Update app.py

app.py

@@ -752,73 +752,6 @@ async def create_mask_and_inpaint_simple_lama(
 
 
 
-from PIL import Image
-
-def resize_mask_to_match(image_path, mask_path):
-    # オリジナル画像とマスク画像を読み込む
-    original_image = Image.open(image_path)
-    mask_image = Image.open(mask_path)
-
-    # マスク画像をオリジナル画像のサイズにリサイズ
-    resized_mask = mask_image.resize(original_image.size)
-
-    # マスク画像を上書き保存
-    resized_mask.save(mask_path)
-@app.post("/inpaint_with_face")
-async def face_recognize(
-    image: UploadFile = File(...),
-    face_image: UploadFile = File(...),
-    option: int = Form(...),
-    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)
-    stamp_img = cv2.imread(stamp_path)
-
-    # 顔の位置とエンコーディングを取得
-    face_locations = face_recognition.face_locations(target_image)
-    face_encodings = face_recognition.face_encodings(target_image, face_locations)
-
-    # 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(...),