docs updated

Author: agyurjin

superannotate/input_converters/conversion.py

@@ -238,6 +238,7 @@ def import_annotation(
     Vector          object_detection
     Vector          instance_segmentation
     Vector          vector_annotation
+    Pixel           instance_segmentation
     ==============  ======================
 
     ==============  ======================

superannotate/input_converters/converters/sagemaker_converters/sagemaker_to_sa_vector.py

@@ -28,14 +28,21 @@ def sagemaker_object_detection_to_sa_vector(data_path, main_key, output_dir):
             manifest = dataset_manifest[int(img['datasetObjectId'])]
             file_name = '%s___objects.json' % Path(manifest['source-ref']).name
 
-            sa_metadata = {'name': Path(manifest['source-ref']).name}
-
             classes = img['consolidatedAnnotation']['content'][
                 main_key + '-metadata']['class-map']
             for key, value in classes.items():
                 if key not in classes_ids.keys():
                     classes_ids[key] = value
 
+            image_size = img['consolidatedAnnotation']['content'][main_key][
+                'image_size']
+
+            sa_metadata = {
+                'name': Path(manifest['source-ref']).name,
+                'width': image_size['width'],
+                'height': image_size['height']
+            }
+
             annotations = img['consolidatedAnnotation']['content'][main_key][
                 'annotations']
             sa_instances = []

superannotate/input_converters/export_from_sa_conversions.py

@@ -53,6 +53,8 @@ def _move_files(data_set, src):
         for tup in data_set:
             for i in tup:
                 shutil.copy(i, train_path / Path(i).name)
+    else:
+        logger.warning("Images doesn't exist")
 
 
 def _create_classes_mapper(imgs, classes_json):
@@ -70,9 +72,6 @@ def export_from_sa(args):
     :param args: All arguments that will be used during convertion.
     :type args: Namespace
     """
-    # if args.platform == "Desktop":
-    #     args.input_dir = _split_json(args.input_dir)
-
     data_set = None
 
     (args.output_dir / "image_set").mkdir(parents=True, exist_ok=True)