{"id":24506218,"url":"https://github.com/ragul-rofi/animalclassificationml","last_synced_at":"2025-10-04T19:15:34.947Z","repository":{"id":273231827,"uuid":"919021728","full_name":"ragul-rofi/AnimalClassificationML","owner":"ragul-rofi","description":"Animal Classification: A CNN-based image recognition model.","archived":false,"fork":false,"pushed_at":"2025-01-19T16:57:26.000Z","size":36699,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-08-26T02:51:00.656Z","etag":null,"topics":["keras-tensorflow","machine-learning","ml-model","python","tensorflow"],"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/ragul-rofi.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":"2025-01-19T14:09:04.000Z","updated_at":"2025-02-17T05:21:05.000Z","dependencies_parsed_at":"2025-03-15T08:44:42.056Z","dependency_job_id":null,"html_url":"https://github.com/ragul-rofi/AnimalClassificationML","commit_stats":null,"previous_names":["ragul-rofi/animalclassificationml"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ragul-rofi/AnimalClassificationML","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ragul-rofi%2FAnimalClassificationML","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ragul-rofi%2FAnimalClassificationML/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ragul-rofi%2FAnimalClassificationML/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ragul-rofi%2FAnimalClassificationML/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ragul-rofi","download_url":"https://codeload.github.com/ragul-rofi/AnimalClassificationML/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ragul-rofi%2FAnimalClassificationML/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278360967,"owners_count":25974381,"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","status":"online","status_checked_at":"2025-10-04T02:00:05.491Z","response_time":63,"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":["keras-tensorflow","machine-learning","ml-model","python","tensorflow"],"created_at":"2025-01-21T23:33:54.495Z","updated_at":"2025-10-04T19:15:34.902Z","avatar_url":"https://github.com/ragul-rofi.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Animal Classification Project\n\n## Project Overview\n\nThis project shows deep learning to classify animals in images. The model is trained using a dataset of labeled images and is implemented using TensorFlow/Keras. The dataset is split into training, validation, and test sets for training, model evaluation, and testing the performance of the trained model.\n\n## Table of Contents\n1. [Project Overview](#project-overview)\n4. [Dataset](#dataset)\n5. [Training the Model](#training-the-model)\n6. [Evaluating the Model](#evaluating-the-model)\n7. [File Structure](#file-structure)\n8. [License](#license)\n\n## Dependencies\n\nTo run this project, ensure you have Python installed along with the following libraries:\n\n- **TensorFlow** (for training and evaluating the model)\n- **Keras** (for model building)\n- **scikit-learn** (for dataset splitting)\n\n\nDataset\n-------\n\nThe dataset used in this project contains images of various animals. The images are split into the following categories:\n\n*   **Training Data**: 80% of the total dataset used for training the model.\n    \n*   **Validation Data**: 10% used for model validation during training.\n    \n*   **Test Data**: 10% used for evaluating the final model.\n    \n\nThe prepared dataset structure should look like this:\n\n```bash\nprocessed_dataset/\n├── train/\n├── validation/\n└── test/\n```\nTraining the Model\n----------------\nTo train the model, run the following command:\n\n```bash\npython main.py\n```\n\n### Hyperparameters:\n\n*   **Epochs**: Set to 10 (You can modify this value in the code).\n    \n*   **Batch Size**: 32 (Also adjustable).\n    \n*   **Model**: A CNN built with multiple convolutional layers, max pooling, and dense layers.\n    \n\n### The process will:\n\n*   Load and preprocess the data.\n    \n*   Build the CNN model.\n    \n*   Train the model and save the best model using checkpoints.\n    \n\nYou can adjust training parameters such as epochs and batch size in the code.\n\nEvaluating the Model\n--------------------\n\nAfter training the model, evaluate it using the following command:\n\n```bash\npython evaluate_model.py\n```\nThis will:\n\n*   Load the best-trained model.\n    \n*   Evaluate its performance on the test data.\n    \n*   Print the accuracy and loss of the model on the test dataset.\n\nLicense\n-------\n\nThis project is licensed under the MIT License - see the [LICENSE](https://github.com/ragul-rofi/AnimalClassificationML/blob/main/LICENSE) file for details.\n\n### Notes:\n\n*   **Git LFS**: For large files like the .keras model file, use [Git Large File Storage (LFS)](https://git-lfs.github.com/). Follow the instructions in the Git LFS documentation to set it up.\n    \n*   **Data Privacy**: Make sure you have the appropriate rights and permissions to share or use the dataset if it contains sensitive information.\n    \n*   **Dataset Download**: If you need to download an existing dataset, refer to the dataset page or use any other public animal classification dataset.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fragul-rofi%2Fanimalclassificationml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fragul-rofi%2Fanimalclassificationml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fragul-rofi%2Fanimalclassificationml/lists"}