[Fix] Fix visualizor (#3154)

## Motivation

**Current visualize result**


![rs-dev](https://github.com/open-mmlab/mmsegmentation/assets/15952744/147ea3f7-f632-457b-b257-031199320825)

**Fixed the visualization result**



![rs-fix](https://github.com/open-mmlab/mmsegmentation/assets/15952744/98a86025-5a1e-4c2b-83e0-653dd659ba79)


## Modification

remove mmengine `draw_binary_masks` api

demo/inference_demo.ipynb

@@ -21,7 +21,6 @@
    "outputs": [],
    "source": [
     "import torch\n",
-    "import mmcv\n",
     "import matplotlib.pyplot as plt\n",
     "from mmengine.model.utils import revert_sync_batchnorm\n",
     "from mmseg.apis import init_model, inference_model, show_result_pyplot"
@@ -48,7 +47,7 @@
    "outputs": [],
    "source": [
     "# build the model from a config file and a checkpoint file\n",
-    "model = init_model(config_file, checkpoint_file, device='cuda:0')"
+    "model = init_model(config_file, checkpoint_file, device='cpu')"
    ]
   },
   {
@@ -71,8 +70,8 @@
    "outputs": [],
    "source": [
     "# show the results\n",
-    "vis_result = show_result_pyplot(model, img, result)\n",
-    "plt.imshow(mmcv.bgr2rgb(vis_result))"
+    "vis_result = show_result_pyplot(model, img, result, show=False)\n",
+    "plt.imshow(vis_result)"
    ]
   },
   {
@@ -99,7 +98,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.10.11"
   },
   "pycharm": {
    "stem_cell": {

mmseg/apis/inference.py

@@ -187,7 +187,7 @@ def show_result_pyplot(model: BaseSegmentor,
     if hasattr(model, 'module'):
         model = model.module
     if isinstance(img, str):
-        image = mmcv.imread(img)
+        image = mmcv.imread(img, channel_order='rgb')
     else:
         image = img
     if save_dir is not None:

mmseg/visualization/local_visualizer.py

@@ -108,14 +108,14 @@ def _draw_sem_seg(self, image: np.ndarray, sem_seg: PixelData,
 
         colors = [palette[label] for label in labels]
 
-        self.set_image(image)
-
-        # draw semantic masks
+        mask = np.zeros_like(image, dtype=np.uint8)
         for label, color in zip(labels, colors):
-            self.draw_binary_masks(
-                sem_seg == label, colors=[color], alphas=self.alpha)
+            mask[sem_seg[0] == label, :] = color
 
-        return self.get_image()
+        color_seg = (image * (1 - self.alpha) + mask * self.alpha).astype(
+            np.uint8)
+        self.set_image(color_seg)
+        return color_seg
 
     def set_dataset_meta(self,
                          classes: Optional[List] = None,
@@ -226,6 +226,6 @@ def add_datasample(
             self.show(drawn_img, win_name=name, wait_time=wait_time)
 
         if out_file is not None:
-            mmcv.imwrite(mmcv.bgr2rgb(drawn_img), out_file)
+            mmcv.imwrite(mmcv.rgb2bgr(drawn_img), out_file)
         else:
             self.add_image(name, drawn_img, step)