Update app.py

app.py

@@ -769,14 +769,20 @@ async def face_recognize(
     image: UploadFile = File(...),
     face_image: UploadFile = File(...),
     option: int = Form(...),
-    stamp_image: UploadFile = File(...)
+    stamp_image: UploadFile = File(...),
+    threshold: float = Form(0.8)
 ):
     timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
     unique_id = uuid.uuid4().hex
     input_path = save_image(image.file, f"./input_{timestamp}_{unique_id}.jpg")
     stamp_path = save_image(stamp_image.file, f"./stamp_{timestamp}_{unique_id}.jpg")
     face_path = save_image(face_image.file, f"./face_{timestamp}_{unique_id}.jpg")
-    
+
+    # 認識済みの顔データのエンコード
+    known_face_encodings = []
+    reference_image = face_recognition.load_image_file(face_path)
+    known_face_encodings.append(face_recognition.face_encodings(reference_image)[0])
+
     # 画像の読み込み
     target_image = face_recognition.load_image_file(input_path)
     rgb_image = cv2.cvtColor(target_image, cv2.COLOR_RGB2BGR)
@@ -786,22 +792,34 @@ async def face_recognize(
     face_locations = face_recognition.face_locations(target_image)
     face_encodings = face_recognition.face_encodings(target_image, face_locations)
 
-    # 顔認識してスタンプまたはモザイクで隠す処理
-    for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
-        if option == 1:  # スタンプで隠す
-            stamp_resized = cv2.resize(stamp_img, (right - left, bottom - top))
-            rgb_image[top:bottom, left:right] = stamp_resized
-        elif option == 2:  # モザイクで隠す
-            face_region = rgb_image[top:bottom, left:right]
-            blurred_face = cv2.GaussianBlur(face_region, (99, 99), 30)
-            rgb_image[top:bottom, left:right] = blurred_face
+    # 最も信頼度の高い顔を見つける
+    best_match_index = None
+    min_distance = float("inf")
+    for i, (top, right, bottom, left), face_encoding in zip(range(len(face_locations)), face_locations, face_encodings):
+        face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
+        if np.any(face_distances < threshold):
+            best_index = np.argmin(face_distances)
+            if face_distances[best_index] < min_distance:
+                min_distance = face_distances[best_index]
+                best_match_index = i  # 最も信頼度の高い顔のインデックス
+
+    # 最も信頼度の高い顔以外を隠す
+    for i, (top, right, bottom, left) in enumerate(face_locations):
+        if i != best_match_index:  # 信頼度の高い顔以外を隠す
+            if option == 1:  # スタンプで隠す
+                stamp_resized = cv2.resize(stamp_img, (right - left, bottom - top))
+                rgb_image[top:bottom, left:right] = stamp_resized
+            elif option == 2:  # モザイクで隠す
+                face_region = rgb_image[top:bottom, left:right]
+                blurred_face = cv2.GaussianBlur(face_region, (99, 99), 30)
+                rgb_image[top:bottom, left:right] = blurred_face
 
     # 結果を保存または返却 (ここでは仮に保存)
     output_path = f"./output_{timestamp}_{unique_id}.jpg"
     cv2.imwrite(output_path, rgb_image)
 
     return FileResponse(output_path)
-    
+
 @app.post("/create-mask-and-inpaint-sum")
 async def create_mask_sum(image: UploadFile = File(...), risk_level: int = Form(...),
     x1: float = Form(...),