Upload app.py

app.py

@@ -795,33 +795,11 @@ class CLIPService:
             if max(image.size) > max_size:
                 image.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
             
-            # Try multiple processor configurations
-            try:
-                # Method 1: Standard CLIP processing
-                inputs = self.clip_processor(
-                    images=image, 
-                    return_tensors="pt",
-                    do_rescale=True,
-                    do_normalize=True
-                )
-            except Exception as e1:
-                logger.warning(f"Method 1 failed: {e1}, trying method 2...")
-                try:
-                    # Method 2: With padding
-                    inputs = self.clip_processor(
-                        images=image, 
-                        return_tensors="pt",
-                        padding=True,
-                        do_rescale=True,
-                        do_normalize=True
-                    )
-                except Exception as e2:
-                    logger.warning(f"Method 2 failed: {e2}, trying method 3...")
-                    # Method 3: Manual preprocessing
-                    inputs = self.clip_processor(
-                        images=[image], 
-                        return_tensors="pt"
-                    )
+            # Use the working method directly (Method 3) to avoid fallback overhead
+            inputs = self.clip_processor(
+                images=[image], 
+                return_tensors="pt"
+            )
             
             inputs = {k: v.to(self.device) for k, v in inputs.items()}