Update name of class and arg

Author: Dmitry Sidnev

demos/background_subtraction_demo/python/README.md

@@ -43,7 +43,7 @@ Based on this an instance segmentation model must be trained at least for person
 
 As input, the demo application accepts a path to a single image file, a video file or a numeric ID of a web camera specified with a command-line argument `-i`
 
-> **NOTE**: if you use image background matting models, `--bgr` argument should be specified. This is a background image that equal to a real background behind a person on an input frame and must have the same shape as an input image.
+> **NOTE**: if you use image background matting models, `--background` argument should be specified. This is a background image that equal to a real background behind a person on an input frame and must have the same shape as an input image.
 
 The demo workflow is the following:
 
@@ -92,7 +92,8 @@ usage: background_subtraction_demo.py [-h] -m MODEL
                                       [-d DEVICE] [-t PROB_THRESHOLD]
                                       [--resize_type {crop,standard,fit_to_window,fit_to_window_letterbox}]
                                       [--labels LABELS]
-                                      [--target_bgr TARGET_BGR] [--bgr BGR]
+                                      [--target_bgr TARGET_BGR]
+                                      [--background BACKGROUND]
                                       [--blur_bgr BLUR_BGR]
                                       [-nireq NUM_INFER_REQUESTS]
                                       [-nstreams NUM_STREAMS]
@@ -130,7 +131,8 @@ Options:
   --target_bgr TARGET_BGR
                         Optional. Background onto which to composite the
                         output (by default to green field).
-  --bgr BGR             Optional. Background image for background-matting
+  --background BACKGROUND
+                        Optional. Background image for background-matting
                         model.
   --blur_bgr BLUR_BGR   Optional. Background blur strength (by default with
                         value 0 is not applied).

demos/background_subtraction_demo/python/background_subtraction_demo.py

@@ -26,7 +26,7 @@
 
 sys.path.append(str(Path(__file__).resolve().parents[2] / 'common/python'))
 
-from openvino.model_zoo.model_api.models import MaskRCNNModel, OutputTransform, RESIZE_TYPES, YolactModel, BackgroundMattingWithBGR, VideoBackgroundMatting
+from openvino.model_zoo.model_api.models import MaskRCNNModel, OutputTransform, RESIZE_TYPES, YolactModel, BackgroundMattingWithBackground, VideoBackgroundMatting
 from openvino.model_zoo.model_api.models.utils import load_labels
 from openvino.model_zoo.model_api.performance_metrics import PerformanceMetrics
 from openvino.model_zoo.model_api.pipelines import get_user_config, AsyncPipeline
@@ -62,7 +62,7 @@ def build_argparser():
     args.add_argument('--labels', help='Optional. Labels mapping file.', default=None, type=str)
     args.add_argument('--target_bgr', default=None, type=str,
                       help='Optional. Background onto which to composite the output (by default to green field).')
-    args.add_argument('--bgr', default=None, type=str,
+    args.add_argument('--background', default=None, type=str,
                       help='Optional. Background image for background-matting model.')
     args.add_argument('--blur_bgr', default=0, type=int,
                       help='Optional. Background blur strength (by default with value 0 is not applied).')
@@ -113,15 +113,15 @@ def get_model(model_adapter, configuration, args):
         model = VideoBackgroundMatting(model_adapter, configuration)
         is_matting_model = True
     elif len(inputs) == 2 and len(outputs) in (2, 3) and 'bgr' in inputs.keys():
-        if args.bgr is None:
-            raise ValueError('The BackgroundMattingWithBGR model expects the specified "--bgr" option.')
-        model = BackgroundMattingWithBGR(model_adapter, configuration)
+        if args.background is None:
+            raise ValueError('The BackgroundMattingWithBackground model expects the specified "--background" option.')
+        model = BackgroundMattingWithBackground(model_adapter, configuration)
         need_bgr_input = True
         is_matting_model = True
     else:
         model = MaskRCNNModel(model_adapter, configuration)
-    if not need_bgr_input and args.bgr is not None:
-        log.warning('The \"--bgr\" option works only for BackgroundMattingWithBGR model. Option will be omitted.')
+    if not need_bgr_input and args.background is not None:
+        log.warning('The \"--background\" option works only for BackgroundMattingWithBackground model. Option will be omitted.')
 
     if args.raw_output_message and is_matting_model:
         log.warning('\'--raw_output_message\' argument is set but is used background-matting based model, nothing to show')
@@ -223,7 +223,7 @@ def main():
 
     model, need_bgr_input = get_model(model_adapter, configuration, args)
 
-    input_bgr = open_images_capture(args.bgr, False).read() if need_bgr_input else None
+    input_bgr = open_images_capture(args.background, False).read() if need_bgr_input else None
 
     person_id = -1
     for i, label in enumerate(labels):

demos/common/python/openvino/model_zoo/model_api/models/__init__.py

@@ -16,7 +16,7 @@
 
 
 from .bert import BertEmbedding, BertNamedEntityRecognition, BertQuestionAnswering
-from .background_matting import BackgroundMattingWithBGR, VideoBackgroundMatting
+from .background_matting import BackgroundMattingWithBackground, VideoBackgroundMatting
 from .centernet import CenterNet
 from .classification import Classification
 from .deblurring import Deblurring
@@ -38,7 +38,7 @@
 from .yolo import YOLO, YoloV3ONNX, YoloV4, YOLOF, YOLOX
 
 __all__ = [
-    'BackgroundMattingWithBGR',
+    'BackgroundMattingWithBackground',
     'BertEmbedding',
     'BertNamedEntityRecognition',
     'BertQuestionAnswering',

demos/common/python/openvino/model_zoo/model_api/models/background_matting.py

@@ -89,7 +89,7 @@ def initialize_rec(self):
         return rec
 
 
-class BackgroundMattingWithBGR(ImageModel):
+class BackgroundMattingWithBackground(ImageModel):
     __model__ = 'Background-matting'
 
     def __init__(self, model_adapter, configuration, preload=False):