{"id":23223169,"url":"https://github.com/shadmehrbakhtiary/dog-cat-classification","last_synced_at":"2026-04-28T18:35:35.705Z","repository":{"id":220715198,"uuid":"752288825","full_name":"ShadmehrBakhtiary/dog-cat-classification","owner":"ShadmehrBakhtiary","description":"This project implements a Convolutional Neural Network (CNN) to classify images of dogs and cats","archived":false,"fork":false,"pushed_at":"2024-02-03T19:41:39.000Z","size":5,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-05T16:35:13.998Z","etag":null,"topics":["classification","cnn","python","tenserflow"],"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/ShadmehrBakhtiary.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":"2024-02-03T15:21:04.000Z","updated_at":"2024-03-23T07:50:52.000Z","dependencies_parsed_at":null,"dependency_job_id":"1a1eb719-7331-4e7b-81f0-18309ea12d72","html_url":"https://github.com/ShadmehrBakhtiary/dog-cat-classification","commit_stats":null,"previous_names":["shadmehrbakhtiary/dog-cat-classification"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ShadmehrBakhtiary/dog-cat-classification","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ShadmehrBakhtiary%2Fdog-cat-classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ShadmehrBakhtiary%2Fdog-cat-classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ShadmehrBakhtiary%2Fdog-cat-classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ShadmehrBakhtiary%2Fdog-cat-classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ShadmehrBakhtiary","download_url":"https://codeload.github.com/ShadmehrBakhtiary/dog-cat-classification/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ShadmehrBakhtiary%2Fdog-cat-classification/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32394467,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-28T14:34:11.604Z","status":"ssl_error","status_checked_at":"2026-04-28T14:32:37.009Z","response_time":56,"last_error":"SSL_read: 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":["classification","cnn","python","tenserflow"],"created_at":"2024-12-18T23:16:22.868Z","updated_at":"2026-04-28T18:35:35.700Z","avatar_url":"https://github.com/ShadmehrBakhtiary.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Dog-Cat Image Classification using CNN\n\nThis project implements a Convolutional Neural Network (CNN) to classify images of dogs and cats. The model is trained on a high-quality dataset of dog and cat images to achieve accurate classification.\n\n\n## Overview\n\nThe project uses deep learning techniques to build and train a CNN model for image classification. The model is trained on a large dataset of dog and cat images to learn and differentiate between the two classes.\n\n## Requirements\n\n- Python 3\n- TensorFlow\n- Keras\n- NumPy\n- Matplotlib\n- Jupyter Notebook (optional, for running the code in a notebook)\n\n## Dataset\n\nThe dataset used for training and testing the model consists of a large number of dog and cat images. Due to the high size of the dataset, it is not included in this repository.\n\n## Model Architecture\n\nThe CNN model architecture used for image classification consists of several convolutional layers, pooling layers, and fully connected layers. The model is designed to learn and extract features from the input images to make accurate predictions.\n\n## Training\n\nThe model is trained using the dataset, and the training process involves optimizing the model's parameters to minimize classification errors. The training process may take a significant amount of time due to the large dataset size.\n\n## Evaluation\n\nThe trained model is evaluated on a separate test set to measure its performance in classifying unseen images of dogs and cats.\n\n## Results\n\nThe results of the image classification model, including accuracy and performance metrics, will be presented in the project.\n\n## Usage\n\nTo use the trained model for classifying images of dogs and cats, follow the instructions provided in the project code.\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshadmehrbakhtiary%2Fdog-cat-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshadmehrbakhtiary%2Fdog-cat-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshadmehrbakhtiary%2Fdog-cat-classification/lists"}