Fix download_from_cvat bug: revised based on the new CVAT API.

monailabel/datastore/cvat.py

@@ -225,7 +225,7 @@
         task_id, task_name = self.get_cvat_task_id(project_id, create=False)
         logger.info(f"Preparing to download/update final labels from: {project_id} => {task_id} => {task_name}")
 
-        # Step 1: Initiate export process
+        # Step 1: Initiate export process using the new POST endpoint.
         export_url = f"{self.api_url}/api/tasks/{task_id}/dataset/export?format=Segmentation+mask+1.1&location=local&save_images=false"
         try:
             response = requests.post(export_url, auth=self.auth)
@@ -242,67 +242,71 @@
             logger.exception(f"Error while initiating export process: {e}")
             return None
 
-        # Step 2: Poll export status
+        # Step 2: Poll export status using the new GET endpoint.
         status_url = f"{self.api_url}/api/requests/{rq_id}"
         for _ in range(max_retry_count):
             try:
                 status_response = requests.get(status_url, auth=self.auth)
-                status = status_response.json().get("status")
-                if status == "finished":
+                status_data = status_response.json()
+                current_status = status_data.get("status")
+                if current_status == "finished":
                     logger.info("Export process completed successfully.")
                     break
-                elif status == "failed":
-                    logger.error(f"Export process failed: {status_response.json()}")
+                elif current_status == "failed":
+                    logger.error(f"Export process failed: {status_data}")
                     return None
                 logger.info(f"Export in progress... Retrying in {retry_wait_time} seconds.")
                 time.sleep(retry_wait_time)
             except Exception as e:
                 logger.exception(f"Error checking export status: {e}")
-            time.sleep(retry_wait_time)
+                time.sleep(retry_wait_time)
         else:
             logger.error("Export process did not complete within the maximum retries.")
             return None
 
-        # Step 3: Download the dataset
-        download_url = f"{self.api_url}/api/tasks/{task_id}/annotations?format=Segmentation+mask+1.1&location=local&save_images=false&action=download"
+        # Step 3: Retrieve the download URL from the export status.
+        result_url = status_data.get("result_url")
+        if not result_url:
+            logger.error("Export process finished but no result_url was provided.")
+            return None
+
+        # Step 4: Download the ZIP file from the result_url.
         tmp_folder = tempfile.TemporaryDirectory().name
         os.makedirs(tmp_folder, exist_ok=True)
 
         tmp_zip = tempfile.NamedTemporaryFile(suffix=".zip").name
         retry_count = 0
         for retry in range(max_retry_count):
             try:
-                logger.info(f"Downloading exported dataset from: {download_url}")
-                r = requests.get(download_url, allow_redirects=True, auth=self.auth)
-
+                logger.info(f"Downloading exported dataset from: {result_url}")
+                r = requests.get(result_url, allow_redirects=True, auth=self.auth)
                 with open(tmp_zip, "wb") as fp:
                     fp.write(r.content)
                 shutil.unpack_archive(tmp_zip, tmp_folder)
 
+                # Process the segmentation files
                 segmentations_dir = os.path.join(tmp_folder, "SegmentationClass")
                 final_labels = self._datastore.label_path(DefaultLabelTag.FINAL)
                 for f in os.listdir(segmentations_dir):
                     label = os.path.join(segmentations_dir, f)
                     if os.path.isfile(label) and label.endswith(".png"):
                         os.makedirs(final_labels, exist_ok=True)
-
                         dest = os.path.join(final_labels, f)
                         if self.normalize_label:
                             img = np.array(Image.open(label))
                             mask = np.zeros_like(img)
-
                             labelmap = self._load_labelmap_txt(os.path.join(tmp_folder, "labelmap.txt"))
                             for name, color in labelmap.items():
                                 if name in self.label_map:
                                     idx = self.label_map.get(name)
                                     mask[np.all(img == color, axis=-1)] = idx
-                            Image.fromarray(mask[:, :, 0]).save(dest)  # single channel
-                            logger.info(f"Copy Final Label: {label} to {dest}; unique: {np.unique(mask)}")
+                            Image.fromarray(mask[:, :, 0]).save(dest)
+                            logger.info(f"Copied Final Label: {label} to {dest}; unique: {np.unique(mask)}")
                         else:
                             Image.open(label).save(dest)
-                            logger.info(f"Copy Final Label: {label} to {dest}")
+                            logger.info(f"Copied Final Label: {label} to {dest}")
 
-                # Rename task after consuming/downloading the labels
+                # Rename the task to indicate that labels have been processed.
                 patch_url = f"{self.api_url}/api/tasks/{task_id}"
                 body = {"name": f"{self.done_prefix}_{task_name}"}
                 requests.patch(patch_url, allow_redirects=True, auth=self.auth, json=body)
@@ -311,7 +315,7 @@
                 if retry_count:
                     logger.exception(e)
                 logger.error(f"{retry} => Failed to download...")
-            retry_count = retry_count + 1
+            retry_count += 1
         return None