.launch()
+