{"id":18276230,"url":"https://github.com/hilab-git/iplc","last_synced_at":"2025-04-05T03:31:22.926Z","repository":{"id":247036803,"uuid":"822985646","full_name":"HiLab-git/IPLC","owner":"HiLab-git","description":null,"archived":false,"fork":false,"pushed_at":"2025-01-03T13:59:58.000Z","size":1400,"stargazers_count":5,"open_issues_count":3,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-20T21:38:01.670Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/HiLab-git.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-07-02T08:00:19.000Z","updated_at":"2025-02-08T12:46:32.000Z","dependencies_parsed_at":"2024-07-06T08:22:47.397Z","dependency_job_id":"0f475417-5930-4a7b-880a-8161021fe018","html_url":"https://github.com/HiLab-git/IPLC","commit_stats":null,"previous_names":["hilab-git/iplc"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HiLab-git%2FIPLC","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HiLab-git%2FIPLC/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HiLab-git%2FIPLC/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HiLab-git%2FIPLC/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/HiLab-git","download_url":"https://codeload.github.com/HiLab-git/IPLC/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247284911,"owners_count":20913691,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-05T12:15:28.435Z","updated_at":"2025-04-05T03:31:17.896Z","avatar_url":"https://github.com/HiLab-git.png","language":"Python","readme":"## IPLC\r\n\r\n\r\n## 👉 Requirements\r\nNon-exhaustive list:\r\n* python3.9+\r\n* Pytorch 1.10.1\r\n* nibabel\r\n* Scipy\r\n* NumPy\r\n* Scikit-image\r\n* yaml\r\n* tqdm\r\n* pandas\r\n* scikit-image\r\n* SimpleITK\r\n\r\n\r\n## 👉 Usage\r\n1. Download the [M\u0026MS Dataset](http://www.ub.edu/mnms), and organize the dataset directory structure as follows:\r\n```\r\nyour/data_root/\r\n       train/\r\n            img/\r\n                A/\r\n                    A0S9V9_0.nii.gz\r\n                    ...\r\n                B/\r\n                C/\r\n                ...\r\n            lab/\r\n                A/\r\n                    A0S9V9_0_gt.nii.gz\r\n                    ...\r\n                B/\r\n                C/\r\n                ...\r\n       valid/\r\n            img/\r\n            lab/\r\n       test/\r\n           img/\r\n           lab/\r\n```\r\nThe network takes nii files as an input. The gt folder contains gray-scale images of the ground-truth, where the gray-scale level is the number of the class (0,1,...K).\r\n\r\n2. Download the [SAM-Med2D model](https://drive.google.com/file/d/1ARiB5RkSsWmAB_8mqWnwDF8ZKTtFwsjl/view?usp=drive_link) and move the model to the \"your_root/pretrain_model\" directory in your project.\r\n\r\n3. Train the source model in the source domain, for instance, you can train the source model using domain A on the M\u0026MS dataset:\r\n\r\n```\r\npython train_source.py --config \"./config/train2d_source.cfg\"\r\n```\r\n\r\n4. Adapt the source model to the target domain, for instance, you can adapt the source model to domain B on the M\u0026MS dataset:\r\n\r\n```\r\npython adapt_mian.py --config \"./config/adapt.cfg\"\r\n```\r\n\r\n## 🤝 Acknowledgement\r\n- Thanks to the open-source of the following projects: [Segment Anything](https://github.com/facebookresearch/segment-anything); [SAM-Med2D](https://github.com/cv-chaitali/SAM-Med2D)\r\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhilab-git%2Fiplc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhilab-git%2Fiplc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhilab-git%2Fiplc/lists"}