single image inference

segmentation/image_demo.py

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+# Copyright (c) OpenMMLab. All rights reserved.
+from argparse import ArgumentParser
+
+import mmcv
+
+import mmcv_custom   # noqa: F401,F403
+import mmseg_custom   # noqa: F401,F403
+from mmseg.apis import inference_segmentor, init_segmentor, show_result_pyplot
+from mmseg.core.evaluation import get_palette
+from mmcv.runner import load_checkpoint
+from mmseg.core import get_classes
+import cv2
+import os.path as osp
+
+
+def main():
+    parser = ArgumentParser()
+    parser.add_argument('config', help='Config file')
+    parser.add_argument('checkpoint', help='Checkpoint file')
+    parser.add_argument('img', help='Image file')
+    parser.add_argument('--out', type=str, default="demo", help='out dir')
+    parser.add_argument(
+        '--device', default='cuda:0', help='Device used for inference')
+    parser.add_argument(
+        '--palette',
+        default='cityscapes',
+        help='Color palette used for segmentation map')
+    parser.add_argument(
+        '--opacity',
+        type=float,
+        default=0.5,
+        help='Opacity of painted segmentation map. In (0, 1] range.')
+    args = parser.parse_args()
+
+    # build the model from a config file and a checkpoint file
+
+    model = init_segmentor(args.config, checkpoint=None, device=args.device)
+    checkpoint = load_checkpoint(model, args.checkpoint, map_location='cpu')
+    if 'CLASSES' in checkpoint.get('meta', {}):
+        model.CLASSES = checkpoint['meta']['CLASSES']
+    else:
+        model.CLASSES = get_classes(args.palette)
+
+    # test a single image
+    result = inference_segmentor(model, args.img)
+    # show the results
+    if hasattr(model, 'module'):
+        model = model.module
+    img = model.show_result(args.img, result,
+                            palette=get_palette(args.palette),
+                            show=False, opacity=args.opacity)
+    mmcv.mkdir_or_exist(args.out)
+    out_path = osp.join(args.out, osp.basename(args.img))
+    cv2.imwrite(out_path, img)
+    print(f"Result is save at {out_path}")
+
+if __name__ == '__main__':
+    main()