From ff6216cdf36fb6450471fbf01a18de9696a44532 Mon Sep 17 00:00:00 2001
From: dddennnisss <dddennnisss.sergeevich@yandex.ru>
Date: Fri, 14 Aug 2026 11:41:48 +0700
Subject: [PATCH] =?UTF-8?q?=D0=A4=D0=B8=D0=BA=D1=81:=20=D0=BF=D0=BE=D0=B4?=
 =?UTF-8?q?=D0=B4=D0=B5=D1=80=D0=B6=D0=BA=D0=B0=20WebP=20=D1=87=D0=B5?=
 =?UTF-8?q?=D1=80=D0=B5=D0=B7=20PIL=20fallback?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 photo_bot/photo_processor.py | 94 +++++++++++++++++++++++-------------
 1 file changed, 61 insertions(+), 33 deletions(-)

diff --git a/photo_bot/photo_processor.py b/photo_bot/photo_processor.py
index b6cde0e..8d8ed9b 100644
--- a/photo_bot/photo_processor.py
+++ b/photo_bot/photo_processor.py
@@ -3,7 +3,7 @@ import cv2
 import logging
 import numpy as np
 import requests
-from PIL import Image, ImageFilter, ImageEnhance
+from PIL import Image
 
 logger = logging.getLogger(__name__)
 
@@ -12,6 +12,26 @@ API_URL = "https://profile.sibcem.ru/SibCemProfile/api/photo-bot/upload/"
 API_KEY = "sibcem_bot_2026_a7f3k9m2x8q1w5e4r6t"
 
 
+def _image_to_cv2(image_bytes: bytes):
+    """Конвертирует байты изображения в OpenCV матрицу (поддержка webp)."""
+    # Сначала пробуем cv2.imdecode
+    nparr = np.frombuffer(image_bytes, np.uint8)
+    img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+    if img is not None:
+        return img
+    
+    # Если не сработало, пробуем через PIL (для webp и других форматов)
+    try:
+        pil_img = Image.open(io.BytesIO(image_bytes))
+        if pil_img.mode != 'RGB':
+            pil_img = pil_img.convert('RGB')
+        img = cv2.cvtColor(np.array(pil_img), cv2.COLOR_RGB2BGR)
+        return img
+    except Exception as e:
+        logger.error(f"Не удалось открыть изображение: {e}")
+        return None
+
+
 def get_crop_coordinates(image_bytes: bytes) -> tuple | None:
     """
     Ищет лицо на фото и возвращает координаты квадратного кропа.
@@ -19,38 +39,46 @@ def get_crop_coordinates(image_bytes: bytes) -> tuple | None:
     Returns:
         (crop_x1, crop_y1, crop_x2, crop_y2) или None если лицо не найдено.
     """
-    img = cv2.imdecode(np.frombuffer(image_bytes, np.uint8), cv2.IMREAD_COLOR)
-    if img is None:
+    try:
+        img = _image_to_cv2(image_bytes)
+        if img is None:
+            logger.warning("Не удалось декодировать изображение")
+            return None
+        
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        
+        cascade_path = cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
+        face_cascade = cv2.CascadeClassifier(cascade_path)
+        faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=8, minSize=(50, 50))
+        
+        if len(faces) == 0:
+            logger.warning("Лицо не найдено на фото")
+            return None
+        
+        if len(faces) > 1:
+            faces = sorted(faces, key=lambda f: f[2] * f[3], reverse=True)
+        
+        x, y, w, h = faces[0]
+        
+        margin = int(w * 0.3)
+        y1 = max(0, y - int(margin * 1.5))
+        y2 = min(img.shape[0], y + h + margin)
+        x1 = max(0, x - margin)
+        x2 = min(img.shape[1], x + w + margin)
+        
+        side = min(x2 - x1, y2 - y1)
+        center_x, center_y = (x1 + x2) // 2, (y1 + y2) // 2
+        crop_x1 = max(0, center_x - side // 2)
+        crop_y1 = max(0, center_y - side // 2)
+        crop_x2 = crop_x1 + side
+        crop_y2 = crop_y1 + side
+        
+        logger.info(f"Лицо найдено: ({x},{y},{w},{h}), кроп: ({crop_x1},{crop_y1},{crop_x2},{crop_y2})")
+        return (crop_x1, crop_y1, crop_x2, crop_y2)
+        
+    except Exception as e:
+        logger.error(f"Ошибка в get_crop_coordinates: {e}", exc_info=True)
         return None
-    
-    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-    
-    cascade_path = cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
-    face_cascade = cv2.CascadeClassifier(cascade_path)
-    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=8, minSize=(50, 50))
-    
-    if len(faces) == 0:
-        return None
-    
-    if len(faces) > 1:
-        faces = sorted(faces, key=lambda f: f[2] * f[3], reverse=True)
-    
-    x, y, w, h = faces[0]
-    
-    margin = int(w * 0.3)
-    y1 = max(0, y - int(margin * 1.5))
-    y2 = min(img.shape[0], y + h + margin)
-    x1 = max(0, x - margin)
-    x2 = min(img.shape[1], x + w + margin)
-    
-    side = min(x2 - x1, y2 - y1)
-    center_x, center_y = (x1 + x2) // 2, (y1 + y2) // 2
-    crop_x1 = max(0, center_x - side // 2)
-    crop_y1 = max(0, center_y - side // 2)
-    crop_x2 = crop_x1 + side
-    crop_y2 = crop_y1 + side
-    
-    return (crop_x1, crop_y1, crop_x2, crop_y2)
 
 
 def _upload_to_api(image_bytes: bytes, user_id: str, coords: tuple) -> dict:
@@ -121,5 +149,5 @@ def prepare_ad_photo(input_path: str, user_id: str, output_path: str = None, tar
             }
 
     except Exception as e:
-        logger.error(f"Ошибка в prepare_ad_photo: {e}")
+        logger.error(f"Ошибка в prepare_ad_photo: {e}", exc_info=True)
         return {"success": False, "error": str(e)}