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detection/image_demo.py

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+# Copyright (c) OpenMMLab. All rights reserved.
+import asyncio
+from argparse import ArgumentParser
+
+from mmdet.apis import (async_inference_detector, inference_detector,
+                        init_detector, show_result_pyplot)
+import mmcv
+import mmcv_custom  # noqa: F401,F403
+import mmdet_custom  # noqa: F401,F403
+import os.path as osp
+
+
+def parse_args():
+    parser = ArgumentParser()
+    parser.add_argument('img', help='Image file')
+    parser.add_argument('config', help='Config file')
+    parser.add_argument('checkpoint', help='Checkpoint 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='coco',
+        choices=['coco', 'voc', 'citys', 'random'],
+        help='Color palette used for visualization')
+    parser.add_argument(
+        '--score-thr', type=float, default=0.3, help='bbox score threshold')
+    parser.add_argument(
+        '--async-test',
+        action='store_true',
+        help='whether to set async options for async inference.')
+    args = parser.parse_args()
+    return args
+
+
+def main(args):
+    # build the model from a config file and a checkpoint file
+    model = init_detector(args.config, args.checkpoint, device=args.device)
+    # test a single image
+    result = inference_detector(model, args.img)
+    
+    mmcv.mkdir_or_exist(args.out)
+    out_file = osp.join(args.out, osp.basename(args.img))
+    # show the results
+    model.show_result(
+        args.img,
+        result,
+        score_thr=args.score_thr,
+        show=False,
+        bbox_color=args.palette,
+        text_color=(200, 200, 200),
+        mask_color=args.palette,
+        out_file=out_file
+    )
+    print(f"Result is save at {out_file}")
+
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    main(args)