只是更改了一些配置
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@@ -61,7 +61,7 @@ class EmbeddingFoodClassifierApp:
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"""加载训练好的embedding模型和FAISS索引"""
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try:
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# 模型路径
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model_path = "../model/embedding_20250930_102826/best_embedding_model.pth"
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model_path = "../model/embedding_20251010_111257/best_embedding_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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@@ -62,7 +62,7 @@ class EmbeddingFoodClassifierApp:
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"""加载训练好的embedding模型和FAISS索引"""
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try:
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# 模型路径
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model_path = "../model/embedding_20250930_102826/best_embedding_model.pth"
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model_path = "../model/embedding_20251010_111257/best_embedding_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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@@ -1136,8 +1136,8 @@ class EmbeddingFoodClassifierApp:
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topk_scores, topk_indices = torch.topk(sims, k=min(k, sims.shape[1]), dim=1)
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indices = topk_indices.cpu().numpy()
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scores = topk_scores.cpu().numpy()
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# print("相似度索引:", indices)
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# print("相似度分数:", scores)
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print("相似度索引:", indices)
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print("相似度分数:", scores)
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# 收集相似图片的类别
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similar_classes = []
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@@ -27,7 +27,7 @@ for class_name in os.listdir(input_root):
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input_dir = os.path.join(input_root, class_name)
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output_dir = os.path.join(output_root, class_name)
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os.makedirs(output_dir, exist_ok=True)
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if class_name == "肉沫酸豆角":
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if class_name == "手撕包菜":
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# 读取类别下所有图片路径
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img_files = [f for f in os.listdir(input_dir) if f.lower().endswith(('.jpg', '.png', '.jpeg'))]
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img_paths = [os.path.join(input_dir, f) for f in img_files]
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@@ -477,7 +477,7 @@ class FAISSSearcher:
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def main():
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"""主函数"""
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# 配置参数
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MODEL_PATH = "../model/embedding_20250930_102826/best_embedding_model.pth"
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MODEL_PATH = "../model/embedding_20251010_111257/best_embedding_model.pth"
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TRAIN_DIR = "../dataset/train"
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OUTPUT_DIR = "faiss_index"
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BATCH_SIZE = 16
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