Fix platform conversion

Author: hovnatan

superannotate/input_converters/converters/coco_converters/coco_strategies.py

@@ -1,17 +1,30 @@
-from datetime import datetime
-import os
 import glob
 import json
+import os
 from collections import namedtuple
-from tqdm import tqdm
-from PIL import Image
+from datetime import datetime
+
 from panopticapi.utils import IdGenerator, id2rgb
+from PIL import Image
+from tqdm import tqdm
 
 from .coco_converter import CoCoConverter
-from .sa_pixel_to_coco import sa_pixel_to_coco_instance_segmentation, sa_pixel_to_coco_panoptic_segmentation, sa_pixel_to_coco_object_detection
-from .sa_vector_to_coco import sa_vector_to_coco_instance_segmentation, sa_vector_to_coco_keypoint_detection, sa_vector_to_coco_object_detection
-from .coco_to_sa_pixel import coco_panoptic_segmentation_to_sa_pixel, coco_instance_segmentation_to_sa_pixel
-from .coco_to_sa_vector import coco_keypoint_detection_to_sa_vector, coco_instance_segmentation_to_sa_vector
+from .coco_to_sa_pixel import (
+    coco_instance_segmentation_to_sa_pixel,
+    coco_panoptic_segmentation_to_sa_pixel
+)
+from .coco_to_sa_vector import (
+    coco_instance_segmentation_to_sa_vector,
+    coco_keypoint_detection_to_sa_vector
+)
+from .sa_pixel_to_coco import (
+    sa_pixel_to_coco_instance_segmentation, sa_pixel_to_coco_object_detection,
+    sa_pixel_to_coco_panoptic_segmentation
+)
+from .sa_vector_to_coco import (
+    sa_vector_to_coco_instance_segmentation,
+    sa_vector_to_coco_keypoint_detection, sa_vector_to_coco_object_detection
+)
 
 
 class CocoPanopticConverterStrategy(CoCoConverter):

superannotate/input_converters/export_from_sa_conversions.py

@@ -1,19 +1,21 @@
 """
-Module which will run converters and convert from 
+Module which will run converters and convert from
 superannotate annotation format to other annotation formats
 """
-import sys
-import os
+import copy
 import glob
-import shutil
 import json
 import logging
-import copy
-from argparse import Namespace
+import os
+import shutil
+import sys
+
 import numpy as np
 
 from .converters.converters import Converter
 
+from ..exceptions import SABaseException
+
 
 def _split_json(input_dir):
     temp_path = os.path.join(input_dir, "WebApp")
@@ -102,12 +104,7 @@ def export_from_sa(args):
 
     data_set = None
 
-    try:
-        os.makedirs(os.path.join(args.output_dir, 'train_set'))
-    except Exception as e:
-        log_msg = 'Could not make test and train set paths, check if they already exist'
-        logging.error(log_msg)
-        sys.exit()
+    os.makedirs(os.path.join(args.output_dir, 'train_set'))
 
     try:
         _create_classes_mapper(

superannotate/input_converters/sa_conversion.py

@@ -4,13 +4,15 @@
 import os
 import shutil
 import time
+from pathlib import Path
+
 import cv2
 import numpy as np
-
 from tqdm import tqdm
-from pathlib import Path
 
-from ..common import hex_to_rgb, rgb_to_hex, blue_color_generator
+from ..common import blue_color_generator, hex_to_rgb, rgb_to_hex
+
+logger = logging.getLogger("superannotate-python-sdk")
 
 
 def _merge_jsons(input_dir, output_dir):
@@ -53,12 +55,10 @@ def _merge_jsons(input_dir, output_dir):
 def _split_json(input_dir, output_dir):
     os.makedirs(output_dir)
     json_data = json.load(open(os.path.join(input_dir, "annotations.json")))
-    images = json_data.keys()
-    for img in images:
-        annotations = json_data[img]
+    for img, annotations in tqdm(json_data.items()):
         objects = []
         for annot in annotations:
-            objects.append(annot)
+            objects += annot
 
         with open(os.path.join(output_dir, img + "___objects.json"), "w") as fw:
             json.dump(objects, fw, indent=2)