Update app.py

app.py

@@ -195,7 +195,7 @@ async def predict_single_dog(image):
     
 #     return dogs
 
-async def detect_multiple_dogs(image, conf_threshold=0.35, iou_threshold=0.55):
+async def detect_multiple_dogs(image, conf_threshold=0.25, iou_threshold=0.6):
     results = model_yolo(image, conf=conf_threshold, iou=iou_threshold)[0]
     dogs = []
     boxes = []
@@ -221,7 +221,6 @@ async def detect_multiple_dogs(image, conf_threshold=0.35, iou_threshold=0.55):
     return dogs
 
 def is_valid_dog(image):
-    # 將PIL Image轉換為numpy陣列
     img_array = np.array(image)
     
     # 1. 簡單的紋理檢測
@@ -235,11 +234,13 @@ def is_valid_dog(image):
     colors = kmeans.cluster_centers_
     color_variety = np.std(colors)
     
-    # 3. 形狀檢測（簡化版，檢查長寬比）
+    # 3. 形狀檢測（檢查長寬比和面積）
     aspect_ratio = image.width / image.height
+    area_ratio = (image.width * image.height) / (image.width * image.height)
     
-    # 根據特徵綜合判斷
-    if texture > 10 and color_variety > 30 and 0.5 < aspect_ratio < 2:
+    # 放寬判斷條件
+    if (texture > 5 and color_variety > 20 and 
+        0.3 < aspect_ratio < 3 and area_ratio > 0.05):
         return True
     return False