[Enhancement]Add out_file in add_datasample to directly save image

mmseg/apis/inference.py

@@ -199,9 +199,8 @@ def show_result_pyplot(model: BaseSegmentor,
         draw_gt=draw_gt,
         draw_pred=draw_pred,
         wait_time=wait_time,
+        out_file=out_file,
         show=show)
     vis_img = visualizer.get_image()
-    if out_file is not None:
-        mmcv.imwrite(vis_img, out_file)
 
     return vis_img

mmseg/visualization/local_visualizer.py

@@ -1,6 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from typing import Dict, List, Optional, Tuple
 
+import mmcv
 import numpy as np
 from mmengine.dist import master_only
 from mmengine.structures import PixelData
@@ -99,22 +100,28 @@ def _draw_sem_seg(self, image: np.ndarray, sem_seg: PixelData,
         return self.get_image()
 
     @master_only
-    def add_datasample(self,
-                       name: str,
-                       image: np.ndarray,
-                       data_sample: Optional[SegDataSample] = None,
-                       draw_gt: bool = True,
-                       draw_pred: bool = True,
-                       show: bool = False,
-                       wait_time: float = 0,
-                       step: int = 0) -> None:
+    def add_datasample(
+            self,
+            name: str,
+            image: np.ndarray,
+            data_sample: Optional[SegDataSample] = None,
+            draw_gt: bool = True,
+            draw_pred: bool = True,
+            show: bool = False,
+            wait_time: float = 0,
+            # TODO: Supported in mmengine's Viusalizer.
+            out_file: Optional[str] = None,
+            step: int = 0) -> None:
         """Draw datasample and save to all backends.
 
         - If GT and prediction are plotted at the same time, they are
         displayed in a stitched image where the left image is the
         ground truth and the right image is the prediction.
         - If ``show`` is True, all storage backends are ignored, and
         the images will be displayed in a local window.
+        - If ``out_file`` is specified, the drawn image will be
+        saved to ``out_file``. it is usually used when the display
+        is not available.
 
         Args:
             name (str): The image identifier.
@@ -128,6 +135,7 @@ def add_datasample(self,
                 Defaults to True.
             show (bool): Whether to display the drawn image. Default to False.
             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.
         """
         classes = self.dataset_meta.get('classes', None)
@@ -166,5 +174,8 @@ def add_datasample(self,
 
         if show:
             self.show(drawn_img, win_name=name, wait_time=wait_time)
+
+        if out_file is not None:
+            mmcv.imwrite(drawn_img, out_file)
         else:
             self.add_image(name, drawn_img, step)

tests/test_visualization/test_local_visualizer.py

@@ -118,19 +118,14 @@ def test_cityscapes_add_datasample_forward(gt_sem_seg):
                              [255, 0, 0], [0, 0, 142], [0, 0, 70],
                              [0, 60, 100], [0, 80, 100], [0, 0, 230],
                              [119, 11, 32]])
-                seg_local_visualizer.add_datasample(out_file, image,
-                                                    data_sample)
-
                 # test out_file
-                seg_local_visualizer.add_datasample(out_file, image,
-                                                    data_sample)
-                assert os.path.exists(
-                    osp.join(tmp_dir, 'vis_data', 'vis_image',
-                             out_file + '_0.png'))
-                drawn_img = cv2.imread(
-                    osp.join(tmp_dir, 'vis_data', 'vis_image',
-                             out_file + '_0.png'))
-                assert drawn_img.shape == (h, w, 3)
+                seg_local_visualizer.add_datasample(
+                    out_file,
+                    image,
+                    data_sample,
+                    out_file=osp.join(tmp_dir, 'test.png'))
+                self._assert_image_and_shape(
+                    osp.join(tmp_dir, 'test.png'), (h, w, 3))
 
                 # test gt_instances and pred_instances
                 pred_sem_seg_data = dict(
@@ -139,12 +134,13 @@ def test_cityscapes_add_datasample_forward(gt_sem_seg):
 
                 data_sample.pred_sem_seg = pred_sem_seg
 
+                # test draw prediction with gt
                 seg_local_visualizer.add_datasample(out_file, image,
                                                     data_sample)
                 self._assert_image_and_shape(
                     osp.join(tmp_dir, 'vis_data', 'vis_image',
                              out_file + '_0.png'), (h, w * 2, 3))
-
+                # test draw prediction without gt
                 seg_local_visualizer.add_datasample(
                     out_file, image, data_sample, draw_gt=False)
                 self._assert_image_and_shape(