{"id":28712832,"url":"https://github.com/mohanseetha/pneumonia-prediction","last_synced_at":"2025-06-15T00:02:15.852Z","repository":{"id":298874403,"uuid":"1001352560","full_name":"mohanseetha/pneumonia-prediction","owner":"mohanseetha","description":"an end-to-end deep learning project for detecting pneumonia in chest x-ray images using pytorch and a pre-trained resnet18 model, featuring a streamlit web app for easy, local predictions","archived":false,"fork":false,"pushed_at":"2025-06-13T10:15:39.000Z","size":40786,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-13T11:23:57.161Z","etag":null,"topics":["deep-learning","machine-learning","pytorch","resnet-18","streamlit"],"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/mohanseetha.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,"zenodo":null}},"created_at":"2025-06-13T08:29:36.000Z","updated_at":"2025-06-13T10:15:42.000Z","dependencies_parsed_at":"2025-06-13T11:34:21.542Z","dependency_job_id":null,"html_url":"https://github.com/mohanseetha/pneumonia-prediction","commit_stats":null,"previous_names":["mohanseetha/pneumonia-prediction"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mohanseetha/pneumonia-prediction","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mohanseetha%2Fpneumonia-prediction","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mohanseetha%2Fpneumonia-prediction/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mohanseetha%2Fpneumonia-prediction/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mohanseetha%2Fpneumonia-prediction/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mohanseetha","download_url":"https://codeload.github.com/mohanseetha/pneumonia-prediction/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mohanseetha%2Fpneumonia-prediction/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":259901296,"owners_count":22929219,"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","machine-learning","pytorch","resnet-18","streamlit"],"created_at":"2025-06-15T00:00:44.023Z","updated_at":"2025-06-15T00:02:15.841Z","avatar_url":"https://github.com/mohanseetha.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Chest X-ray Pneumonia Detection with Deep Learning\n\nThis project implements an end-to-end deep learning pipeline for automatic detection of pneumonia from chest X-ray images. Using transfer learning with PyTorch and a pre-trained ResNet18 model, the system classifies chest X-rays as NORMAL or PNEUMONIA. The project also features a user-friendly Streamlit web app for fast, local inference.\n\n## Features\n\n- **Data Preparation**: Guide and notebook (Colab) for dataset preprocessing and augmentation.\n- **Model Training**: PyTorch-based transfer learning with ResNet18.\n- **Evaluation**: Classification report, confusion matrix, ROC curve, and Precision-Recall curve.\n- **Deployment**: Streamlit app for local image upload and instant prediction.\n- **Clean Structure**: Modular folders for models, notebooks, and app code.\n\n## Quick Start\n\n1. Clone the Repository\n\n```\ngit clone git@github.com:mohanseetha/pneumonia-prediction.git\ncd pneumonia-prediction\n```\n\n2. Install Dependencies\n\n```\npip install torch torchvision streamlit scikit-learn matplotlib pillow\n```\n\n3. Open `⁠notebooks/chest_xray_training.ipynb⁠` in Google Colab or Jupyter.\n\n4. Follow the instructions to prepare the data, train, and evaluate the model.\n\n5. Download the resulting `⁠.pth⁠` file and place it in the `⁠models/`⁠ folder.\n\n6. Run the Streamlit App\n\n```\nstreamlit run app.py\n```\n\nOpen http://localhost:8501 in your browser. Upload a chest X-ray image and receive a prediction: NORMAL or PNEUMONIA.\n\n## References\n\n- [Chest X-ray Images (Pneumonia) Dataset on Kaggle](https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia/data)\n- [PyTorch Documentation](https://docs.pytorch.org/docs/stable/index.html)\n- [Streamlit Documentation](https://docs.streamlit.io/)\n\n## Note\n\nThis project is for educational and research purposes only.\nPlease consult a medical professional for any health-related decisions.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohanseetha%2Fpneumonia-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmohanseetha%2Fpneumonia-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohanseetha%2Fpneumonia-prediction/lists"}