更改配置文件
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@@ -17,8 +17,8 @@ def main():
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# 1. 加载训练好的embedding模型权重
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# base_model = create_resnet50_embedding(embedding_dim=512, pretrained=True)
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base_model = create_mobile_resnet50_embedding(embedding_dim=512, pretrained=True)
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# model_path = "../model/DishClassification/cosface_20251105_200551/best_cosface_model.pth"
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model_path = "../model/WholeIngredientRecognition/cosface_20251106_134718/best_cosface_model.pth"
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model_path = "../model/DishClassification/cosface_20251110_144822/best_cosface_model.pth"
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# model_path = "../model/WholeIngredientRecognition/cosface_20251106_134718/best_cosface_model.pth"
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# model_path = "../model/ProcessedIngredientRecognition/embedding_20251029_173607/best_embedding_model.pth"
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if not os.path.exists(model_path):
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@@ -92,8 +92,8 @@ def main():
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traced_model = torch.jit.trace(mobile_wrapper, single_input)
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# 保存模型
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# output_path = "../model/DishClassification/cosface_20251105_200551/best_embedding_model_mobile.pt"
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output_path = "../model/WholeIngredientRecognition/cosface_20251106_134718/best_embedding_model_mobile.pt"
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output_path = "../model/DishClassification/cosface_20251110_144822/best_embedding_model_mobile.pt"
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# output_path = "../model/WholeIngredientRecognition/cosface_20251106_134718/best_embedding_model_mobile.pt"
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# output_path = "../model/ProcessedIngredientRecognition/embedding_20251029_173607/best_embedding_model_mobile.pt"
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traced_model.save(output_path)
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print(f"✓ TorchScript模型保存成功: {output_path}")
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