Update tasks/image.py

tasks/image.py

@@ -178,7 +178,7 @@ async def evaluate_image(request: ImageEvaluationRequest):
         # Threshold and process the segmentation mask
         probabilities = torch.sigmoid(logits)
         predicted_mask = (probabilities[0, 1] > 0.30).cpu().numpy().astype(np.uint8)
-        predicted_mask_resized = cv2.resize(predicted_mask, original_shape[::-1], interpolation=cv2.INTER_NEAREST)
+        predicted_mask_resized = cv2.resize(predicted_mask, (512,512), interpolation=cv2.INTER_NEAREST)
         
         # Extract bounding boxes
         predicted_boxes = get_bounding_boxes_from_mask(predicted_mask_resized)