Update app.py

app.py

@@ -87,51 +87,25 @@ def segment_clothing(img, clothes=["Hat", "Upper-clothes", "Skirt", "Pants", "Dr
     return img_with_alpha.convert("RGB"), final_mask, detected_categories  # Return detected categories
 
 
-#def find_similar_images(query_embedding, collection, top_k=5):
-#    all_embeddings = collection.get(include=['embeddings'])['embeddings']
-#    database_embeddings = np.array(all_embeddings)
-#    similarities = np.dot(database_embeddings, query_embedding.T).squeeze()
-#    top_indices = np.argsort(similarities)[::-1][:top_k]
-#    
-#    all_data = collection.get(include=['metadatas'])['metadatas']
-#    top_metadatas = [all_data[idx] for idx in top_indices]
-    
-#    results = []
-#    for idx, metadata in enumerate(top_metadatas):
-#        results.append({
-#            'info': metadata,
-#            'similarity': similarities[top_indices[idx]]
-#        })
-#    return results
-
 def find_similar_images(query_embedding, collection, top_k=5):
-    # 모든 임베딩을 가져옴
     all_embeddings = collection.get(include=['embeddings'])['embeddings']
     database_embeddings = np.array(all_embeddings)
-    
-    # 유사도 계산
-    similarities = cosine_similarity(database_embeddings, query_embedding.reshape(1, -1)).squeeze()
+    similarities = np.dot(database_embeddings, query_embedding.T).squeeze()
     top_indices = np.argsort(similarities)[::-1][:top_k]
     
-    # 메타데이터 가져옴
     all_data = collection.get(include=['metadatas'])['metadatas']
     top_metadatas = [all_data[idx] for idx in top_indices]
     
     results = []
     for idx, metadata in enumerate(top_metadatas):
-        # 이미지 URLs 필드가 쉼표로 구분된 문자열로 저장된 경우, 이를 리스트로 변환
-        image_urls = metadata['image_url'].split(',')
-        # 첫 번째 이미지를 대표 이미지로 사용
-        representative_image_url = image_urls[0] if image_urls else None
-        
         results.append({
             'info': metadata,
-            'similarity': similarities[top_indices[idx]],
-            'image_url': representative_image_url  # 첫 번째 이미지 URL 사용
+            'similarity': similarities[top_indices[idx]]
         })
     return results
 
 
+
 # 세션 상태 초기화
 if 'step' not in st.session_state:
     st.session_state.step = 'input'