{"id":18994754,"url":"https://github.com/aritrosaha10/blindspotdetection","last_synced_at":"2025-07-20T06:04:50.511Z","repository":{"id":104928261,"uuid":"373611722","full_name":"AritroSaha10/BlindSpotDetection","owner":"AritroSaha10","description":"A camera-based solution for checking a blind spot programmatically using machine learning. ","archived":false,"fork":false,"pushed_at":"2024-04-25T15:54:32.000Z","size":10725,"stargazers_count":10,"open_issues_count":0,"forks_count":2,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-22T12:57:18.302Z","etag":null,"topics":["camera","jupyter-notebook","machine-learning","python","raspberry-pi","raspberry-pi-4","rpi","rpi4","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":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/AritroSaha10.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":"2021-06-03T18:56:22.000Z","updated_at":"2025-03-03T14:09:57.000Z","dependencies_parsed_at":null,"dependency_job_id":"96be1e91-e411-4930-8c86-c9826d73d0fd","html_url":"https://github.com/AritroSaha10/BlindSpotDetection","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/AritroSaha10/BlindSpotDetection","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AritroSaha10%2FBlindSpotDetection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AritroSaha10%2FBlindSpotDetection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AritroSaha10%2FBlindSpotDetection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AritroSaha10%2FBlindSpotDetection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AritroSaha10","download_url":"https://codeload.github.com/AritroSaha10/BlindSpotDetection/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AritroSaha10%2FBlindSpotDetection/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266076051,"owners_count":23872729,"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":["camera","jupyter-notebook","machine-learning","python","raspberry-pi","raspberry-pi-4","rpi","rpi4","tensorflow"],"created_at":"2024-11-08T17:26:57.135Z","updated_at":"2025-07-20T06:04:50.486Z","avatar_url":"https://github.com/AritroSaha10.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Blind Spot Detection using Machine Learning\nA lightweight camera-based solution for checking a blind spot programmatically using TensorFlow and Python on a Raspberry Pi. \n\n## Repository Contents\nThis repository contains multiple elements of the project. These elements include:\n- Jupyter Notebook going into how the model was made\n- The trained model\n- Python program that uses the model on two cameras\n\n## Model Info\nUsing transfer learning on MobileNetV2, an accuracy of ~98% was reached for blind spot detection with an average prediction time of 0.09s on the Raspberry Pi 4 without any machine learning accelerators. Given an ML accelerator such as the [Google Coral USB Accelerator](https://coral.ai/products/accelerator/), it would likely reach prediction times of 0.0026s (2.6ms, [source](https://coral.ai/docs/edgetpu/benchmarks/)).\n\n## Demo Video\nWant to skip straight into the details? Check out [this video](https://youtu.be/gVqHdGIRrTY) demoing the machine learning algorithm.\n\n[![Demo Video](https://i.imgur.com/ZLRfkQ5.png)](https://youtu.be/gVqHdGIRrTY)\n\n## License\nThis project is under the GNU General Public License, version 3. More info is available in [LICENSE](/LICENSE)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faritrosaha10%2Fblindspotdetection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faritrosaha10%2Fblindspotdetection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faritrosaha10%2Fblindspotdetection/lists"}