[Feature] add -with-labels arg to inferencer for visualization without labels

demo/image_demo.py

@@ -19,6 +19,11 @@ def main():
         type=float,
         default=0.5,
         help='Opacity of painted segmentation map. In (0, 1] range.')
+    parser.add_argument(
+        '--with-labels',
+        action='store_true',
+        default=False,
+        help='Whether to display the class labels.')
     parser.add_argument(
         '--title', default='result', help='The image identifier.')
     args = parser.parse_args()
@@ -36,6 +41,7 @@ def main():
         result,
         title=args.title,
         opacity=args.opacity,
+        with_labels=args.with_labels,
         draw_gt=False,
         show=False if args.out_file is not None else True,
         out_file=args.out_file)

demo/image_demo_with_inferencer.py

@@ -27,6 +27,11 @@ def main():
         type=float,
         default=0.5,
         help='Opacity of painted segmentation map. In (0, 1] range.')
+    parser.add_argument(
+        '--with-labels',
+        action='store_true',
+        default=False,
+        help='Whether to display the class labels.')
     args = parser.parse_args()
 
     # build the model from a config file and a checkpoint file
@@ -38,7 +43,11 @@ def main():
 
     # test a single image
     mmseg_inferencer(
-        args.img, show=args.show, out_dir=args.out_dir, opacity=args.opacity)
+        args.img,
+        show=args.show,
+        out_dir=args.out_dir,
+        opacity=args.opacity,
+        with_labels=args.with_labels)
 
 
 if __name__ == '__main__':

mmseg/apis/inference.py

@@ -127,7 +127,7 @@ def show_result_pyplot(model: BaseSegmentor,
                        draw_pred: bool = True,
                        wait_time: float = 0,
                        show: bool = True,
-                       withLabels: Optional[bool] = True,
+                       with_labels: Optional[bool] = True,
                        save_dir=None,
                        out_file=None):
     """Visualize the segmentation results on the image.
@@ -147,7 +147,7 @@ def show_result_pyplot(model: BaseSegmentor,
             that means "forever". Defaults to 0.
         show (bool): Whether to display the drawn image.
             Default to True.
-        withLabels(bool, optional): Add semantic labels in visualization
+        with_labels(bool, optional): Add semantic labels in visualization
             result, Default to True.
         save_dir (str, optional): Save file dir for all storage backends.
             If it is None, the backend storage will not save any data.
@@ -183,7 +183,7 @@ def show_result_pyplot(model: BaseSegmentor,
         wait_time=wait_time,
         out_file=out_file,
         show=show,
-        withLabels=withLabels)
+        with_labels=with_labels)
     vis_img = visualizer.get_image()
 
     return vis_img

mmseg/apis/mmseg_inferencer.py

@@ -60,7 +60,8 @@ class MMSegInferencer(BaseInferencer):
     preprocess_kwargs: set = set()
     forward_kwargs: set = {'mode', 'out_dir'}
     visualize_kwargs: set = {
-        'show', 'wait_time', 'img_out_dir', 'opacity', 'return_vis'
+        'show', 'wait_time', 'img_out_dir', 'opacity', 'return_vis',
+        'with_labels'
     }
     postprocess_kwargs: set = {'pred_out_dir', 'return_datasample'}
 
@@ -201,7 +202,8 @@ def visualize(self,
                   show: bool = False,
                   wait_time: int = 0,
                   img_out_dir: str = '',
-                  opacity: float = 0.8) -> List[np.ndarray]:
+                  opacity: float = 0.8,
+                  with_labels: Optional[bool] = True) -> List[np.ndarray]:
         """Visualize predictions.
 
         Args:
@@ -254,7 +256,8 @@ def visualize(self,
                 wait_time=wait_time,
                 draw_gt=False,
                 draw_pred=True,
-                out_file=out_file)
+                out_file=out_file,
+                with_labels=with_labels)
             if return_vis:
                 results.append(self.visualizer.get_image())
             self.num_visualized_imgs += 1

mmseg/visualization/local_visualizer.py

@@ -103,7 +103,7 @@ def _draw_sem_seg(self,
                       sem_seg: PixelData,
                       classes: Optional[List],
                       palette: Optional[List],
-                      withLabels: Optional[bool] = True) -> np.ndarray:
+                      with_labels: Optional[bool] = True) -> np.ndarray:
         """Draw semantic seg of GT or prediction.
 
         Args:
@@ -119,7 +119,7 @@ def _draw_sem_seg(self,
             palette (list, optional): Input palette for result rendering, which
                 is a list of color palette responding to the classes.
                 Defaults to None.
-            withLabels(bool, optional): Add semantic labels in visualization
+            with_labels(bool, optional): Add semantic labels in visualization
                 result, Default to True.
 
         Returns:
@@ -139,7 +139,7 @@ def _draw_sem_seg(self,
         for label, color in zip(labels, colors):
             mask[sem_seg[0] == label, :] = color
 
-        if withLabels:
+        if with_labels:
             font = cv2.FONT_HERSHEY_SIMPLEX
             # (0,1] to change the size of the text relative to the image
             scale = 0.05
@@ -265,7 +265,7 @@ def add_datasample(
             # TODO: Supported in mmengine's Viusalizer.
             out_file: Optional[str] = None,
             step: int = 0,
-            withLabels: Optional[bool] = True) -> None:
+            with_labels: Optional[bool] = True) -> None:
         """Draw datasample and save to all backends.
 
         - If GT and prediction are plotted at the same time, they are
@@ -291,7 +291,7 @@ def add_datasample(
             wait_time (float): The interval of show (s). Defaults to 0.
             out_file (str): Path to output file. Defaults to None.
             step (int): Global step value to record. Defaults to 0.
-            withLabels(bool, optional): Add semantic labels in visualization
+            with_labels(bool, optional): Add semantic labels in visualization
                 result, Defaults to True.
         """
         classes = self.dataset_meta.get('classes', None)
@@ -307,7 +307,7 @@ def add_datasample(
                                             'visualizing semantic ' \
                                             'segmentation results.'
                 gt_img_data = self._draw_sem_seg(image, data_sample.gt_sem_seg,
-                                                 classes, palette, withLabels)
+                                                 classes, palette, with_labels)
 
             if 'gt_depth_map' in data_sample:
                 gt_img_data = gt_img_data if gt_img_data is not None else image
@@ -325,7 +325,7 @@ def add_datasample(
                 pred_img_data = self._draw_sem_seg(image,
                                                    data_sample.pred_sem_seg,
                                                    classes, palette,
-                                                   withLabels)
+                                                   with_labels)
 
             if 'pred_depth_map' in data_sample:
                 pred_img_data = pred_img_data if pred_img_data is not None \