{"id":24098468,"url":"https://github.com/matlab-deep-learning/pretrained-yolox-network-for-object-detection","last_synced_at":"2025-07-20T05:33:37.838Z","repository":{"id":44924531,"uuid":"513138530","full_name":"matlab-deep-learning/Pretrained-YOLOX-Network-For-Object-Detection","owner":"matlab-deep-learning","description":"YOLOX inference in MATLAB for Object Detection with yolox_s, yolox_m \u0026 yolox_l networks","archived":false,"fork":false,"pushed_at":"2024-02-01T12:54:20.000Z","size":290,"stargazers_count":27,"open_issues_count":0,"forks_count":1,"subscribers_count":6,"default_branch":"main","last_synced_at":"2025-05-07T19:47:41.303Z","etag":null,"topics":["computer-vision","deep-learning","image-processing","matlab","matlab-deep-learning","object-detection","pretrained-models","yolo","yolox-models"],"latest_commit_sha":null,"homepage":"https://www.mathworks.com/help/vision/ug/getting-started-with-object-detection-using-deep-learning.html","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/matlab-deep-learning.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":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2022-07-12T12:44:52.000Z","updated_at":"2025-03-09T04:00:08.000Z","dependencies_parsed_at":"2023-11-07T12:26:36.691Z","dependency_job_id":"eeb86290-46ad-4947-b891-876710a28a6a","html_url":"https://github.com/matlab-deep-learning/Pretrained-YOLOX-Network-For-Object-Detection","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/matlab-deep-learning/Pretrained-YOLOX-Network-For-Object-Detection","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matlab-deep-learning%2FPretrained-YOLOX-Network-For-Object-Detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matlab-deep-learning%2FPretrained-YOLOX-Network-For-Object-Detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matlab-deep-learning%2FPretrained-YOLOX-Network-For-Object-Detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matlab-deep-learning%2FPretrained-YOLOX-Network-For-Object-Detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/matlab-deep-learning","download_url":"https://codeload.github.com/matlab-deep-learning/Pretrained-YOLOX-Network-For-Object-Detection/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matlab-deep-learning%2FPretrained-YOLOX-Network-For-Object-Detection/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266071519,"owners_count":23871940,"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":["computer-vision","deep-learning","image-processing","matlab","matlab-deep-learning","object-detection","pretrained-models","yolo","yolox-models"],"created_at":"2025-01-10T14:46:07.702Z","updated_at":"2025-07-20T05:33:37.797Z","avatar_url":"https://github.com/matlab-deep-learning.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Pretrained YOLOX Network For Object Detection\n\nThis repository provides multiple pretrained YOLOX [1] object detection networks for MATLAB®, trained on the COCO 2017[2] dataset. These object detectors can detect 80 different object categories including [person, car, traffic light, etc](/src/%2Bhelper/getCOCOClasess.m). [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=matlab-deep-learning/Pretrained-YOLOX-Network-For-Object-Detection)\n\n**Creator**: MathWorks Development\n\n\n## Requirements\n- MATLAB® R2023b or later\n- Deep Learning Toolbox™\n- Computer Vision Toolbox™\n- Computer Vision Toolbox™ Automated Visual Inspection Library\n\nNote: Previous MATLAB® release users can use [this](https://github.com/matlab-deep-learning/Pretrained-YOLOX-Network-For-Object-Detection/tree/previous) branch to download the pretrained models.\n\n\n## Getting Started\n[Getting Started with YOLOX for Object Detection](https://in.mathworks.com/help/vision/ug/getting-started-with-yolox-object-detection.html)\n\n\n### Detect Objects Using Pretrained YoloX\nUse to code below to perform detection on an example image using the pretrained model.\n\nNote: This functionality requires Deep Learning Toolbox™ and the Computer Vision Toolbox™ Automated Visual Inspection Library. You can install the Computer Vision Toolbox Automated Visual Inspection Library from Add-On Explorer. For more information about installing add-ons, see [Get and Manage Add-Ons](https://in.mathworks.com/help/matlab/matlab_env/get-add-ons.html).\n\n```matlab\n% Read test image.\nimg = imread(fullfile(\"data\", \"inputTeam.jpg\"));\n\n% Create a yoloxobjectdetector object to configure a pretrained YOLOX network with a CSP-DarkNet-53 backbone as the feature extractor.\ndetector = yoloxObjectDetector(\"small-coco\");\n\n% Perform detection using pretrained model.\n[bboxes,scores,labels] = detect(detector,I);\n\n% Visualize results.\nannotations = string(labels) + \": \" + (round(100*scores)) + \"%\";\nimg = insertObjectAnnotation(img, \"rectangle\", bboxes, annotations);\nfigure, imshow(img);\n```\n![Results](/data/results.jpg)\n\n### Train YOLOX Network and Perform Transfer Learning\nTo train a YOLOX object detection network on a labeled data set, use the [trainYOLOXObjectDetector](https://in.mathworks.com/help/vision/ref/trainyoloxobjectdetector.html) function. You must specify the class names for the data set you use to train the network. Then, train an untrained or pretrained network by using the [trainYOLOXObjectDetector](https://in.mathworks.com/help/vision/ref/trainyoloxobjectdetector.html) function. The training function returns the trained network as a [yoloxObjectDetector](https://in.mathworks.com/help/vision/ref/yoloxobjectdetector.html) object.\n\nTo learn how to configure and train a YOLOX object detector for transfer learning to detect small objects, see the [Detect Defects on Printed Circuit Boards Using YOLOX Network](https://in.mathworks.com/help/vision/ug/detect-pcb-defects-using-yolox-deep-learning.html) example.\n\n\n## Network Details\nYOLOX is one of the best performing object detectors and is considered as an improvement to the existing YOLO variants such as YOLO v4, and YOLO v5.\n![YOLOX architecture](/data/yolox_arch.png)\n\n\n## References\n[1] Ge, Zheng, Songtao Liu, Feng Wang, Zeming Li, and Jian Sun. \"Yolox: Exceeding yolo series in 2021.\" arXiv preprint arXiv:2107.08430 (2021).\n\n[2] Lin, T., et al. \"Microsoft COCO: Common objects in context. arXiv 2014.\" arXiv preprint arXiv:1405.0312 (2014).\n\n\nCopyright 2022 - 2024 The MathWorks, Inc.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmatlab-deep-learning%2Fpretrained-yolox-network-for-object-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmatlab-deep-learning%2Fpretrained-yolox-network-for-object-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmatlab-deep-learning%2Fpretrained-yolox-network-for-object-detection/lists"}