{"id":13618855,"url":"https://github.com/ajithvcoder/Custom_Objectdetection_Yolov5","last_synced_at":"2025-04-14T15:33:39.287Z","repository":{"id":111986744,"uuid":"389102281","full_name":"ajithvcoder/Custom_Objectdetection_Yolov5","owner":"ajithvcoder","description":"Contains code to train custom images on Yolov5","archived":false,"fork":false,"pushed_at":"2021-07-24T13:15:27.000Z","size":5029,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-05-22T03:08:01.014Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/ajithvcoder.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}},"created_at":"2021-07-24T13:10:40.000Z","updated_at":"2021-07-24T13:15:29.000Z","dependencies_parsed_at":"2023-09-09T21:00:38.659Z","dependency_job_id":null,"html_url":"https://github.com/ajithvcoder/Custom_Objectdetection_Yolov5","commit_stats":null,"previous_names":["ajithvcoder/custom_objectdetection_yolov5"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajithvcoder%2FCustom_Objectdetection_Yolov5","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajithvcoder%2FCustom_Objectdetection_Yolov5/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajithvcoder%2FCustom_Objectdetection_Yolov5/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajithvcoder%2FCustom_Objectdetection_Yolov5/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ajithvcoder","download_url":"https://codeload.github.com/ajithvcoder/Custom_Objectdetection_Yolov5/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248173813,"owners_count":21059594,"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":[],"created_at":"2024-08-01T21:00:31.427Z","updated_at":"2025-04-14T15:33:37.180Z","avatar_url":"https://github.com/ajithvcoder.png","language":"Jupyter Notebook","funding_links":[],"categories":["Uncategorized"],"sub_categories":["Uncategorized"],"readme":"### YoloV5 Custom Object training\n\nColab notebook - [here](https://colab.research.google.com/drive/1CGXHcgIS9Gv7QXtFdgdHL13Wy3k4Vdg3?usp=sharing)\n\nit is also available [here](./Custom_YOLOv5_Training_Tutorial.ipynb)\n\n**Steps for training**\n\n**Data preparation**\n- You can refer customim.zip file for data preparation\n- Download 30 images of two classes - 15 images for car and 15 images for flight\n- You can go to this site https://www.makesense.ai/ and upload all images\n- Now you can give the label names and then start annotation\n- click Actions--\u003eExport annotations\n\n1) In colab notbook do the setup\n2) Upload data(customim.zip)(avaliable in this repo)/ custom data to colab and place it in \"datasets\" folder. Make like below tree structure\n\n```\n# Tree structure\ndatasets \n        ----\u003ecustomim\n                        ---\u003eimages\n                                  --\u003etrain\n                                          --\u003e001.jpg\n                                          --\u003e002.jpg\n                                          ...\n                        ---\u003elabels\n                                  --\u003etrain\n                                          --\u003e001.txt\n                                          --\u003e002.txt\n                                          ...\n```\n\n3) Modify coco128.yaml file like below with path of custom dataset , number of classes and class names\n\n**coco128.yaml**\n```\n\n# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]\npath: ../datasets/customim  # dataset root dir\ntrain: images/train  # train images (relative to 'path') 128 images\nval: images/train  # val images (relative to 'path') 128 images\ntest:  # test images (optional)\n\n# Classes\nnc: 2  # number of classes\nnames: [ 'car','flight' ]  # class names\n\n\n```\n\n4) you can run the cell to train for 200 epochs\n5) Upload the [test images](./test.zip) or your own test images to colab\n5) Now you can provide the path of weights and test images to detect.py \n\n```\n!python detect.py --weights runs/train/exp5/weights/last.pt --img 640 --conf 0.25 --source test/\n```\n\n#### Results\n\n![img1](assets/001.jpg)\n![img1](assets/002.jpg)\n![img1](assets/003.jpg)\n![img1](assets/004.jpg)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fajithvcoder%2FCustom_Objectdetection_Yolov5","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fajithvcoder%2FCustom_Objectdetection_Yolov5","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fajithvcoder%2FCustom_Objectdetection_Yolov5/lists"}