{"id":28476180,"url":"https://github.com/zainlatif/rat_detection_cnn_image","last_synced_at":"2026-05-05T08:31:46.444Z","repository":{"id":296541223,"uuid":"993731132","full_name":"zainlatif/Rat_Detection_CNN_image","owner":"zainlatif","description":"🐭 rat detection using cnn this beginner-level computer vision project uses a convolutional neural network (cnn) to classify images as containing a rat or not. built in jupyter notebook with tensorflow and keras, it uses a pre-trained dataset and allows you to test custom images by placing them in a testing_folder.","archived":false,"fork":false,"pushed_at":"2025-06-21T05:51:40.000Z","size":94812,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-21T06:29:55.406Z","etag":null,"topics":["animal-detection","cnn","deep-learning","jupyter-notebook","object-detection","python","rat-detection","tensorflow"],"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/zainlatif.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":"2025-05-31T11:57:35.000Z","updated_at":"2025-06-21T05:51:45.000Z","dependencies_parsed_at":"2025-06-01T00:41:20.203Z","dependency_job_id":null,"html_url":"https://github.com/zainlatif/Rat_Detection_CNN_image","commit_stats":null,"previous_names":["zainlatif/rat_detection_cnn_image"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/zainlatif/Rat_Detection_CNN_image","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zainlatif%2FRat_Detection_CNN_image","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zainlatif%2FRat_Detection_CNN_image/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zainlatif%2FRat_Detection_CNN_image/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zainlatif%2FRat_Detection_CNN_image/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/zainlatif","download_url":"https://codeload.github.com/zainlatif/Rat_Detection_CNN_image/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zainlatif%2FRat_Detection_CNN_image/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263050730,"owners_count":23405909,"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":["animal-detection","cnn","deep-learning","jupyter-notebook","object-detection","python","rat-detection","tensorflow"],"created_at":"2025-06-07T15:06:15.371Z","updated_at":"2026-05-05T08:31:41.408Z","avatar_url":"https://github.com/zainlatif.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Rat Detection CNN\n\nThis project implements a Convolutional Neural Network (CNN) for detecting rats in images. The model is trained using a dataset of images containing rats and images without rats.\n\n## Project Structure\n\n- `dataset/`: Contains the training data for the model.\n  - `rat/`: Folder with images of rats for training.\n  - `no_rat/`: Folder with images without rats for training.\n  \n- `testing_folder/`: Contains sample images used for testing the trained model.\n  - `test_image.jpeg`: A sample image for testing the model's predictions.\n\n- `model/`: Stores the trained CNN model.\n  - `rat_cnn_model.h5`: The file where the trained model is saved.\n\n- `rat_detection.ipynb`: A Jupyter notebook that includes:\n  - Code for training the CNN model.\n  - Evaluation of the model's performance.\n  - Making predictions on new images.\n\n## Setup Instructions\n\n1. Clone the repository:\n   ```\n   git clone \u003crepository-url\u003e\n   ```\n\n2. Navigate to the project directory:\n   ```\n   cd Rat_Detection_CNN\n   ```\n\n3. Install the required packages:\n   ```\n   pip install -r requirements.txt\n   ```\n\n## Usage\n\n1. Open the `rat_detection.ipynb` notebook in Jupyter.\n2. Follow the instructions in the notebook to train the model and evaluate its performance.\n3. Use the trained model to make predictions on new images.\n\n## License\n\nThis project is licensed under the MIT License.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzainlatif%2Frat_detection_cnn_image","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzainlatif%2Frat_detection_cnn_image","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzainlatif%2Frat_detection_cnn_image/lists"}