try get faces

src/diary_cover_similarity.py

@@ -10,7 +10,7 @@ from utils.es import es_query
 from utils.images import face_to_vec, url_to_ndarray
 
 
-def save_diary_image_info(file):
+def save_diary_image_info(file, face_to_vec_f):
     q = {
         "query": {
             "bool": {
@@ -47,7 +47,10 @@ def save_diary_image_info(file):
             diary_id = item["_source"]["id"]
             before_cover_url = item["_source"]["before_cover_url"] + "-w"
             after_cover_url = item["_source"]["after_cover_url"] + "-w"
-            print(str(diary_id) + " " + after_cover_url)
+            # print(str(diary_id) + " " + after_cover_url)
+            img = url_to_ndarray(after_cover_url)
+            faces = face_to_vec_f(img)
+            print(faces)
 
 
 def main():
@@ -63,40 +66,40 @@ def main():
 
     diary_after_cover_vec_file = "./diary_after_cover_vec.txt"
 
-    # save_diary_image_info(diary_after_cover_vec_file)
-
     face_rec = dlib.face_recognition_model_v1(facerec_model_path)
     face_detector = dlib.get_frontal_face_detector()
     shape_predictor = dlib.shape_predictor(shape_model_path)
     face_to_vec_f = lambda img: face_to_vec(img, face_rec, face_detector, shape_predictor)
 
-    if img.any():
-        faces = face_to_vec_f(img)
-
-        if len(faces) > 0:
-            for face in faces:
-                print(face)
-                print("\n")
-                print("-------------")
-                face_feature = np.array(json.loads(face["feature"]))
-
-            ids = [17418645]
-            ids_np = np.array(ids).astype("int")
-            faces_np = np.array([face_feature]).astype("float32")
-            print(ids_np)
-            print(faces_np)
-
-            index = faiss.IndexHNSWFlat(128, 32)
-            print("index: ")
-            print(index)
-            index2 = faiss.IndexIDMap(index)
-            print("index2: ")
-            print(index2)
-            res = index2.add_with_ids(faces_np, ids_np)
-            print("res: ")
-            print(res)
-        else:
-            print("no faces")
+    save_diary_image_info(diary_after_cover_vec_file, face_to_vec_f)
+
+    # if img.any():
+    #     faces = face_to_vec_f(img)
+
+    #     if len(faces) > 0:
+    #         for face in faces:
+    #             print(face)
+    #             print("\n")
+    #             print("-------------")
+    #             face_feature = np.array(json.loads(face["feature"]))
+
+    #         ids = [17418645]
+    #         ids_np = np.array(ids).astype("int")
+    #         faces_np = np.array([face_feature]).astype("float32")
+    #         print(ids_np)
+    #         print(faces_np)
+
+    #         index = faiss.IndexHNSWFlat(128, 32)
+    #         print("index: ")
+    #         print(index)
+    #         index2 = faiss.IndexIDMap(index)
+    #         print("index2: ")
+    #         print(index2)
+    #         index2.add_with_ids(faces_np, ids_np)
+    #         print("index2: ")
+    #         print(index2)
+    #     else:
+    #         print("no faces")
 
 
 if __name__ == "__main__":