更改配置文件
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@@ -66,15 +66,15 @@ class EmbeddingFoodClassifierApp:
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# model_path = "../model/embedding_20251011_133653/best_embedding_model.pth"
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# model_path = os.path.join(BASE_DIR, "../model/embedding_20251011_133653/best_embedding_model.pth")
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# model_path = os.path.join(BASE_DIR, "../model/ProcessedIngredientRecognition/embedding_20251029_170904/best_embedding_model.pth")
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model_path = os.path.join(BASE_DIR, "../model/WholeIngredientRecognition/cosface_20251106_134718/best_cosface_model.pth")
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# model_path = os.path.join(BASE_DIR, "../model/DishClassification/cosface_20251105_200551/best_cosface_model.pth")
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# model_path = os.path.join(BASE_DIR, "../model/WholeIngredientRecognition/cosface_20251106_134718/best_cosface_model.pth")
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model_path = os.path.join(BASE_DIR, "../model/DishClassification/cosface_20251110_144822/best_cosface_model.pth")
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# FAISS索引目录
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# index_dir = "../faiss_vector_db/faiss_index"
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# index_dir = os.path.join(BASE_DIR, "../faiss_vector_db/faiss_index")
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# index_dir = os.path.join(BASE_DIR, "../faiss_vector_db/ProcessedIngredientRecognition/faiss_index")
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index_dir = os.path.join(BASE_DIR, "../faiss_vector_db/WholeIngredientRecognition/faiss_index")
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# index_dir = os.path.join(BASE_DIR, "../faiss_vector_db/DishClassification/faiss_index")
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# index_dir = os.path.join(BASE_DIR, "../faiss_vector_db/WholeIngredientRecognition/faiss_index")
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index_dir = os.path.join(BASE_DIR, "../faiss_vector_db/DishClassification/faiss_index")
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if os.path.exists(model_path) and os.path.exists(index_dir):
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# 1. 加载embedding模型
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@@ -497,16 +497,16 @@ def main():
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# 配置参数
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# MODEL_PATH = "../model/embedding_20251011_133653/best_embedding_model.pth"
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# MODEL_PATH = "../model/ProcessedIngredientRecognition/embedding_20251103_172012/best_embedding_model.pth"
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MODEL_PATH = "../model/WholeIngredientRecognition/cosface_20251106_134718/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_20251105_200551/best_embedding_model.pth"
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# MODEL_PATH = "../model/DishClassification/cosface_20251105_200551/best_cosface_model.pth"
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MODEL_PATH = "../model/DishClassification/cosface_20251110_144822/best_cosface_model.pth"
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# TRAIN_DIR = "../dataset/ProcessedIngredientRecognition/train"
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TRAIN_DIR = "../dataset/WholeIngredientRecognition/train"
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# TRAIN_DIR = "../dataset/DishClassification/train"
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# TRAIN_DIR = "../dataset/WholeIngredientRecognition/train"
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TRAIN_DIR = "../dataset/DishClassification/train"
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# OUTPUT_DIR = "ProcessedIngredientRecognition/faiss_index"
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OUTPUT_DIR = "WholeIngredientRecognition/faiss_index"
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# OUTPUT_DIR = "DishClassification/faiss_index"
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# OUTPUT_DIR = "WholeIngredientRecognition/faiss_index"
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OUTPUT_DIR = "DishClassification/faiss_index"
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BATCH_SIZE = 16
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INDEX_TYPE = 'flat' # 'flat', 'ivf', 'hnsw'
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EMBEDDING_DIM = 512
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@@ -162,11 +162,11 @@ def plot_2d(Z: np.ndarray, y: np.ndarray, title: str, out_path: Optional[str] =
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def main():
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parser = argparse.ArgumentParser(description="可视化高维 embedding 并进行坍塌诊断")
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# parser.add_argument("--embeddings", type=str, default=os.path.join("DishClassification/faiss_index", "embeddings.json"), help="embeddings.json 路径")
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parser.add_argument("--embeddings", type=str, default=os.path.join("WholeIngredientRecognition/faiss_index", "embeddings.json"), help="embeddings.json 路径")
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parser.add_argument("--embeddings", type=str, default=os.path.join("DishClassification/faiss_index", "embeddings.json"), help="embeddings.json 路径")
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# parser.add_argument("--embeddings", type=str, default=os.path.join("WholeIngredientRecognition/faiss_index", "embeddings.json"), help="embeddings.json 路径")
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# parser.add_argument("--embeddings", type=str, default=os.path.join("ProcessedIngredientRecognition/faiss_index", "embeddings.json"), help="embeddings.json 路径")
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# parser.add_argument("--labels", type=str, default=os.path.join("DishClassification/faiss_index", "labels.json"), help="labels.json 路径")
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parser.add_argument("--labels", type=str, default=os.path.join("WholeIngredientRecognition/faiss_index", "labels.json"), help="labels.json 路径")
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parser.add_argument("--labels", type=str, default=os.path.join("DishClassification/faiss_index", "labels.json"), help="labels.json 路径")
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# parser.add_argument("--labels", type=str, default=os.path.join("WholeIngredientRecognition/faiss_index", "labels.json"), help="labels.json 路径")
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# parser.add_argument("--labels", type=str, default=os.path.join("ProcessedIngredientRecognition/faiss_index", "labels.json"), help="labels.json 路径")
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parser.add_argument("--method", type=str, default="pca", choices=["pca", "tsne", "umap"], help="降维方法")
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parser.add_argument("--seed", type=int, default=42)
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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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@@ -347,8 +347,8 @@ def main(task_key: str = 'dish', s: float = 64.0, m: float = 0.35, num_epochs: i
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if __name__ == '__main__':
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import argparse
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parser = argparse.ArgumentParser()
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# parser.add_argument('task', choices=list(TASKS.keys()), nargs='?', default='dish')
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parser.add_argument('task', choices=list(TASKS.keys()), nargs='?', default='whole_ingredient')
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parser.add_argument('task', choices=list(TASKS.keys()), nargs='?', default='dish')
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# parser.add_argument('task', choices=list(TASKS.keys()), nargs='?', default='whole_ingredient')
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parser.add_argument('--s', type=float, default=64.0)
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parser.add_argument('--m', type=float, default=0.35)
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parser.add_argument('--epochs', type=int, default=60)
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