Update app.py

app.py

@@ -11,7 +11,7 @@ from PIL import Image, ImageFilter
 import numpy as np
 import cv2
 import pycocotools.mask as mask_util
-
+import face_recognition
 from fastapi import FastAPI, File, UploadFile, Form
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import FileResponse, HTMLResponse
@@ -47,7 +47,10 @@ import matplotlib.pyplot as plt
 #この下のコードは特定の領域をマスクしないタイプのコード
 import uuid
 from datetime import datetime
-
+import torch
+import cv2
+import numpy as np
+from ultralytics import YOLO  # YOLOv8ライブラリ
 
 
 import cv2
@@ -648,10 +651,7 @@ def classify_new_image(new_image_vector, sums_data, loaded_vectors, loaded_objec
     new_image_label = knn.predict([new_image_vector])
     return new_image_label[0]
 
-import torch
-import cv2
-import numpy as np
-from ultralytics import YOLO  # YOLOv8ライブラリ
+
 
 def process_image_vec(image_path):
     # GPUを使用できるか確認
@@ -764,7 +764,44 @@ def resize_mask_to_match(image_path, mask_path):
 
     # 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(...)
+):
+    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")
+    
+    # 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)
+
+    # 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
+
+    # 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(...),
@@ -778,14 +815,11 @@ async def create_mask_sum(image: UploadFile = File(...), risk_level: int = Form(
     point1 = [default_x if math.isnan(x1) else x1, default_y if math.isnan(y1) else y1]
 
     point2 = [default_x if math.isnan(x2) else x2, default_y if math.isnan(y2) else y2]
-
-
-    input_path = save_image(image.file, "input.jpg")
-    mask_path = special_process_image_yolo(risk_level, input_path, point1, point2,thresholds=thresholds)
-    # 現在のタイムスタンプを生成
     timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
     # 一意な識別子を生成
     unique_id = uuid.uuid4().hex
+    input_path = save_image(image.file, f"./input_{timestamp}_{unique_id}.jpg")
+    mask_path = special_process_image_yolo(risk_level, input_path, point1, point2,thresholds=thresholds)
     output_path = f"./output_simple_lama_{timestamp}_{unique_id}.jpg"
 
     # OpenCVでインペイント