由于我的实验都是基于MMSeg再autodl云平台做的,训练好模型后使用demo/image_demo_with_inference.py获得的推理图会带有标签,如下 解决办法 MMSeg版本为1.2.1 使用demo/image_demo.py推理,将show_result_pyplot的show参数设为false,这是因为云服务器场景不能像windows那样跳出一个框展示推理图 把show_result_pyplot的...
print('图像个数', len(os.listdir(PATH_IMAGE))) print('标注个数', len(os.listdir(PATH_MASKS))) 查看单张图像及其语义分割标注 指定图像文件名 file_name = 'SAS_21883_001_10.png' img_path = os.path.join(PATH_IMAGE, file_name) mask_path = os.path.join(PATH_MASKS, file_name) p...
'DATASETS','build_dataset','PIPELINES','CityscapesDataset','PascalVOCDataset','ADE20KDataset','PascalContextDataset','PascalContextDataset59','ChaseDB1Dataset','DRIVEDataset','HRFDataset','STAREDataset','DarkZurichDataset','NightDrivingDataset','COCOStuffDataset','LoveDADataset','MultiImageMixDataset...
python demo/image_demo.py \ data/street_uk.jpeg \ configs/mask2former/mask2former_swin-l-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024.py \ https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-l-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024/mask2former_sw...
python demo/image_demo.py demo/demo.png \\ configs/pspnet/pspnet_r50-d8_4xb2-40k_cityscapes-512x1024.py \\ pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth \\--device cuda:0--out-file result.jpg MMSegmentation 的文件结构 ...
python demo/image_demo.py demo/demo.png pspnet_r50-d8_512x1024_40k_cityscapes.py pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth --device cpu --out-file result.jpg 1. 如果运行成功,会在当前文件夹中看到一张新的图片 ...
# test a single image img = 'demo/demo.png' result = inference_segmentor(model, img) # show the results show_result_pyplot(model, img, result, get_palette('cityscapes')) /content/mmsegmentation/mmseg/models/segmentors/base.py:265: UserWarning: show==False and out_file is not specified,...
python demo/image_demo.py demo/demo.png pspnet_r50-d8_512x1024_40k_cityscapes.py pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth --device cpu --out-file result.jpg 发现报错: ModuleNotFoundError:Nomodulenamed'mmcv' ...
不过,“semi-local”一词更合适。 当前online demo的实现基于原始NL-means的patch版本。 此版本基于一个简单的观察。 在计算欧几里得距离d(B(p),B(q))时,patch B(p)中的所有像素都具有相同的重要性,因此权重f(d(B(p),B(q)) 可以用来对patch B(p)中的所有像素进行去噪,而不仅限于p。
.circleci .dev_scripts .github configs demo docker docs en _static advanced_guides device migration notes user_guides .readthedocs.yaml Makefile api.rst conf.py get_started.md index.rst make.bat model_zoo.md modelzoo_statistics.md overview.md ...