{"id":25473640,"url":"https://github.com/sahilsnk/docker-ai-image-classifier","last_synced_at":"2026-05-08T14:32:54.451Z","repository":{"id":276187038,"uuid":"928507123","full_name":"sahilsnk/docker-ai-image-classifier","owner":"sahilsnk","description":"This project is a web-based AI image classifier that utilizes MobileNetV2, a pre-trained deep learning model, to classify images uploaded by users. The application is built using Flask and deployed using Docker and Render for cloud hosting with CI/CD integration","archived":false,"fork":false,"pushed_at":"2025-02-08T18:39:07.000Z","size":4076,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-31T11:51:34.920Z","etag":null,"topics":["docker","flask","image-classification"],"latest_commit_sha":null,"homepage":"https://docker-ai-image-classifier.onrender.com/","language":"Python","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/sahilsnk.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":"2025-02-06T18:43:12.000Z","updated_at":"2025-02-08T18:39:10.000Z","dependencies_parsed_at":null,"dependency_job_id":"1384d5cb-ab06-4b71-a2be-a0a76b99a0a5","html_url":"https://github.com/sahilsnk/docker-ai-image-classifier","commit_stats":null,"previous_names":["sahilsnk/docker-ai-image-classifier"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/sahilsnk/docker-ai-image-classifier","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sahilsnk%2Fdocker-ai-image-classifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sahilsnk%2Fdocker-ai-image-classifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sahilsnk%2Fdocker-ai-image-classifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sahilsnk%2Fdocker-ai-image-classifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sahilsnk","download_url":"https://codeload.github.com/sahilsnk/docker-ai-image-classifier/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sahilsnk%2Fdocker-ai-image-classifier/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32784451,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-08T08:22:46.396Z","status":"ssl_error","status_checked_at":"2026-05-08T08:22:45.650Z","response_time":54,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["docker","flask","image-classification"],"created_at":"2025-02-18T10:36:14.553Z","updated_at":"2026-05-08T14:32:54.419Z","avatar_url":"https://github.com/sahilsnk.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Docker AI Image Classifier\n\n## Overview\nThis project is an AI-powered image classification web application built using **Flask** and **MobileNetV2**. It allows users to upload images, which are then classified into different categories using a pre-trained deep learning model. The application is containerized using **Docker** and deployed on **Render** with a CI/CD pipeline.\n\n## Features\n- Upload images via a simple web interface\n- Classify images using **MobileNetV2** (pre-trained on ImageNet)\n- Display classification results in a user-friendly UI\n- Dockerized for easy deployment\n- Integrated CI/CD pipeline for automated deployment\n\n## Tech Stack\n- **Backend:** Flask\n- **Machine Learning Model:** MobileNetV2 (TensorFlow/Keras)\n- **Frontend:** HTML, CSS\n- **Containerization:** Docker\n- **CI/CD:** GitHub Actions\n- **Hosting:** Render\n\n## Setup and Installation\n### Prerequisites\nEnsure you have the following installed:\n- Python (3.8 or later)\n- pip\n- Docker\n- Git\n\n### Clone the Repository\n```sh\n git clone https://github.com/your-username/docker-ai-image-classifier.git\n cd docker-ai-image-classifier\n```\n\n### Install Dependencies\n```sh\npip install -r requirements.txt\n```\n\n### Run the Application\n```sh\npython app.py\n```\nThe application will be accessible at `http://127.0.0.1:5000/`.\n\n## Docker Instructions\n### Build the Docker Image\n```sh\ndocker build -t docker-ai-image-classifier .\n```\n\n### Run the Docker Container\n```sh\ndocker run -d -p 5000:5000 --name image_classifier docker-ai-image-classifier\n```\n\n### Stop and Remove the Container\n```sh\ndocker stop image_classifier\ndocker rm image_classifier\n```\n\n## CI/CD Pipeline\n### GitHub Actions Workflow\nThis project includes a **GitHub Actions** workflow that automates testing, building, and deployment.\n\n1. **On push to `main` branch:**\n   - The workflow runs tests (if available).\n   - Builds a Docker image and pushes it to **Docker Hub**.\n   - Triggers deployment to **Render**.\n\n2. **Secrets Required:**\n   - `DOCKERHUB_USERNAME` and `DOCKERHUB_PASSWORD`\n   - `RENDER_DEPLOY_HOOK`\n\n### Deployment to Render\n- Create a new **Web Service** on Render.\n- Connect your GitHub repository.\n- Set the **Build Command:** `docker build -t your-username/docker-ai-image-classifier .`\n- Set the **Start Command:** `docker run -p 5000:5000 your-username/docker-ai-image-classifier`\n\n## Usage\n1. Open the web application.\n2. Upload an image.\n3. The model classifies the image and displays the top predictions.\n\n## Contributing\nContributions are welcome! Feel free to submit issues or pull requests.\n\n## License\nThis project is licensed under the MIT License.\n\n## Contact\nFor any questions, reach out via email: [sahilsnaik00@gmail.com]\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsahilsnk%2Fdocker-ai-image-classifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsahilsnk%2Fdocker-ai-image-classifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsahilsnk%2Fdocker-ai-image-classifier/lists"}