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修改配置

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zhangpu
2025-11-13 18:03:17 +08:00
parent 3ae8c677ff
commit 5279700e1c
3 changed files with 11 additions and 9 deletions
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faiss_vector_db/build_faiss_index.py
+3 -3
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@@ -146,7 +146,7 @@ class FAISSIndexBuilder:
for image_file in image_files: for image_file in image_files:
# 可以不添加那些增强的图片 # 可以不添加那些增强的图片
if image_file.startswith("img"): if image_file.lower().startswith("img"):
image_path = os.path.join(class_dir, image_file) image_path = os.path.join(class_dir, image_file)
image_paths.append(image_path) image_paths.append(image_path)
class_names.append(class_name) class_names.append(class_name)
@@ -497,8 +497,8 @@ def main():
# 配置参数 # 配置参数
# MODEL_PATH = "../model/embedding_20251011_133653/best_embedding_model.pth" # MODEL_PATH = "../model/embedding_20251011_133653/best_embedding_model.pth"
# MODEL_PATH = "../model/ProcessedIngredientRecognition/embedding_20251103_172012/best_embedding_model.pth" # MODEL_PATH = "../model/ProcessedIngredientRecognition/embedding_20251103_172012/best_embedding_model.pth"
MODEL_PATH = "../model/WholeIngredientRecognition/cosface_20251113_160103/best_cosface_model.pth" # MODEL_PATH = "../model/WholeIngredientRecognition/cosface_20251113_160103/best_cosface_model.pth"
# MODEL_PATH = "../model/WholeIngredientRecognition/grid_search_20251113_095659/model_s68.0_m0.4.pth" MODEL_PATH = "../model/WholeIngredientRecognition/grid_search_20251113_095659/model_s68.0_m0.4.pth"
# MODEL_PATH = "../model/DishClassification/cosface_20251105_200551/best_embedding_model.pth" # MODEL_PATH = "../model/DishClassification/cosface_20251105_200551/best_embedding_model.pth"
# MODEL_PATH = "../model/DishClassification/cosface_20251111_153649/best_cosface_model.pth" # MODEL_PATH = "../model/DishClassification/cosface_20251111_153649/best_cosface_model.pth"
# TRAIN_DIR = "../dataset/ProcessedIngredientRecognition/train" # TRAIN_DIR = "../dataset/ProcessedIngredientRecognition/train"
faiss_vector_db/visualize_embeddings.py
+4 -4
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@@ -162,11 +162,11 @@ def plot_2d(Z: np.ndarray, y: np.ndarray, title: str, out_path: Optional[str] =
def main(): def main():
parser = argparse.ArgumentParser(description="可视化高维 embedding 并进行坍塌诊断") parser = argparse.ArgumentParser(description="可视化高维 embedding 并进行坍塌诊断")
parser.add_argument("--embeddings", type=str, default=os.path.join("DishClassification/faiss_index", "embeddings.json"), help="embeddings.json 路径") # parser.add_argument("--embeddings", type=str, default=os.path.join("DishClassification/faiss_index", "embeddings.json"), help="embeddings.json 路径")
# parser.add_argument("--embeddings", type=str, default=os.path.join("WholeIngredientRecognition/faiss_index", "embeddings.json"), help="embeddings.json 路径") parser.add_argument("--embeddings", type=str, default=os.path.join("WholeIngredientRecognition/faiss_index", "embeddings.json"), help="embeddings.json 路径")
# parser.add_argument("--embeddings", type=str, default=os.path.join("ProcessedIngredientRecognition/faiss_index", "embeddings.json"), help="embeddings.json 路径") # parser.add_argument("--embeddings", type=str, default=os.path.join("ProcessedIngredientRecognition/faiss_index", "embeddings.json"), help="embeddings.json 路径")
parser.add_argument("--labels", type=str, default=os.path.join("DishClassification/faiss_index", "labels.json"), help="labels.json 路径") # parser.add_argument("--labels", type=str, default=os.path.join("DishClassification/faiss_index", "labels.json"), help="labels.json 路径")
# parser.add_argument("--labels", type=str, default=os.path.join("WholeIngredientRecognition/faiss_index", "labels.json"), help="labels.json 路径") parser.add_argument("--labels", type=str, default=os.path.join("WholeIngredientRecognition/faiss_index", "labels.json"), help="labels.json 路径")
# parser.add_argument("--labels", type=str, default=os.path.join("ProcessedIngredientRecognition/faiss_index", "labels.json"), help="labels.json 路径") # parser.add_argument("--labels", type=str, default=os.path.join("ProcessedIngredientRecognition/faiss_index", "labels.json"), help="labels.json 路径")
parser.add_argument("--method", type=str, default="pca", choices=["pca", "tsne", "umap"], help="降维方法") parser.add_argument("--method", type=str, default="pca", choices=["pca", "tsne", "umap"], help="降维方法")
parser.add_argument("--seed", type=int, default=42) parser.add_argument("--seed", type=int, default=42)
toAndroid/toAndroidEmbedding.py
+4 -2
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@@ -17,8 +17,9 @@ def main():
# 1. 加载训练好的embedding模型权重 # 1. 加载训练好的embedding模型权重
# base_model = create_resnet50_embedding(embedding_dim=512, pretrained=True) # base_model = create_resnet50_embedding(embedding_dim=512, pretrained=True)
base_model = create_mobile_resnet50_embedding(embedding_dim=512, pretrained=True) base_model = create_mobile_resnet50_embedding(embedding_dim=512, pretrained=True)
model_path = "../model/DishClassification/cosface_20251110_144822/best_cosface_model.pth" # model_path = "../model/DishClassification/cosface_20251110_144822/best_cosface_model.pth"
# model_path = "../model/WholeIngredientRecognition/cosface_20251106_134718/best_cosface_model.pth" # model_path = "../model/WholeIngredientRecognition/cosface_20251106_134718/best_cosface_model.pth"
model_path = "../model/WholeIngredientRecognition/grid_search_20251113_095659/model_s68.0_m0.4.pth"
# model_path = "../model/ProcessedIngredientRecognition/embedding_20251029_173607/best_embedding_model.pth" # model_path = "../model/ProcessedIngredientRecognition/embedding_20251029_173607/best_embedding_model.pth"
if not os.path.exists(model_path): if not os.path.exists(model_path):
@@ -92,7 +93,8 @@ def main():
traced_model = torch.jit.trace(mobile_wrapper, single_input) traced_model = torch.jit.trace(mobile_wrapper, single_input)
# 保存模型 # 保存模型
output_path = "../model/DishClassification/cosface_20251110_144822/best_embedding_model_mobile.pt" # output_path = "../model/DishClassification/cosface_20251110_144822/best_embedding_model_mobile.pt"
output_path = "../model/WholeIngredientRecognition/grid_search_20251113_095659/best_embedding_model_mobile.pt"
# output_path = "../model/WholeIngredientRecognition/cosface_20251106_134718/best_embedding_model_mobile.pt" # output_path = "../model/WholeIngredientRecognition/cosface_20251106_134718/best_embedding_model_mobile.pt"
# output_path = "../model/ProcessedIngredientRecognition/embedding_20251029_173607/best_embedding_model_mobile.pt" # output_path = "../model/ProcessedIngredientRecognition/embedding_20251029_173607/best_embedding_model_mobile.pt"
traced_model.save(output_path) traced_model.save(output_path)