{"id":25990129,"url":"https://github.com/oemanuelfirmino/image_classifier","last_synced_at":"2026-06-01T08:32:01.682Z","repository":{"id":271648062,"uuid":"914134636","full_name":"oEmanuelFirmino/image_classifier","owner":"oEmanuelFirmino","description":"A deep learning model using CNN to classify dog and cat images, with an interactive Streamlit interface for real-time predictions and training visualizations.","archived":false,"fork":false,"pushed_at":"2026-02-07T01:41:24.000Z","size":1227,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2026-02-07T13:07:25.543Z","etag":null,"topics":["data-science","deep-learning","machine-learning","neural-network","python"],"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/oEmanuelFirmino.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":"2025-01-09T02:27:32.000Z","updated_at":"2026-02-07T01:41:28.000Z","dependencies_parsed_at":null,"dependency_job_id":"a1d267f6-d269-4e74-abaf-7900b2ce2202","html_url":"https://github.com/oEmanuelFirmino/image_classifier","commit_stats":null,"previous_names":["oemanuelfirmino/image_classifier"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/oEmanuelFirmino/image_classifier","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oEmanuelFirmino%2Fimage_classifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oEmanuelFirmino%2Fimage_classifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oEmanuelFirmino%2Fimage_classifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oEmanuelFirmino%2Fimage_classifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/oEmanuelFirmino","download_url":"https://codeload.github.com/oEmanuelFirmino/image_classifier/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oEmanuelFirmino%2Fimage_classifier/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33767435,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-01T02:00:06.963Z","response_time":115,"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":["data-science","deep-learning","machine-learning","neural-network","python"],"created_at":"2025-03-05T13:32:57.649Z","updated_at":"2026-06-01T08:32:01.667Z","avatar_url":"https://github.com/oEmanuelFirmino.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# Image Classifier\n\nA deep learning model using Convolutional Neural Networks (CNN) to classify images of dogs and cats. The project features an interactive Streamlit interface for real-time image prediction and visualization of model training metrics.\n\n## Features\n\n- Upload images of dogs or cats for classification.\n- Real-time predictions with confidence scores.\n- Visualization of training history (accuracy, loss).\n- Displays model architecture summary.\n\n## Technologies Used\n\n- **TensorFlow/Keras**: For the deep learning model.\n- **Streamlit**: For building the web interface.\n- **Plotly**: For interactive data visualizations.\n- **Matplotlib**: For training history plots.\n\n## Installation\n\n1. Clone this repository:\n\n   ```bash\n   git clone https://github.com/oEmanuelFirmino/image_classifier.git\n   ```\n\n2. Install the required dependencies:\n\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n3. Run the Streamlit app:\n\n   ```bash\n   streamlit run app.py\n   ```\n\n## Model Training\n\nThe model is a Convolutional Neural Network (CNN) with the following architecture:\n- 3 Convolutional layers with MaxPooling.\n- Global Average Pooling layer.\n- Fully connected Dense layer with 128 neurons.\n- Dropout regularization to prevent overfitting.\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foemanuelfirmino%2Fimage_classifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Foemanuelfirmino%2Fimage_classifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foemanuelfirmino%2Fimage_classifier/lists"}