{"id":28100136,"url":"https://github.com/farhad-here/image-dataset-splitter","last_synced_at":"2026-04-29T04:37:53.174Z","repository":{"id":293056385,"uuid":"982802538","full_name":"farhad-here/Image-Dataset-Splitter","owner":"farhad-here","description":"A simple Streamlit app that splits a zipped image dataset into train, validation, and test folders automatically.","archived":false,"fork":false,"pushed_at":"2025-05-29T07:46:03.000Z","size":12,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-29T08:57:27.895Z","etag":null,"topics":["deep-learning","io","os","python","random","shutil","streamlit","zipfile"],"latest_commit_sha":null,"homepage":"https://image-dataset-splitter.streamlit.app/","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/farhad-here.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,"zenodo":null}},"created_at":"2025-05-13T12:33:05.000Z","updated_at":"2025-05-29T07:46:06.000Z","dependencies_parsed_at":null,"dependency_job_id":"71abf4d1-5908-4ab3-bf90-27cd6e88ba43","html_url":"https://github.com/farhad-here/Image-Dataset-Splitter","commit_stats":null,"previous_names":["farhad-here/image-dataset-splitter"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/farhad-here/Image-Dataset-Splitter","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/farhad-here%2FImage-Dataset-Splitter","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/farhad-here%2FImage-Dataset-Splitter/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/farhad-here%2FImage-Dataset-Splitter/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/farhad-here%2FImage-Dataset-Splitter/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/farhad-here","download_url":"https://codeload.github.com/farhad-here/Image-Dataset-Splitter/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/farhad-here%2FImage-Dataset-Splitter/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":261759469,"owners_count":23205555,"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":["deep-learning","io","os","python","random","shutil","streamlit","zipfile"],"created_at":"2025-05-13T18:30:32.803Z","updated_at":"2026-04-29T04:37:53.137Z","avatar_url":"https://github.com/farhad-here.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 📁 Image Dataset Splitter\n\nThis Streamlit app allows you to split any labeled image dataset into `train`, `validation`, and `test` sets — all with a single click. Simply upload a `.zip` file where each folder represents a class, and the app will generate a downloadable zip with the organized dataset structure.\n\n---\n\n## 🚀 Features\n\n✅ Upload a `.zip` file with folders of images (each folder is treated as a class)  \n✅ Automatically split into `train`, `val`, and `test` folders  \n✅ Random shuffling of images for fair distribution  \n✅ Download the final dataset as a ready-to-use `.zip`  \n✅ Clean UI with Streamlit  \n\n---\n\n## 📂 Expected Input Format\n\nYour input `.zip` file should be structured like this:\n\n\nEach folder is interpreted as a separate class label.\n\n---\n\n## 🧾 Output Format\n\nAfter splitting, the app generates a `.zip` file like this:\n\n\n---\n\n## ⚙️ Configuration\n\nYou can modify the train/val/test split ratios by editing this line in `app.py`:\n\n```python\nSPLIT_RATIO = (0.7, 0.15, 0.15)\n\ngit clone https://github.com/your-username/image-dataset-splitter.git\ncd image-dataset-splitter\n```\n\n```python\npip install streamlit\nstreamlit run app.py\n```\n---\n\n📌 Use Cases\n- Preparing image datasets for machine learning / deep learning\n\n- Organizing animal or object classification datasets\n\n- Creating train/val/test splits without writing custom scripts\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffarhad-here%2Fimage-dataset-splitter","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffarhad-here%2Fimage-dataset-splitter","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffarhad-here%2Fimage-dataset-splitter/lists"}