xrli-U / MuSc

This is an official PyTorch implementation for "MuSc : Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images" (MuSc ICLR2024).
MIT License
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btad和mvtec_anomaly_detection无法可视化 #3

Open zbtong6799 opened 3 months ago

zbtong6799 commented 3 months ago

visa可以直接可视化结果。可是剩余的两个数据集在结果文件夹只空的文件夹。请问是参数设置出现什么问题了吗?以下是我的参数设置。 parser = argparse.ArgumentParser(description='MuSc') parser.add_argument('--config', type=str, default='./configs/musc.yaml', help='config file path') parser.add_argument('--data_path', type=str, default="./data/mvtec_anomaly_detection/", help='dataset path') parser.add_argument('--dataset_name', type=str, default="mvtec_ad", help='dataset name') parser.add_argument('--class_name', type=str, default="ALL", help='category') parser.add_argument('--device', type=int, default=0, help='gpu id') parser.add_argument('--output_dir', type=str, default="./output/", help='save results path') parser.add_argument('--vis', type=str, default="true", help='visualization') parser.add_argument('--vis_type', type=str, default="single_norm", help='normalization type in visualization') parser.add_argument('--save_excel', type=str, default=None, help='save excel') parser.add_argument('--r_list', type=int, nargs="+", default=None, help='aggregation degrees of LNAMD') parser.add_argument('--feature_layers', type=int, nargs="+", default=None, help='feature layers') parser.add_argument('--backbone_name', type=str, default=None, help='backbone') parser.add_argument('--pretrained', type=str, default=None, help='pretrained datasets') parser.add_argument('--img_resize', type=int, default=224, help='image size') parser.add_argument('--batch_size', type=int, default=32, help='batch size') parser.add_argument('--divide_num', type=int, default=None, help='the number of divided subsets')

zbtong6799 commented 3 months ago

问题解决,要在ubuntu系统运行,微软系统无法保存可视化结果