{"id":26491308,"url":"https://github.com/marrlab/instantdl","last_synced_at":"2025-03-20T08:28:08.051Z","repository":{"id":37637344,"uuid":"246520785","full_name":"marrlab/InstantDL","owner":"marrlab","description":"InstantDL: An easy and convenient deep learning pipeline for image segmentation and classification","archived":false,"fork":false,"pushed_at":"2023-03-24T22:25:51.000Z","size":132634,"stargazers_count":43,"open_issues_count":3,"forks_count":8,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-03-13T15:40:17.456Z","etag":null,"topics":["classification","deep-learning","docker","gpu","image-segmentation","instance-segmentation","pixel-wise-regression","regression","semantic-segmentation"],"latest_commit_sha":null,"homepage":"https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04037-3","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/marrlab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2020-03-11T08:53:40.000Z","updated_at":"2025-03-07T02:29:15.000Z","dependencies_parsed_at":"2023-01-21T12:45:16.046Z","dependency_job_id":null,"html_url":"https://github.com/marrlab/InstantDL","commit_stats":{"total_commits":309,"total_committers":7,"mean_commits":"44.142857142857146","dds":0.4271844660194175,"last_synced_commit":"320c52d02e8bebf07fde76affb4f598207b47cd1"},"previous_names":[],"tags_count":6,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/marrlab%2FInstantDL","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/marrlab%2FInstantDL/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/marrlab%2FInstantDL/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/marrlab%2FInstantDL/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/marrlab","download_url":"https://codeload.github.com/marrlab/InstantDL/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244577141,"owners_count":20475250,"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":["classification","deep-learning","docker","gpu","image-segmentation","instance-segmentation","pixel-wise-regression","regression","semantic-segmentation"],"created_at":"2025-03-20T08:28:07.131Z","updated_at":"2025-03-20T08:28:08.045Z","avatar_url":"https://github.com/marrlab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# InstandDL: An easy and convenient deep learning pipeline for image segmentation and classification\n\n[![Build Status](https://travis-ci.com/marrlab/InstantDL.svg?branch=develop-test)](https://travis-ci.com/marrlab/InstantDL)\n\nInstantDL enables experts and non-experts to use state-of-the art deep learning methods on biomedical image data. InstantDL offers the four most common tasks in medical image processing: Semantic segmentation, instance segmentation, pixel-wise regression and classification. For more in depth discussion on the methods, as well as comparing the results and bechmarks using this package, please refer to our preprint on bioRxiv [here](https://doi.org/10.1101/2020.06.22.164103)\n\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"docs/Instand_DL_farbig_RGB.png\"  width=\"400\" /\u003e\n\u003c/p\u003e\n\n---------------------------------------------------------------------\n\n## Documentation\n\nFor documentation please refere to [docs](docs)\n\nFor a short video introducing InstantDL please see:\n\n\u003ca href=\"https://www.youtube.com/watch?v=G9_lB0gDKu4\"\u003e\n\u003cp align=\"center\"\u003e\n\u003cimg href=\"InstantDL\" src=\"http://img.youtube.com/vi/Wy4wlEyE2fA/0.jpg\"\nwidth=\"500\" align=\"center\"\u003e\n\u003c/p\u003e\n\u003ca\u003e\n\n## Contributing\n\nWe are happy about any contributions. For any suggested changes, please send a pull request to the *develop* branch.\n\n## Citation\n\nIf you use InstantDL, please cite this paper:\n\n```\n@article {\nauthor = {Waibel, Dominik Jens Elias and Shetab Boushehri, Sayedali and Marr, Carsten},\ntitle = {InstantDL - An easy-to-use deep learning pipeline for image segmentation and classification},\nyear = {2021},\ndoi = {10.1186/s12859-021-04037-3},\nURL = {https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04037-3#article-info},\neprint = {https://doi.org/10.1186/s12859-021-04037-3},\njournal = {BMC Bioinformatics}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmarrlab%2Finstantdl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmarrlab%2Finstantdl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmarrlab%2Finstantdl/lists"}