{"id":19665351,"url":"https://github.com/savinrazvan/traffic","last_synced_at":"2026-05-06T14:40:23.856Z","repository":{"id":250906008,"uuid":"835757073","full_name":"SavinRazvan/traffic","owner":"SavinRazvan","description":"This project aims to develop a neural network using TensorFlow to classify traffic signs from images, utilizing the German Traffic Sign Recognition Benchmark (GTSRB) dataset.","archived":false,"fork":false,"pushed_at":"2024-07-30T17:13:55.000Z","size":190,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-27T03:50:21.337Z","etag":null,"topics":["ai","cnn","data-augmentation","data-preprocessing","deep-learning","gtsrb","image-recognition","machine-learning","model-evaluation","model-training","opencv","tensorflow","traffic-sign-classification"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/SavinRazvan.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","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":"2024-07-30T13:23:44.000Z","updated_at":"2024-08-08T04:42:01.000Z","dependencies_parsed_at":"2024-07-30T19:40:01.814Z","dependency_job_id":"b8448c4e-b967-4bca-aabd-039e077caaaf","html_url":"https://github.com/SavinRazvan/traffic","commit_stats":null,"previous_names":["savinrazvan/traffic"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/SavinRazvan/traffic","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SavinRazvan%2Ftraffic","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SavinRazvan%2Ftraffic/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SavinRazvan%2Ftraffic/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SavinRazvan%2Ftraffic/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/SavinRazvan","download_url":"https://codeload.github.com/SavinRazvan/traffic/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SavinRazvan%2Ftraffic/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32699077,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-06T08:33:17.875Z","status":"ssl_error","status_checked_at":"2026-05-06T08:33:17.221Z","response_time":117,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: 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":["ai","cnn","data-augmentation","data-preprocessing","deep-learning","gtsrb","image-recognition","machine-learning","model-evaluation","model-training","opencv","tensorflow","traffic-sign-classification"],"created_at":"2024-11-11T16:22:20.609Z","updated_at":"2026-05-06T14:40:23.836Z","avatar_url":"https://github.com/SavinRazvan.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"### Traffic Sign Classification with TensorFlow\n\nThis project aims to develop a neural network using TensorFlow to classify traffic signs from images, utilizing the German Traffic Sign Recognition Benchmark (GTSRB) dataset.\n\n#### Features\n1. **Data Preparation**:\n   - Images are preprocessed using OpenCV for resizing and normalization.\n   - Data augmentation techniques are applied to enhance the diversity of the training dataset.\n\n2. **Model Development**:\n   - A convolutional neural network (CNN) is constructed with TensorFlow.\n   - The architecture includes convolutional layers for feature extraction, pooling layers for downsampling, and fully connected layers for final classification.\n\n3. **Evaluation**:\n   - The model's performance is validated using a separate test dataset.\n   - Predictions are made on unseen data to evaluate real-world applicability.\n\n4. **Documentation**:\n   - Comprehensive documentation of the experimentation process, including hyperparameter tuning and model iterations.\n\n#### Dataset\nThe GTSRB dataset can be accessed via the following links:\n- [GTSRB - Training and Testing Dataset](https://cdn.cs50.net/ai/2023/x/projects/5/gtsrb.zip)\n- [GTSRB Small - Training and Testing Dataset](https://cdn.cs50.net/ai/2023/x/projects/5/gtsrb-small.zip)\n\n#### Code Modifications\nThis implementation includes several enhancements for improved model performance and additional functionality.\n\n#### Additional Resources\nFor further information, visit the [project page](https://cs50.harvard.edu/ai/2020/projects/5/traffic/).","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsavinrazvan%2Ftraffic","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsavinrazvan%2Ftraffic","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsavinrazvan%2Ftraffic/lists"}