{"id":20291542,"url":"https://github.com/edisonslightbulbs/ptod-model-training","last_synced_at":"2026-04-15T14:07:18.543Z","repository":{"id":118368943,"uuid":"402410888","full_name":"edisonslightbulbs/PTOD-model-training","owner":"edisonslightbulbs","description":"Transfer learning using PyTorch and YOLOv5","archived":false,"fork":false,"pushed_at":"2022-03-19T18:02:05.000Z","size":16117,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-01-14T09:12:14.943Z","etag":null,"topics":["cxx11","deep-learning","k4a","object-detection","opencv","python","pytorch","transfer-learning","yolov5"],"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/edisonslightbulbs.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":"2021-09-02T12:24:14.000Z","updated_at":"2023-11-01T19:10:55.000Z","dependencies_parsed_at":null,"dependency_job_id":"432f01e1-f9f9-403b-bc14-eb3b87a1fa44","html_url":"https://github.com/edisonslightbulbs/PTOD-model-training","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/edisonslightbulbs%2FPTOD-model-training","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/edisonslightbulbs%2FPTOD-model-training/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/edisonslightbulbs%2FPTOD-model-training/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/edisonslightbulbs%2FPTOD-model-training/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/edisonslightbulbs","download_url":"https://codeload.github.com/edisonslightbulbs/PTOD-model-training/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241787486,"owners_count":20020101,"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":["cxx11","deep-learning","k4a","object-detection","opencv","python","pytorch","transfer-learning","yolov5"],"created_at":"2024-11-14T15:12:51.337Z","updated_at":"2026-04-15T14:07:18.504Z","avatar_url":"https://github.com/edisonslightbulbs.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Transfer learning using PyTorch's object detection API\n\n\n|   Platform |   Hardware\t|  Dependencies \t|\n|---\t|---\t|---\t|\n|   :white_square_button: Linux\t|   :white_square_button: Azure Kinect \t| :white_square_button: [ gflags](https://github.com/gflags/gflags)\t|\n|| |  :white_square_button: [ glog ](https://github.com/google/glog)  \t|\n||| :white_square_button:  [ Azure Kinect SDK ](https://github.com/microsoft/Azure-Kinect-Sensor-SDK) |\n||| :white_square_button:  [ opencv ](https://github.com/opencv/opencv) |\n||| :white_square_button:  [ Anaconda ](https://www.anaconda.com/products/individual) |\n||| :white_square_button:  [ Yolov5 ](https://github.com/ultralytics/yolov5) |\n||| :white_square_button:  [ Image annotation tool ](https://github.com/tzutalin/labelImg) |\n\n---\n\nThis project is made up of two sub-projects:  [`image-capturing`](./image-capturing) [`model-training`](./model-training).  [`image-capturing`](./image-capturing) is a CMake project that uses Microsoft's Azure Kinect to capture so-called depth color images (of cause, this can be changed). [`model-training`](./model-training) uses shell and python scripts to exploit Tensor Flow's object detection API and train an object detection.\n\n---\n\nThe notebooks in [`model-training README.md`](./model-training/README.md) are self-documenting, but more on that in the [`model-training README.md`](./model-training/README.md). In principle, one can use any other camera, a webcam, or even already captured images (i.e., given a reasonable number of image captures exist) to train the detection model.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fedisonslightbulbs%2Fptod-model-training","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fedisonslightbulbs%2Fptod-model-training","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fedisonslightbulbs%2Fptod-model-training/lists"}