fixed linter issues (#2305)

cvat/apps/engine/serializers.py

@@ -297,7 +297,7 @@ class TaskSerializer(WriteOnceMixin, serializers.ModelSerializer):
                     .format(db_label.name))
             if not label.get('color', None):
                 label_names = [l.name for l in
-                    models.Label.objects.filter(task_id=instance.id).exclude(id=db_label.id).order_by('id')
+                    instance.label_set.all().exclude(id=db_label.id).order_by('id')
                 ]
                 db_label.color = get_label_color(db_label.name, label_names)
             else:

serverless/openvino/dextr/nuclio/model_handler.py

@@ -9,7 +9,7 @@ from model_loader import ModelLoader
 
 class ModelHandler:
     def __init__(self):
-        base_dir = os.environ.get("MODEL_PATH", "/opt/nuclio")
+        base_dir = os.path.abspath(os.environ.get("MODEL_PATH", "/opt/nuclio"))
         model_xml = os.path.join(base_dir, "dextr.xml")
         model_bin = os.path.join(base_dir, "dextr.bin")
         self.model = ModelLoader(model_xml, model_bin)

serverless/openvino/omz/intel/person-reidentification-retail-300/nuclio/model_handler.py

@@ -12,8 +12,8 @@ from model_loader import ModelLoader
 
 class ModelHandler:
     def __init__(self):
-        base_dir = os.environ.get("MODEL_PATH",
-            "/opt/nuclio/open_model_zoo/intel/person-reidentification-retail-0300/FP32")
+        base_dir = os.path.abspath(os.environ.get("MODEL_PATH",
+            "/opt/nuclio/open_model_zoo/intel/person-reidentification-retail-0300/FP32"))
         model_xml = os.path.join(base_dir, "person-reidentification-retail-0300.xml")
         model_bin = os.path.join(base_dir, "person-reidentification-retail-0300.bin")
 

serverless/openvino/omz/intel/semantic-segmentation-adas-0001/nuclio/model_handler.py

@@ -10,8 +10,8 @@ from model_loader import ModelLoader
 
 class ModelHandler:
     def __init__(self, labels):
-        base_dir = os.environ.get("MODEL_PATH",
-            "/opt/nuclio/open_model_zoo/intel/semantic-segmentation-adas-0001/FP32")
+        base_dir = os.path.abspath(os.environ.get("MODEL_PATH",
+            "/opt/nuclio/open_model_zoo/intel/semantic-segmentation-adas-0001/FP32"))
         model_xml = os.path.join(base_dir, "semantic-segmentation-adas-0001.xml")
         model_bin = os.path.join(base_dir, "semantic-segmentation-adas-0001.bin")
         self.model = ModelLoader(model_xml, model_bin)

serverless/openvino/omz/intel/text-detection-0004/nuclio/model_handler.py

@@ -191,8 +191,8 @@ class PixelLinkDecoder():
 
 class ModelHandler:
     def __init__(self, labels):
-        base_dir = os.environ.get("MODEL_PATH",
-            "/opt/nuclio/open_model_zoo/intel/text-detection-0004/FP32")
+        base_dir = os.path.abspath(os.environ.get("MODEL_PATH",
+            "/opt/nuclio/open_model_zoo/intel/text-detection-0004/FP32"))
         model_xml = os.path.join(base_dir, "text-detection-0004.xml")
         model_bin = os.path.join(base_dir, "text-detection-0004.bin")
         self.model = ModelLoader(model_xml, model_bin)

serverless/openvino/omz/public/faster_rcnn_inception_v2_coco/nuclio/model_handler.py

@@ -7,8 +7,8 @@ from model_loader import ModelLoader
 
 class ModelHandler:
     def __init__(self, labels):
-        base_dir = os.environ.get("MODEL_PATH",
-            "/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/FP32")
+        base_dir = os.path.abspath(os.environ.get("MODEL_PATH",
+            "/opt/nuclio/open_model_zoo/public/faster_rcnn_inception_v2_coco/FP32"))
         model_xml = os.path.join(base_dir, "faster_rcnn_inception_v2_coco.xml")
         model_bin = os.path.join(base_dir, "faster_rcnn_inception_v2_coco.bin")
         self.model = ModelLoader(model_xml, model_bin)

serverless/openvino/omz/public/mask_rcnn_inception_resnet_v2_atrous_coco/nuclio/model_handler.py

@@ -32,8 +32,8 @@ def segm_postprocess(box: list, raw_cls_mask, im_h, im_w):
 
 class ModelHandler:
     def __init__(self, labels):
-        base_dir = os.environ.get("MODEL_PATH",
-            "/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/FP32")
+        base_dir = os.path.abspath(os.environ.get("MODEL_PATH",
+            "/opt/nuclio/open_model_zoo/public/mask_rcnn_inception_resnet_v2_atrous_coco/FP32"))
         model_xml = os.path.join(base_dir, "mask_rcnn_inception_resnet_v2_atrous_coco.xml")
         model_bin = os.path.join(base_dir, "mask_rcnn_inception_resnet_v2_atrous_coco.bin")
         self.model = ModelLoader(model_xml, model_bin)

serverless/openvino/omz/public/yolo-v3-tf/nuclio/model_handler.py

@@ -112,8 +112,8 @@ def intersection_over_union(box_1, box_2):
 
 class ModelHandler:
     def __init__(self, labels):
-        base_dir = os.environ.get("MODEL_PATH",
-            "/opt/nuclio/open_model_zoo/public/yolo-v3-tf/FP32")
+        base_dir = os.path.abspath(os.environ.get("MODEL_PATH",
+            "/opt/nuclio/open_model_zoo/public/yolo-v3-tf/FP32"))
         model_xml = os.path.join(base_dir, "yolo-v3-tf.xml")
         model_bin = os.path.join(base_dir, "yolo-v3-tf.bin")
         self.model = ModelLoader(model_xml, model_bin)

serverless/pytorch/foolwood/siammask/nuclio/model_handler.py

@@ -14,8 +14,8 @@ class ModelHandler:
         self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
         torch.backends.cudnn.benchmark = True
 
-        base_dir = os.environ.get("MODEL_PATH",
-            "/opt/nuclio/SiamMask/experiments/siammask_sharp")
+        base_dir = os.path.abspath(os.environ.get("MODEL_PATH",
+            "/opt/nuclio/SiamMask/experiments/siammask_sharp"))
         class configPath:
             config = os.path.join(base_dir, "config_davis.json")
 

serverless/pytorch/saic-vul/fbrs/nuclio/model_handler.py

@@ -36,7 +36,7 @@ def convert_mask_to_polygon(mask):
 class ModelHandler:
     def __init__(self):
         torch.backends.cudnn.deterministic = True
-        base_dir = os.environ.get("MODEL_PATH", "/opt/nuclio/fbrs")
+        base_dir = os.path.abspath(os.environ.get("MODEL_PATH", "/opt/nuclio/fbrs"))
         model_path = os.path.join(base_dir, "resnet101_dh256_sbd.pth")
         state_dict = torch.load(model_path, map_location='cpu')
 

serverless/tensorflow/matterport/mask_rcnn/nuclio/model_loader.py

@@ -17,7 +17,7 @@ tf.compat.v1.disable_eager_execution()
 # The directory should contain a clone of
 # https://github.com/matterport/Mask_RCNN repository and
 # downloaded mask_rcnn_coco.h5 model.
-MASK_RCNN_DIR = os.environ.get('MASK_RCNN_DIR')
+MASK_RCNN_DIR = os.path.abspath(os.environ.get('MASK_RCNN_DIR'))
 if MASK_RCNN_DIR:
     sys.path.append(MASK_RCNN_DIR)  # To find local version of the library
     sys.path.append(os.path.join(MASK_RCNN_DIR, 'samples/coco'))