{"id":24156084,"url":"https://github.com/programmer-rd-ai/digivis","last_synced_at":"2025-06-10T17:04:44.341Z","repository":{"id":180393892,"uuid":"664135567","full_name":"Programmer-RD-AI/DigiVis","owner":"Programmer-RD-AI","description":"A PyTorch-based deep learning implementation for MNIST digit recognition featuring CNNs, GPU acceleration, experiment tracking, and comprehensive testing capabilities.","archived":false,"fork":false,"pushed_at":"2025-01-12T11:17:45.000Z","size":85960,"stargazers_count":1,"open_issues_count":14,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-03-01T23:52:19.285Z","etag":null,"topics":["cnn","computer-vision","cuda","data-science","deep-learning","digit-recognition","image-classification","machine-learning","mnist","neural-networks","python","pytorch","wandb"],"latest_commit_sha":null,"homepage":"https://wandb.ai/ranuga-d/DigiVis/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Programmer-RD-AI.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":"2023-07-09T02:40:28.000Z","updated_at":"2025-01-12T11:21:27.000Z","dependencies_parsed_at":"2025-01-12T12:31:37.876Z","dependency_job_id":null,"html_url":"https://github.com/Programmer-RD-AI/DigiVis","commit_stats":null,"previous_names":["programmer-rd-ai/digit-recognizer-v2"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Programmer-RD-AI%2FDigiVis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Programmer-RD-AI%2FDigiVis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Programmer-RD-AI%2FDigiVis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Programmer-RD-AI%2FDigiVis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Programmer-RD-AI","download_url":"https://codeload.github.com/Programmer-RD-AI/DigiVis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241439555,"owners_count":19963098,"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":["cnn","computer-vision","cuda","data-science","deep-learning","digit-recognition","image-classification","machine-learning","mnist","neural-networks","python","pytorch","wandb"],"created_at":"2025-01-12T13:11:05.982Z","updated_at":"2025-03-01T23:52:34.406Z","avatar_url":"https://github.com/Programmer-RD-AI.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DigiVis: Neural Network Vision for Digit Classification\n\nA deep learning implementation for MNIST digit recognition using convolutional neural networks and computer vision techniques. This project combines modern neural architectures with advanced image processing for accurate digit classification.\n\n## Overview\n\nDigiVis is a comprehensive implementation of various neural network architectures for digit recognition, utilizing the MNIST dataset. The project incorporates modern deep learning practices including data normalization, image transformations, and model evaluation metrics.\n\n## Features\n\n- Multiple neural network architectures (CNN and Linear models)\n- Data normalization and preprocessing\n- Image transformations and augmentations\n- Model training with performance metrics\n- Weights \u0026 Biases integration for experiment tracking\n- Comprehensive test suite\n- CUDA support for GPU acceleration\n\n## Requirements\n\n- Python 3.x\n- PyTorch\n- torchvision\n- numpy\n- pandas\n- Pillow\n- wandb\n- matplotlib\n- scikit-learn\n- tqdm\n\n## Installation\n\n1. Clone the repository\n\n```bash\ngit clone https://github.com/Programmer-RD-AI/DigiVis.git\n```\n\n2. Install dependencies\n\n```bash\npip install -r requirements.txt\n```\n\n## Usage\n\nRun the main training script:\n\n```\npython run.py\n```\n\nFor interactive exploration, use the provided Jupyter notebook:\n\n```\njupyter notebook test.ipynb\n```\n\n## Model Configuration\n\n- Image Size: 224x224\n- Batch Size: 32\n- CUDA enabled for GPU acceleration\n- Random seed: 42 for reproducibility\n\n## License\n\nThis project is licensed under the Apache License 2.0 - see the LICENSE file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprogrammer-rd-ai%2Fdigivis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprogrammer-rd-ai%2Fdigivis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprogrammer-rd-ai%2Fdigivis/lists"}