save feature to redis

face_similarity/diary_cover_similarity.py

@@ -77,21 +77,23 @@ def save_diary_image_info():
         }
     }
     count = 0
-    res_dict = {}
+    # before_res_dict = {}
+    after_res_dict = {}
     results = es_scan("diary", q)
     for item in results:
-        if count <= 15:
-            diary_id = item["_id"]
-            # before_cover_url = item["_source"]["before_cover_url"] + "-w"
-            after_cover_url = item["_source"]["after_cover_url"] + "-w"
-            img = url_to_ndarray(after_cover_url)
-            if img.any():
-                count += 1
-                print("count: " + str(count) + " " + str(diary_id))
-                faces = FACE_TO_VEC_FUN(img)
-                for face in faces:
-                    res_dict[diary_id] = face["feature"]
-    print(res_dict)
+        diary_id = item["_id"]
+        # before_cover_url = item["_source"]["before_cover_url"] + "-w"
+        # before_img = url_to_ndarray(before_cover_url)
+
+        after_cover_url = item["_source"]["after_cover_url"] + "-w"
+        img = url_to_ndarray(after_cover_url)
+        if img.any():
+            count += 1
+            print("count: " + str(count) + " " + str(diary_id))
+            faces = FACE_TO_VEC_FUN(img)
+            for face in faces:
+                after_res_dict[diary_id] = face["feature"]
+    redis_client_db.hmset("strategy_embedding:diary:cover:after", after_res_dict)
 
 
 def save_faiss_index(load_file, save_path):