{"id":19601632,"url":"https://github.com/alankrantas/tf-lite-python-object-objection","last_synced_at":"2025-04-27T17:32:03.053Z","repository":{"id":59318498,"uuid":"536627368","full_name":"alankrantas/TF-Lite-Python-Object-Objection","owner":"alankrantas","description":"Object detection examples using pre-trained models on Tensorflow Lite and OpenCV","archived":false,"fork":false,"pushed_at":"2023-07-11T20:32:39.000Z","size":14132,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2023-07-11T21:30:26.700Z","etag":null,"topics":["deep-learning","efficientdet-lite","image-classification","image-recognition","object-detection","opencv","opencv-python","python","ssd-mobilenet","yolo","yolov5"],"latest_commit_sha":null,"homepage":"","language":"Python","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/alankrantas.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}},"created_at":"2022-09-14T14:50:19.000Z","updated_at":"2023-07-11T21:30:26.701Z","dependencies_parsed_at":"2022-09-24T04:30:45.070Z","dependency_job_id":null,"html_url":"https://github.com/alankrantas/TF-Lite-Python-Object-Objection","commit_stats":null,"previous_names":[],"tags_count":0,"template":null,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alankrantas%2FTF-Lite-Python-Object-Objection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alankrantas%2FTF-Lite-Python-Object-Objection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alankrantas%2FTF-Lite-Python-Object-Objection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alankrantas%2FTF-Lite-Python-Object-Objection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alankrantas","download_url":"https://codeload.github.com/alankrantas/TF-Lite-Python-Object-Objection/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224076433,"owners_count":17251756,"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":["deep-learning","efficientdet-lite","image-classification","image-recognition","object-detection","opencv","opencv-python","python","ssd-mobilenet","yolo","yolov5"],"created_at":"2024-11-11T09:19:16.264Z","updated_at":"2024-11-11T09:19:17.522Z","avatar_url":"https://github.com/alankrantas.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Object Detection Examples With Tensorflow Lite and OpenCV (Python)\n\nRunning pre-trained TF Lite models for object detection. You either have to install Tehsorflow or Tensorflow Lite (```tflite_runtime```) and OpenCV (```opencv-python```). These scripts also run a lot faster on a ARM device, for example, a Raspberry Pi 3B or 4B.\n\nThere are three models available here (downloaded from Google):\n\n* SSD-MobileNet V1\n* EfficientDet-Lite0\n* YOLO V5\n\nAll three are trained with the COCO dataset (```labelmap.txt``` is the label list). This is mainly a demostration of how to get the possible things as well as their location from the model.\n\n![result](https://github.com/alankrantas/TF-Lite-Python-Object-Objection/blob/main/result.jpg)\n\n```TF_Lite_Object_Detection.py``` can use either SSD or EfficientNet to process a still image, and ```TF_Lite_Object_Detection_Yolo.py``` is the YOLO version. ```TF_Lite_Object_Detection_Live.py``` use live USB cam images with SSD or EfficientNet (press ```q```).\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falankrantas%2Ftf-lite-python-object-objection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falankrantas%2Ftf-lite-python-object-objection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falankrantas%2Ftf-lite-python-object-objection/lists"}