{"id":25982543,"url":"https://github.com/aastopher/potato_gan","last_synced_at":"2026-04-16T17:35:23.967Z","repository":{"id":151009384,"uuid":"543294009","full_name":"aastopher/Potato_GAN","owner":"aastopher","description":"Potato Generating DCGAN - a deep dive into GAN basics","archived":false,"fork":false,"pushed_at":"2022-10-26T18:12:01.000Z","size":113435,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-07-19T20:27:58.619Z","etag":null,"topics":["deep-learning","gan","gans","generative-adversarial-network","pytorch"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/aastopher.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":"2022-09-29T19:48:06.000Z","updated_at":"2022-10-17T21:54:12.000Z","dependencies_parsed_at":null,"dependency_job_id":"1052a782-e460-42a5-acac-e4864eb18bbd","html_url":"https://github.com/aastopher/Potato_GAN","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/aastopher/Potato_GAN","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aastopher%2FPotato_GAN","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aastopher%2FPotato_GAN/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aastopher%2FPotato_GAN/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aastopher%2FPotato_GAN/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/aastopher","download_url":"https://codeload.github.com/aastopher/Potato_GAN/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aastopher%2FPotato_GAN/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278577929,"owners_count":26009703,"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","status":"online","status_checked_at":"2025-10-06T02:00:05.630Z","response_time":65,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["deep-learning","gan","gans","generative-adversarial-network","pytorch"],"created_at":"2025-03-05T09:32:41.256Z","updated_at":"2025-10-06T08:08:37.996Z","avatar_url":"https://github.com/aastopher.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Potato Generating - DCGAN (Deep Convolutional Generative Adversarial Network)\n\nThe purpose of this project is to introduce the concepts behind basic image generation using a simple implementation of Deep Convolutional Generative Adversarial Networks. This project will detail a basic example, training DCGANs to reproduce images of a single class. Exploring the concepts related to how GANs work in general.\n\n### Running this notebook\n* The notebook will check for the presence of the dataset, if the folder does not exist (it will not on first run) then it will download the dataset automatically.\n* Given that the pickled models exist, the models will automatically be loaded an usable on your current device pre-trained.\n* The notebook will check for the pickled models, if either model does not exists it will begin to re-train on the current device. (i.e. just delete or remove the current model files to re-train)\n\n### References\n\n```\n@misc{https://doi.org/10.48550/arxiv.1406.2661,\n  doi = {10.48550/ARXIV.1406.2661},\n  url = {https://arxiv.org/abs/1406.2661},\n  author = {Goodfellow, Ian J. and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},\n  keywords = {Machine Learning (stat.ML), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},\n  title = {Generative Adversarial Networks},\n  publisher = {arXiv},\n  year = {2014},\n  copyright = {arXiv.org perpetual, non-exclusive license}\n}\n```\n```\n@misc{https://doi.org/10.48550/arxiv.1511.06434,\n  doi = {10.48550/ARXIV.1511.06434},\n  url = {https://arxiv.org/abs/1511.06434},\n  author = {Radford, Alec and Metz, Luke and Chintala, Soumith},\n  keywords = {Machine Learning (cs.LG), Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},\n  title = {Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks},\n  publisher = {arXiv},\n  year = {2015},\n  copyright = {arXiv.org perpetual, non-exclusive license}\n}\n```\n```\n@misc{https://doi.org/10.48550/arxiv.1606.03498,\n  doi = {10.48550/ARXIV.1606.03498},\n  url = {https://arxiv.org/abs/1606.03498},\n  author = {Salimans, Tim and Goodfellow, Ian and Zaremba, Wojciech and Cheung, Vicki and Radford, Alec and Chen, Xi},\n  keywords = {Machine Learning (cs.LG), Computer Vision and Pattern Recognition (cs.CV), Neural and Evolutionary Computing (cs.NE), FOS: Computer and information sciences, FOS: Computer and information sciences}, \n  title = {Improved Techniques for Training GANs},\n  publisher = {arXiv},\n  year = {2016},\n  copyright = {arXiv.org perpetual, non-exclusive license}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faastopher%2Fpotato_gan","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faastopher%2Fpotato_gan","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faastopher%2Fpotato_gan/lists"}