change image download method to async

src/main.py

@@ -2,6 +2,7 @@
 import json
 import os
 from distutils.util import strtobool
+import asyncio
 
 import supervisely as sly
 from dotenv import load_dotenv
@@ -80,15 +81,31 @@ def export_to_coco(api: sly.Api) -> None:
             total_cnt=len(images),
             min_report_percent=5,
         )
-        for batch in sly.batched(images):
-            image_ids = [image_info.id for image_info in batch]
-            sly.logger.info(f"Working with batch of {len(batch)} images with ids: {image_ids}")
 
-            if selected_output == "images":
-                image_paths = [os.path.join(img_dir, image_info.name) for image_info in batch]
-                f.download_batch_with_retry(api, dataset.id, image_ids, image_paths)
+        dataset_path = os.path.join(img_dir, project.name, dataset.name)
+        os.makedirs(dataset_path, exist_ok=True)
+
+        if selected_output == "images":
+            image_ids = [image_info.id for image_info in images]
+            paths = [os.path.join(dataset_path, image_info.name) for image_info in images]
+            if api.server_address.startswith("https://"):
+                semaphore = asyncio.Semaphore(100)
+            else:
+                semaphore = None
+            # api._get_default_semaphore()
+            coro = api.image.download_paths_async(
+                image_ids, paths, semaphore, progress_cb=ds_progress.iters_done_report
+            )
+            loop = sly.utils.get_or_create_event_loop()
+            if loop.is_running():
+                future = asyncio.run_coroutine_threadsafe(coro, loop)
+                future.result()
+            else:
+                loop.run_until_complete(coro)
 
-            ann_infos = api.annotation.download_batch(dataset.id, image_ids)
+        for batch in sly.batched(images):
+            batch_ids = [image_info.id for image_info in batch]
+            ann_infos = api.annotation.download_batch(dataset.id, batch_ids)
             anns = []
             sly.logger.info(f"Preparing to convert {len(ann_infos)} annotations...")
             for ann_info, img_info in zip(ann_infos, batch):
@@ -109,6 +126,36 @@ def export_to_coco(api: sly.Api) -> None:
                 include_captions,
                 RECTANGLE_MARK,
             )
+
+        # for batch in sly.batched(images):
+        #     image_ids = [image_info.id for image_info in batch]
+        #     sly.logger.info(f"Working with batch of {len(batch)} images with ids: {image_ids}")
+
+        #     if selected_output == "images":
+        #         image_paths = [os.path.join(img_dir, image_info.name) for image_info in batch]
+        #         f.download_batch_with_retry(api, dataset.id, image_ids, image_paths)
+
+        #     ann_infos = api.annotation.download_batch(dataset.id, image_ids)
+        #     anns = []
+        #     sly.logger.info(f"Preparing to convert {len(ann_infos)} annotations...")
+        #     for ann_info, img_info in zip(ann_infos, batch):
+        #         ann = convert_geometry.convert_annotation(
+        #             ann_info, img_info, project_meta, meta, RECTANGLE_MARK
+        #         )
+        #         anns.append(ann)
+        #     sly.logger.info(f"{len(anns)} annotations converted...")
+        #     coco_instances, label_id, coco_captions, caption_id = f.create_coco_annotation(
+        #         categories_mapping,
+        #         batch,
+        #         anns,
+        #         label_id,
+        #         coco_instances,
+        #         caption_id,
+        #         coco_captions,
+        #         ds_progress,
+        #         include_captions,
+        #         RECTANGLE_MARK,
+        #     )
         with open(os.path.join(ann_dir, "instances.json"), "w") as file:
             json.dump(coco_instances, file)
         if coco_captions is not None and include_captions: