Merge pull request #4 from supervisely-ecosystem/user-name-hotfix

annotations processing fix
supervisely-ecosystem · Aug 25, 2021 · e6e1617 · e6e1617
2 parents 2bcc963 + ab156fd
commit e6e1617
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Showing 3 changed files with 31 additions and 28 deletions.
diff --git a/debug.env b/debug.env
@@ -6,12 +6,12 @@ DEBUG_CACHE_DIR="/home/paul/Documents/Work/Applications/in progress/export-to-co
 
 LOG_LEVEL="debug"
 
-TASK_ID=8603
+TASK_ID=8637
 
 context.userId=7
 context.teamId=8
 context.workspaceId=58
-modal.state.slyProjectId=1797
+modal.state.slyProjectId=6672
 
 
 SERVER_ADDRESS="put your value here"

diff --git a/src/functions.py b/src/functions.py
@@ -24,6 +24,10 @@ def get_categories_from_meta(meta):
     return categories
 
 
+def get_project_contributors():
+    pass
+
+
 def coco_segmentation(segmentation):  # works only with external vertices for now
     segmentation = [coord for sublist in segmentation for coord in sublist]
     return segmentation
@@ -47,30 +51,29 @@ def create_coco_dataset(coco_dataset_dir):
     return img_dir, ann_dir
 
 
-def create_coco_annotation(meta, categories_mapping, dataset, user_name, image_infos, anns, label_id, progress):
-    coco_ann = dict(
-        info=dict(
-            description=dataset.description,
-            url="None",
-            version=str(1.0),
-            year=int(dataset.created_at[:4]),
-            contributor=user_name,
-            date_created=dataset.created_at,
-        ),
-        licenses=[dict(url="None", id=0, name="None")],
-        images=[
-            # license, url, file_name, height, width, date_captured, id
-        ],
-        #type="instances",
-        annotations=[
-            # segmentation, area, iscrowd, image_id, bbox, category_id, id
-        ],
-        categories=get_categories_from_meta(meta)  # supercategory, id, name
-    )
-    sdfsc = []
-    for image_info, ann in zip(image_infos, anns):
+def create_coco_annotation(meta, categories_mapping, dataset, user_name, image_infos, anns, label_id, coco_ann, progress):
+    if len(coco_ann) == 0:
+        coco_ann = dict(
+            info=dict(
+                description=dataset.description,
+                url="None",
+                version=str(1.0),
+                year=int(dataset.created_at[:4]),
+                contributor=user_name,
+                date_created=dataset.created_at,
+            ),
+            licenses=[dict(url="None", id=0, name="None")],
+            images=[
+                # license, url, file_name, height, width, date_captured, id
+            ],
+            #type="instances",
+            annotations=[
+                # segmentation, area, iscrowd, image_id, bbox, category_id, id
+            ],
+            categories=get_categories_from_meta(meta)  # supercategory, id, name
+        )
 
-        sdfsc.append(image_info.id)
+    for image_info, ann in zip(image_infos, anns):
         coco_ann["images"].append(dict(
             license="None",
             file_name=image_info.name,
@@ -98,7 +101,7 @@ def create_coco_annotation(meta, categories_mapping, dataset, user_name, image_i
                 category_id=categories_mapping[label.obj_class.name],   # The category id corresponds to a single category specified in the categories section
                 id=label_id,                                            # Each annotation also has an id (unique to all other annotations in the dataset)
             ))
-    progress.iters_done_report(len(image_infos))
+        progress.iter_done_report()
     return coco_ann
 
 

diff --git a/src/main.py b/src/main.py
@@ -19,7 +19,7 @@ def export_to_coco(api: sly.Api, task_id, context, state, app_logger):
         coco_ann = {}
         label_id = 0
         images = api.image.get_list(dataset.id)
-        ds_progress = sly.Progress('Converting dataset: {}'.format(dataset.name), total_cnt=len(images))
+        ds_progress = sly.Progress('Converting dataset: {}'.format(dataset.name), total_cnt=len(images), min_report_percent=5)
         for batch in sly.batched(images):
             image_ids = [image_info.id for image_info in batch]
             image_paths = [os.path.join(coco_dataset_dir, img_dir, image_info.name) for image_info in batch]
@@ -28,7 +28,7 @@ def export_to_coco(api: sly.Api, task_id, context, state, app_logger):
             ann_infos = api.annotation.download_batch(dataset.id, image_ids)
             anns = [sly.Annotation.from_json(x.annotation, g.meta) for x in ann_infos]
             anns = [convert_geometry.convert_annotation(ann, meta) for ann in anns]
-            coco_ann = f.create_coco_annotation(meta, categories_mapping, dataset, g.user_name, batch, anns, label_id, ds_progress)
+            coco_ann = f.create_coco_annotation(meta, categories_mapping, dataset, g.user_name, batch, anns, label_id, coco_ann, ds_progress)
         with open(os.path.join(ann_dir, f"instances.json"), 'w') as file:
             json.dump(coco_ann, file)