Update app.py

app.py

@@ -194,7 +194,7 @@ async def predict_single_dog(image):
     return top1_prob, topk_breeds, topk_probs_percent
     
 
-async def detect_multiple_dogs(image, conf_threshold=0.3, iou_threshold=0.5):
+async def detect_multiple_dogs(image, conf_threshold=0.25, iou_threshold=0.4):
     results = model_yolo(image, conf=conf_threshold, iou=iou_threshold)[0]
     dogs = []
     boxes = []
@@ -471,7 +471,7 @@ async def predict(image):
                 breed = topk_breeds[0]
                 description = get_dog_description(breed)
                 formatted_description = format_description(description, breed)
-                explanations.append(f"Dog {i+1}: Breed: {breed}\n{formatted_description}")
+                explanations.append(f"Dog {i+1}: {formatted_description}")
             elif combined_confidence >= 0.2:
                 dog_explanation = f"Dog {i+1}: Top 3 possible breeds:\n"
                 dog_explanation += "\n".join([f"{j+1}. **{breed}** ({prob} confidence)" for j, (breed, prob) in enumerate(zip(topk_breeds[:3], topk_probs_percent[:3]))])