{"id":16392718,"url":"https://github.com/facundoq/tinyimagenet","last_synced_at":"2026-04-09T03:34:02.487Z","repository":{"id":44679351,"uuid":"512939561","full_name":"facundoq/tinyimagenet","owner":"facundoq","description":"Dataset class for PyTorch and the TinyImageNet dataset with automated download \u0026 extraction..","archived":false,"fork":false,"pushed_at":"2023-12-27T15:11:41.000Z","size":83,"stargazers_count":5,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-12-17T03:26:54.664Z","etag":null,"topics":[],"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/facundoq.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":"2022-07-11T23:44:16.000Z","updated_at":"2025-05-18T12:49:30.000Z","dependencies_parsed_at":"2024-10-11T04:51:11.936Z","dependency_job_id":"d869b406-ad6f-4518-b5e1-790b2f648b2d","html_url":"https://github.com/facundoq/tinyimagenet","commit_stats":{"total_commits":6,"total_committers":2,"mean_commits":3.0,"dds":"0.16666666666666663","last_synced_commit":"7f60d24c0d9db766f1d5fdd143c369e00c29ab3e"},"previous_names":[],"tags_count":17,"template":false,"template_full_name":null,"purl":"pkg:github/facundoq/tinyimagenet","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/facundoq%2Ftinyimagenet","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/facundoq%2Ftinyimagenet/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/facundoq%2Ftinyimagenet/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/facundoq%2Ftinyimagenet/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/facundoq","download_url":"https://codeload.github.com/facundoq/tinyimagenet/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/facundoq%2Ftinyimagenet/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31584662,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-08T14:31:17.711Z","status":"online","status_checked_at":"2026-04-09T02:00:06.848Z","response_time":112,"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":[],"created_at":"2024-10-11T04:51:04.645Z","updated_at":"2026-04-09T03:34:02.466Z","avatar_url":"https://github.com/facundoq.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# torchvision-tinyimagenet\nDataset class for PyTorch and the TinyImageNet dataset.\n\n# Installation\n\n``` pip install tinyimagenet ```\n\n# How to use\n````\nfrom tinyimagenet import TinyImageNet\nfrom pathlib import Path\nimport logging\n\nlogging.basicConfig(level=logging.INFO)\n\nsplit =\"val\"\ndataset = TinyImageNet(Path(\"~/.torchvision/tinyimagenet/\"),split=split,imagenet_idx=False)\nn = len(dataset)\nprint(f\"TinyImageNet, split {split}, has  {n} samples.\")\nn_samples = 5\nprint(f\"Showing info of {n_samples} samples...\")\nfor i in range(0,n,n//n_samples):\n    image,klass = dataset[i]\n    print(f\"Sample of class {klass:3d}, image {image}, words {dataset.idx_to_words[klass]}\")\n````\n\nThe `imagenet_idx` indicates if the dataset's labels correspond to those in the full ImageNet dataset. By default (`imagenet_idx=False`) the labels are renumbered sequentially so that the 200 classes are named 0, 1, 2, ..., 199. \n\nYou can also check the [quickstart notebook](https://colab.research.google.com/drive/1FCDsDJg86mCjyeAWOxDW9iF49goWCx4j?usp=sharing) to peruse the dataset.\n\nFinally, we also provide some example notebooks that use TinyImageNet with PyTorch models:\n\n* [Evaluate a pretrained EfficientNet model](https://colab.research.google.com/github/facundoq/tinyimagenet/blob/main/Eval%20EfficientNet%20with%20TinyImageNet.ipynb#scrollTo=41aVk-yvEV-o)\n* [Train a simple CNN on the dataset](\nhttps://colab.research.google.com/github/facundoq/tinyimagenet/blob/main/Train%20basic%20CNN%20with%20TinyImageNet.ipynb#scrollTo=4CiA6z8reXYP)\n* [Finetune an EfficientNet model pretrained on the full ImageNet to classify only the 200 classes of TinyImageNet](https://colab.research.google.com/github/facundoq/tinyimagenet/blob/main/Finetune%20EfficientNet%20with%20TinyImageNet.ipynb)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffacundoq%2Ftinyimagenet","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffacundoq%2Ftinyimagenet","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffacundoq%2Ftinyimagenet/lists"}