Update app.py

app.py

@@ -10,15 +10,15 @@ model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 # Prediction function
 def predict_image(image: Image.Image):
     try:
-        # Step 1: Preprocess the image with padding enabled
+        # Step 1: Preprocess the image with padding and ensure it is batched
         inputs = processor(images=image, return_tensors="pt", padding=True)
         
-        # Step 2: Run inference without gradients
+        # Step 2: Run inference (no gradients)
         with torch.no_grad():
             outputs = model(**inputs)
 
         # Step 3: Post-process the outputs
-        target_sizes = torch.tensor([image.size[::-1]])  # image size needs to be reversed
+        target_sizes = torch.tensor([image.size[::-1]])  # image size reversed to match model format
         results = processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=0.5)[0]
 
         # Step 4: Draw bounding boxes on the image