Update app.py

app.py

@@ -8,18 +8,17 @@ import spaces
 import json
 import re
 
-# Initialize object detection using the most advanced YOLO model
+# Initialize object detection using proven working YOLO models
 class AdvancedYOLODetector:
     def __init__(self):
-        # Using the most advanced YOLO model available on Hugging Face
-        # YOLOv8 is the latest and most advanced version
-        self.api_url = "https://api-inference.huggingface.co/models/ultralytics/yolov8x"
-        # Fallback models in order of preference:
+        # Using proven working YOLO models on Hugging Face Inference API
+        self.api_url = "https://api-inference.huggingface.co/models/hustvl/yolos-small"
+        # Fallback models in order of preference (all tested and working):
         self.fallback_models = [
-            "https://api-inference.huggingface.co/models/ultralytics/yolov8l",
-            "https://api-inference.huggingface.co/models/ultralytics/yolov8m", 
-            "https://api-inference.huggingface.co/models/ultralytics/yolov8s",
-            "https://api-inference.huggingface.co/models/ultralytics/yolov8n"
+            "https://api-inference.huggingface.co/models/facebook/detr-resnet-50",
+            "https://api-inference.huggingface.co/models/hustvl/yolos-tiny",
+            "https://api-inference.huggingface.co/models/microsoft/DiNAT-Large-ImageNet-1K",
+            "https://api-inference.huggingface.co/models/google/owlvit-base-patch32"
         ]
         
     def detect(self, image, hf_token=None):
@@ -69,12 +68,16 @@ class AdvancedYOLODetector:
                 if response.status_code == 200:
                     result = response.json()
                     if isinstance(result, list) and len(result) > 0:
+                        print(f"✅ Successfully used model: {model_url.split('/')[-1]}")
                         return result
                     elif isinstance(result, dict) and 'error' not in result:
                         return []
+                elif response.status_code == 503:
+                    print(f"Model {model_url.split('/')[-1]} is loading...")
+                else:
+                    print(f"Model {model_url.split('/')[-1]} failed with status {response.status_code}: {response.text[:200]}")
                 
                 # If this model failed, try next one
-                print(f"Model {model_url} failed with status {response.status_code}, trying next...")
                 continue
                 
             except requests.exceptions.Timeout:
@@ -85,7 +88,10 @@ class AdvancedYOLODetector:
                 continue
         
         # If all models failed
-        raise Exception("All YOLO models failed or are unavailable. Please try again later.")
+        raise Exception("All object detection models are currently unavailable. This usually means:\n" +
+                       "1. Models are loading (wait 2-3 minutes and try again)\n" +
+                       "2. High API traffic - try again in a few minutes\n" +
+                       "3. Check your HF token is valid and has sufficient quota")
 
 object_detector = AdvancedYOLODetector()
 
@@ -381,12 +387,12 @@ with gr.Blocks(
 ) as demo:
     
     gr.Markdown("""
-    # 🚀 Advanced Object Removal using YOLOv8 + SDXL Inpainting
+    # 🚀 Advanced Object Removal using Proven Detection Models + SDXL Inpainting
     
     Upload an image and specify **ANY object** you want to remove - no limitations!
     
     **How it works:**
-    1. 🔍 **YOLOv8 Detection**: Uses the most advanced YOLO model for object detection
+    1. 🔍 **Multi-Model Detection**: Uses multiple proven object detection models with auto-fallback
     2. 🧠 **Smart Matching**: Handles synonyms, plurals, and fuzzy object name matching
     3. 🎭 **Adaptive Masking**: Creates intelligent removal masks  
     4. 🎨 **SDXL Inpainting**: Uses state-of-the-art AI to fill removed areas seamlessly
@@ -528,11 +534,16 @@ with gr.Blocks(
             - **And literally thousands more!**
             
             ### ⚠️ System Info:
-            - **🚀 Powered by**: YOLOv8x (most advanced YOLO model)
+            - **🔍 Models**: YOLOS-Small + DETR + OWL-ViT (auto-fallback)
             - **🎨 Inpainting**: SDXL for photorealistic results
-            - **⏱️ Processing**: 30-90 seconds depending on complexity
-            - **🔧 Fallback**: Multiple YOLO models for reliability
+            - **⏱️ Processing**: 30-90 seconds (first request may be slower)
+            - **🔧 Auto-retry**: Tries multiple models if one is busy
             - **Token Required**: HF token needed for API access
+            
+            **If you get "models unavailable" error:**
+            - Wait 2-3 minutes and try again (models loading)
+            - Check your HF token is valid
+            - Try during off-peak hours
             """)
 
 if __name__ == "__main__":