{"id":17981035,"url":"https://github.com/nvidia/clara-train-examples","last_synced_at":"2025-10-10T05:46:17.432Z","repository":{"id":58842930,"uuid":"311813416","full_name":"NVIDIA/clara-train-examples","owner":"NVIDIA","description":"Example notebooks demonstrating how to use Clara Train to build Medical Imaging Deep Learning models","archived":false,"fork":false,"pushed_at":"2024-04-22T23:55:36.000Z","size":12606,"stargazers_count":127,"open_issues_count":13,"forks_count":80,"subscribers_count":10,"default_branch":"master","last_synced_at":"2025-03-17T11:11:16.108Z","etag":null,"topics":["automl","clara-train","deep-learning","healthcare-imaging","medical-imaging-computing","medical-imaging-processing","python3","pytorch","tcia-dac"],"latest_commit_sha":null,"homepage":"","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/NVIDIA.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":"2020-11-10T23:50:24.000Z","updated_at":"2025-02-11T17:55:31.000Z","dependencies_parsed_at":"2024-10-29T18:35:10.560Z","dependency_job_id":null,"html_url":"https://github.com/NVIDIA/clara-train-examples","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/NVIDIA%2Fclara-train-examples","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/NVIDIA%2Fclara-train-examples/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/NVIDIA%2Fclara-train-examples/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/NVIDIA%2Fclara-train-examples/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/NVIDIA","download_url":"https://codeload.github.com/NVIDIA/clara-train-examples/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245755672,"owners_count":20667027,"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":["automl","clara-train","deep-learning","healthcare-imaging","medical-imaging-computing","medical-imaging-processing","python3","pytorch","tcia-dac"],"created_at":"2024-10-29T18:07:26.481Z","updated_at":"2025-10-10T05:46:12.364Z","avatar_url":"https://github.com/NVIDIA.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Clara Train Examples\n### Overview of Clara Train\n\nClara Train SDK is a domain optimized developer application framework that includes APIs for AI-Assisted Annotation, making any medical viewer AI capable and v4.1 enables a MONAI based training framework with pre-trained models to start AI development with techniques such as Transfer Learning, Federated Learning, and AutoML.\n\nClara Train has upgraded its underlying infrastructure from Tensorflow to MONAI. [MONAI](https://monai.io/) is an open-source, PyTorch-based framework that provides domain-optimized foundational capabilities for healthcare.\n\nThis repo contains Jupyter Notebooks to help you explore the features and capabilities of Clara Train, including AI-Assisted Annotation, AutoML, and Federated Learning.\n\n## How to navigate this repository\n#### PyTorch - Clara Train 4.1\nIf you're using Clara Train 4.1, you'll want to use the PyTorch folder structure.  You'll find the README.md and Welcome.ipynb files in the [PyTorch/Notebooks](PyTorch/NoteBooks) directory that will help you get started.\n\n#### Tensorflow-Deprecated - Clara Train 3.1\nIf you're still using Clara Train 3.1, we encourage you to upgrade to [Clara Train 4.1](https://ngc.nvidia.com/catalog/containers/nvidia:clara-train-sdk). You can find information on converting your current Clara 3.1 MMAR's to [Clara 4.0 compatible MMAR's on our docs](https://docs.nvidia.com/clara/clara-train-sdk/pt/appendix/migration_from_tf.html#migratefromtf).\n\nIf you're still interested in exploring Clara Train 3.1 using our old Jupyter Notebooks, you'll now find them under the Tensorflow-Deprecated folder.  You'll find all of the instructs in the README.me file. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnvidia%2Fclara-train-examples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnvidia%2Fclara-train-examples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnvidia%2Fclara-train-examples/lists"}