{"id":13699639,"url":"https://github.com/jing-interactive/DancingGaga","last_synced_at":"2025-05-04T16:35:27.702Z","repository":{"id":139898789,"uuid":"138369523","full_name":"jing-interactive/DancingGaga","owner":"jing-interactive","description":"AI 尬舞机","archived":false,"fork":false,"pushed_at":"2019-06-20T09:33:48.000Z","size":4186,"stargazers_count":310,"open_issues_count":1,"forks_count":50,"subscribers_count":23,"default_branch":"master","last_synced_at":"2024-11-13T05:36:01.811Z","etag":null,"topics":["deep-learning","deep-neural-networks","inference","openpose"],"latest_commit_sha":null,"homepage":"","language":"C++","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/jing-interactive.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}},"created_at":"2018-06-23T03:54:55.000Z","updated_at":"2024-11-06T09:44:04.000Z","dependencies_parsed_at":null,"dependency_job_id":"deb56fe4-5499-46bc-b132-8c13e58f9ad2","html_url":"https://github.com/jing-interactive/DancingGaga","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/jing-interactive%2FDancingGaga","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jing-interactive%2FDancingGaga/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jing-interactive%2FDancingGaga/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jing-interactive%2FDancingGaga/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jing-interactive","download_url":"https://codeload.github.com/jing-interactive/DancingGaga/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252366680,"owners_count":21736620,"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","deep-neural-networks","inference","openpose"],"created_at":"2024-08-02T20:00:39.427Z","updated_at":"2025-05-04T16:35:26.952Z","avatar_url":"https://github.com/jing-interactive.png","language":"C++","funding_links":[],"categories":["C++"],"sub_categories":[],"readme":"# DancingGaga\n[Openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose\n) implementation using darknet framework, originated from [openpose-darknet](https://github.com/lincolnhard/openpose-darknet)\n\n# Result\n\n![demo](https://raw.githubusercontent.com/jing-interactive/DancingGaga/master/doc/gaga1.gif)\n\n# Steps to build from Visual Studio 2015\n\n- First you need to build [lightnet](https://github.com/jing-vision/lightnet)\n  - `git clone --recurse-submodules https://github.com/jing-vision/lightnet.git`\n  - Follow [lightnet's building steps](https://github.com/jing-vision/lightnet#how-to-build-from-visual-studio-2015)\n- Then you need to have [premake](https://premake.github.io/download.html) installed and execute `DancingGaga/gen-vs2015.bat` to generate `DancingGaga/vs2015` folder\n- You can find `DancingGaga/vs2015/DancingGaga.sln`, you should be able to build it w/o errors. (If you are lucky like me.)\n\n\n# Steps to run\n\n- Download [weight file](https://drive.google.com/open?id=1BfY0Hx2d2nm3I4JFh0W1cK2aHD1FSGea) and copy it as `bin/openpose.weight`\n  \n- Usage\n```\nDancingGaga.exe -cfg=[openpose.cfg] -weights=[openpose.weight] media-source\n```\ne.g you can detect pose from a video\n```\nDancingGaga.exe pickme-101.mp4\n```\nOr from an image\n```\nDancingGaga.exe person.jpg\n```\nOr even from your default camera (index #0)\n```\nDancingGaga.exe 0\n```\n- Other network models\n```\nDancingGaga.exe -cfg=..\\coco.cfg -weights=..\\coco.weights person.jpg\nDancingGaga.exe -cfg=..\\mpi.cfg -weights=..\\mpi.weights person.jpg\nDancingGaga.exe -cfg=..\\body_25.cfg -weights=..\\body_25.weights person.jpg\n```\n# network layout\n\n```\nlayer     filters    size              input                output\n   0 conv     64  3 x 3 / 1   200 x 200 x   3   -\u003e   200 x 200 x  64 0.138 BF\n   1 conv     64  3 x 3 / 1   200 x 200 x  64   -\u003e   200 x 200 x  64 2.949 BF\n   2 max          2 x 2 / 2   200 x 200 x  64   -\u003e   100 x 100 x  64 0.003 BF\n   3 conv    128  3 x 3 / 1   100 x 100 x  64   -\u003e   100 x 100 x 128 1.475 BF\n   4 conv    128  3 x 3 / 1   100 x 100 x 128   -\u003e   100 x 100 x 128 2.949 BF\n   5 max          2 x 2 / 2   100 x 100 x 128   -\u003e    50 x  50 x 128 0.001 BF\n   6 conv    256  3 x 3 / 1    50 x  50 x 128   -\u003e    50 x  50 x 256 1.475 BF\n   7 conv    256  3 x 3 / 1    50 x  50 x 256   -\u003e    50 x  50 x 256 2.949 BF\n   8 conv    256  3 x 3 / 1    50 x  50 x 256   -\u003e    50 x  50 x 256 2.949 BF\n   9 conv    256  3 x 3 / 1    50 x  50 x 256   -\u003e    50 x  50 x 256 2.949 BF\n  10 max          2 x 2 / 2    50 x  50 x 256   -\u003e    25 x  25 x 256 0.001 BF\n  11 conv    512  3 x 3 / 1    25 x  25 x 256   -\u003e    25 x  25 x 512 1.475 BF\n  12 conv    512  3 x 3 / 1    25 x  25 x 512   -\u003e    25 x  25 x 512 2.949 BF\n  13 conv    256  3 x 3 / 1    25 x  25 x 512   -\u003e    25 x  25 x 256 1.475 BF\n  14 conv    128  3 x 3 / 1    25 x  25 x 256   -\u003e    25 x  25 x 128 0.369 BF\n  15 conv    128  3 x 3 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.184 BF\n  16 conv    128  3 x 3 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.184 BF\n  17 conv    128  3 x 3 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.184 BF\n  18 conv    512  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 512 0.082 BF\n  19 conv     38  1 x 1 / 1    25 x  25 x 512   -\u003e    25 x  25 x  38 0.024 BF\n  20 route  14\n  21 conv    128  3 x 3 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.184 BF\n  22 conv    128  3 x 3 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.184 BF\n  23 conv    128  3 x 3 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.184 BF\n  24 conv    512  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 512 0.082 BF\n  25 conv     19  1 x 1 / 1    25 x  25 x 512   -\u003e    25 x  25 x  19 0.012 BF\n  26 route  19 25 14\n  27 conv    128  7 x 7 / 1    25 x  25 x 185   -\u003e    25 x  25 x 128 1.450 BF\n  28 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  29 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  30 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  31 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  32 conv    128  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.020 BF\n  33 conv     38  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x  38 0.006 BF\n  34 route  26\n  35 conv    128  7 x 7 / 1    25 x  25 x 185   -\u003e    25 x  25 x 128 1.450 BF\n  36 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  37 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  38 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  39 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  40 conv    128  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.020 BF\n  41 conv     19  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x  19 0.003 BF\n  42 route  33 41 14\n  43 conv    128  7 x 7 / 1    25 x  25 x 185   -\u003e    25 x  25 x 128 1.450 BF\n  44 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  45 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  46 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  47 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  48 conv    128  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.020 BF\n  49 conv     38  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x  38 0.006 BF\n  50 route  42\n  51 conv    128  7 x 7 / 1    25 x  25 x 185   -\u003e    25 x  25 x 128 1.450 BF\n  52 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  53 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  54 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  55 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  56 conv    128  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.020 BF\n  57 conv     19  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x  19 0.003 BF\n  58 route  49 57 14\n  59 conv    128  7 x 7 / 1    25 x  25 x 185   -\u003e    25 x  25 x 128 1.450 BF\n  60 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  61 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  62 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  63 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  64 conv    128  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.020 BF\n  65 conv     38  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x  38 0.006 BF\n  66 route  58\n  67 conv    128  7 x 7 / 1    25 x  25 x 185   -\u003e    25 x  25 x 128 1.450 BF\n  68 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  69 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  70 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  71 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  72 conv    128  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.020 BF\n  73 conv     19  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x  19 0.003 BF\n  74 route  65 73 14\n  75 conv    128  7 x 7 / 1    25 x  25 x 185   -\u003e    25 x  25 x 128 1.450 BF\n  76 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  77 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  78 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  79 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  80 conv    128  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.020 BF\n  81 conv     38  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x  38 0.006 BF\n  82 route  74\n  83 conv    128  7 x 7 / 1    25 x  25 x 185   -\u003e    25 x  25 x 128 1.450 BF\n  84 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  85 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  86 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  87 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  88 conv    128  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.020 BF\n  89 conv     19  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x  19 0.003 BF\n  90 route  81 89 14\n  91 conv    128  7 x 7 / 1    25 x  25 x 185   -\u003e    25 x  25 x 128 1.450 BF\n  92 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  93 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  94 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  95 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n  96 conv    128  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.020 BF\n  97 conv     38  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x  38 0.006 BF\n  98 route  90\n  99 conv    128  7 x 7 / 1    25 x  25 x 185   -\u003e    25 x  25 x 128 1.450 BF\n 100 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n 101 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n 102 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n 103 conv    128  7 x 7 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 1.004 BF\n 104 conv    128  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x 128 0.020 BF\n 105 conv     19  1 x 1 / 1    25 x  25 x 128   -\u003e    25 x  25 x  19 0.003 BF\n 106 route  105 97\n```\n\n# Note\n\n1. Darknet version openpose.cfg and openpose.weight are ported from COCO version \n\n  [pose_deploy_linevec.prototxt](https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation/tree/master/model/_trained_COCO) and [pose_iter_440000.caffemodel](  http://posefs1.perception.cs.cmu.edu/Users/ZheCao/pose_iter_440000.caffemodel).\n\n2. You could change net input width, height in openpose.cfg.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjing-interactive%2FDancingGaga","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjing-interactive%2FDancingGaga","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjing-interactive%2FDancingGaga/lists"}