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from mmseg.apis import inference_model, init_model, show_result_pyplot import mmcv config_file = 'pspnet_r50-d8_4xb2-40k_cityscapes-512x1024.py' checkpoint_file = 'pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth' # build the model from a config file and a checkpoint file model = init_model(config_file, checkpoint_file, device='cuda:0') # test a single image and show the results img = 'demo/demo.png' # or img = mmcv.imread(img), which will only load it once result = inference_model(model, img) # visualize the results in a new window show_result_pyplot(model, img, result, show=True) # or save the visualization results to image files # you can change the opacity of the painted segmentation map in (0, 1]. show_result_pyplot(model, img, result, show=True, out_file='result.jpg', opacity=0.5) # test a video and show the results video = mmcv.VideoReader('video.mp4') for frame in video: result = inference_model(model, frame) show_result_pyplot(model, frame, result, wait_time=1)
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