Update app.py

app.py

@@ -18,8 +18,7 @@ def predict_image(image: Image.Image):
             outputs = model(**inputs)
 
         # Step 3: Post-process the outputs
-        # Convert image size to (height, width)
-        target_sizes = torch.tensor([image.size[::-1]])
+        target_sizes = torch.tensor([image.size[::-1]])  # image size needs to be reversed
         results = processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=0.5)[0]
 
         # Step 4: Draw bounding boxes on the image
@@ -29,7 +28,7 @@ def predict_image(image: Image.Image):
             draw.rectangle(box, outline="red", width=2)
             draw.text((box[0], box[1]), f"{model.config.id2label[label.item()]}: {round(score.item(), 3)}", fill="red")
 
-        # Step 5: Return the processed image with status
+        # Step 5: Return the processed image and a success message
         return image, "Object detection complete."
 
     except Exception as e: