{"id":20874450,"url":"https://github.com/imagingdatacommons/idc-sm-annotations-conversion","last_synced_at":"2025-10-13T09:15:54.255Z","repository":{"id":175008164,"uuid":"653172050","full_name":"ImagingDataCommons/idc-sm-annotations-conversion","owner":"ImagingDataCommons","description":null,"archived":false,"fork":false,"pushed_at":"2025-03-01T22:22:32.000Z","size":474,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":6,"default_branch":"main","last_synced_at":"2025-03-01T23:22:55.433Z","etag":null,"topics":["conversion","dicom","pathomics"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ImagingDataCommons.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2023-06-13T14:33:19.000Z","updated_at":"2025-02-20T14:27:22.000Z","dependencies_parsed_at":"2023-12-14T15:27:24.489Z","dependency_job_id":"ab2c75f8-725c-4b65-bbd0-4eebcd77a4fc","html_url":"https://github.com/ImagingDataCommons/idc-sm-annotations-conversion","commit_stats":null,"previous_names":["imagingdatacommons/idc-pan-cancer-annotations-conversion","imagingdatacommons/idc-sm-annotations-conversion"],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ImagingDataCommons%2Fidc-sm-annotations-conversion","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ImagingDataCommons%2Fidc-sm-annotations-conversion/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ImagingDataCommons%2Fidc-sm-annotations-conversion/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ImagingDataCommons%2Fidc-sm-annotations-conversion/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ImagingDataCommons","download_url":"https://codeload.github.com/ImagingDataCommons/idc-sm-annotations-conversion/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243248251,"owners_count":20260752,"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":["conversion","dicom","pathomics"],"created_at":"2024-11-18T06:32:39.289Z","updated_at":"2025-10-13T09:15:49.235Z","avatar_url":"https://github.com/ImagingDataCommons.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# IDC Annotation Conversion\n\nPython project for converting various pathology annotations into DICOM\nformat for ingestion into the Imaging Data Commons.\n\nThe code in this repository is currently under development.\n\n### Installation\n\nThis repository is structured to be directly installable as a Python\ndistribution named `idc-annotation-conversion` via pip. You should be able to\nrun this command from the root of the cloned repository to install the packages\nalong with all its dependencies (defined in `pyproject.toml`) in your current\nPython environment:\n\n```bash\npip install .\n```\nAlternatively, you can install the package directly from remote with:\n\n```bash\npip install https://github.com/ImagingDataCommons/idc-sm-annotations-conversion.git\n```\n\n### Cloud Authentication\n\nYou need to authenticate to the relevant Google cloud buckets to run the code\nin this package. Specifically, access to the following resources is required:\n\n- Project `idc-etl-processing`\n- Bucket `public-datasets-idc`, the public bucket containing DICOM-format whole\n  slide images.\n- Bucket `idc-annotation-conversion-outputs`, or any other bucket specified\n  as the output bucket, if any.\n\nDepending on the conversion process that you are running, you may also need\naccess to:\n\n- Bucket `tcia-nuclei-seg`, which contains the original (CSV format)\n  segmentations for the `pan_cancer_nuclei_seg` conversion process.\n- Project `idc-external-031` and bucket `rms_annotation_test_oct_2023`, which contains the\n  original (XML format) annotations for the `rms` conversion process.\n\nIf you are using an IDC cloud VM, this should be handled\nautomatically for you. Otherwise, you should run:\n\n```\ngcloud auth application-default login --billing-project idc-etl-processing\n```\n\nand then once you are finished:\n\n```\ngcloud auth application-default revoke\n```\n\n### Use\n\nEach conversion process is implemented as a submodule of the `idc_annotation_conversion`\nmodule, which is installed when you installed this package. Each submodule has an\nan entrypoint (a `__main__.py` file), meaning that to run the process once this\npackage is installed you run:\n\n```bash\npython -m idc_annotation_conversion.\u003cmodule\u003e \u003cargs\u003e\n```\n\nSo for example to run the `pan_cancer_nuclei_seg` conversion process:\n\n```bash\npython -m idc_annotation_conversion.pan_cancer_nuclei_seg \u003cargs\u003e\n```\n\nIn each case, the default parameters should be sufficient to run a conversion processon\non the entire collection but there a number of optional arguments to control the process.\nYou can see the options by running `--help` when calling the submodule. E.g.:\n\n```bash\npython -m idc_annotation_conversion.pan_cancer_nuclei_seg --help\n```\n\n### Modules\n\nThe following modules are currently available:\n\n- `pan_cancer_nuclei_seg`: Conversion of Pan Cancer Nuclei segmentations from\n  XML to ANN and SEGs for various TCGA collections.\n- `rms`: Conversion of annotations related to the \"RMS-Mutation-Prediction\"\n  collection. Specifically conversion of hand annotated regions to SR, and\n  ML generated segmentations to SEG.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fimagingdatacommons%2Fidc-sm-annotations-conversion","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fimagingdatacommons%2Fidc-sm-annotations-conversion","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fimagingdatacommons%2Fidc-sm-annotations-conversion/lists"}