Simple containerized REST API extracting (and draw) CMU OpenPose (human pose) key-points from images (provided as file or url). This version is GPU accelerated, using CUDA (10.0) and CuDNN (7.5) compatible hardware.
Example output image:
Example output JSON:
{
"people": [
{
"gender": null,
"age": null,
"pose": {
"nose": {
"x": 0.677286639221095,
"y": 0.18542898178100586,
"confidence": 0.9316593408584595
},
"neck": {
"x": 0.6110341823873173,
"y": 0.2352118682861328,
"confidence": 0.8109888434410095
},
"right_shoulder": {
"x": 0.5725101031021672,
"y": 0.21583173751831056,
"confidence": 0.8107086420059204
},
"right_elbow": {
"x": 0.6039714120198953,
"y": 0.1578795051574707,
"confidence": 0.6835763454437256
},
"right_wrist": {
"x": 0.6284193668696929,
"y": 0.11647865295410156,
"confidence": 0.8801245093345642
},
"left_shoulder": {
"x": 0.6563097334586049,
"y": 0.2572347831726074,
"confidence": 0.8132572770118713
},
"left_elbow": {
"x": 0.7887055937901116,
"y": 0.30966285705566404,
"confidence": 0.790416419506073
},
"left_wrist": {
"x": 0.9037675179576422,
"y": 0.317821159362793,
"confidence": 0.8730279207229614
},
"mid_hip": {
"x": 0.548264248864534,
"y": 0.4061676788330078,
"confidence": 0.7308455109596252
},
"right_hip": {
"x": 0.5203646257590343,
"y": 0.4062485122680664,
"confidence": 0.6943361759185791
},
"right_knee": {
"x": 0.6144056757102834,
"y": 0.5027524185180664,
"confidence": 0.7306333780288696
},
"right_ankle": {
"x": 0.7574588721397364,
"y": 0.4474960708618164,
"confidence": 0.7879128456115723
},
"left_hip": {
"x": 0.5761545190313981,
"y": 0.40345027923583987,
"confidence": 0.6901074647903442
},
"left_knee": {
"x": 0.6354786660433945,
"y": 0.5662445831298828,
"confidence": 0.819564163684845
},
"left_ankle": {
"x": 0.7363890637342022,
"y": 0.693160400390625,
"confidence": 0.7974473237991333
},
"right_eye": {
"x": 0.6599168340553416,
"y": 0.16619421005249024,
"confidence": 0.9014793038368225
},
"left_eye": {
"x": 0.6877881572898153,
"y": 0.18274955749511718,
"confidence": 0.8851550817489624
},
"right_ear": {
"x": 0.6248565722039149,
"y": 0.1688811492919922,
"confidence": 0.889176070690155
},
"left_ear": {
"x": 0.6843981027226501,
"y": 0.2075032615661621,
"confidence": 0.16915567219257355
},
"left_bigtoe": {
"x": 0.7645028884188636,
"y": 0.7538619995117187,
"confidence": 0.7830573320388794
},
"left_smalltoe": {
"x": 0.7714290287445695,
"y": 0.7400554656982422,
"confidence": 0.7159634232521057
},
"left_heel": {
"x": 0.7401083513835407,
"y": 0.6986153411865235,
"confidence": 0.5403489470481873
},
"right_bigtoe": {
"x": 0.8237912146401066,
"y": 0.40610370635986326,
"confidence": 0.6505764722824097
},
"right_smalltoe": {
"x": 0.820223213183748,
"y": 0.4144353103637695,
"confidence": 0.6157740354537964
},
"right_heel": {
"x": 0.7644432031712826,
"y": 0.4338855361938477,
"confidence": 0.5651904344558716
}
}
},
{
"gender": null,
"age": null,
"pose": {
"nose": {
"x": 0.3215829327961468,
"y": 0.25453336715698244,
"confidence": 0.9654165506362915
},
"neck": {
"x": 0.26596107904756616,
"y": 0.3178150177001953,
"confidence": 0.928391695022583
},
"right_shoulder": {
"x": 0.21012789227574546,
"y": 0.2929931831359863,
"confidence": 0.8403418064117432
},
"right_elbow": {
"x": 0.11937395430289173,
"y": 0.2488512420654297,
"confidence": 0.8523696064949036
},
"right_wrist": {
"x": 0.039153621848348946,
"y": 0.2793436050415039,
"confidence": 0.8333181738853455
},
"left_shoulder": {
"x": 0.32853139482591576,
"y": 0.3400200653076172,
"confidence": 0.8353562355041504
},
"left_elbow": {
"x": 0.436659633642501,
"y": 0.38402713775634767,
"confidence": 0.8656612634658813
},
"left_wrist": {
"x": 0.5097585379794876,
"y": 0.3427619552612305,
"confidence": 0.5537052154541016
},
"mid_hip": {
"x": 0.23780097177996642,
"y": 0.5165453720092773,
"confidence": 0.7827401161193848
},
"right_hip": {
"x": 0.20298176504801047,
"y": 0.5164376831054688,
"confidence": 0.7337585687637329
},
"right_knee": {
"x": 0.08450797082500247,
"y": 0.6049499893188477,
"confidence": 0.8458415269851685
},
"right_ankle": {
"x": 0.09507068676217849,
"y": 0.7538065338134765,
"confidence": 0.8094685673713684
},
"left_hip": {
"x": 0.26935891969509035,
"y": 0.5192223739624023,
"confidence": 0.729832112789154
},
"left_knee": {
"x": 0.3808291707935303,
"y": 0.6462666320800782,
"confidence": 0.8145111799240112
},
"left_ankle": {
"x": 0.5167471597921603,
"y": 0.7565208435058594,
"confidence": 0.7894134521484375
},
"right_eye": {
"x": 0.3180591167431872,
"y": 0.24611305236816405,
"confidence": 0.9129397869110107
},
"left_eye": {
"x": 0.3425561263097971,
"y": 0.25456857681274414,
"confidence": 0.900324285030365
},
"right_ear": {
"x": 0.2763218209265156,
"y": 0.2516548347473144,
"confidence": 0.8345515131950378
},
"left_ear": {
"x": 0.342515171044999,
"y": 0.2793706512451172,
"confidence": 0.37775322794914246
},
"left_bigtoe": {
"x": 0.5343347823638674,
"y": 0.8062393951416016,
"confidence": 0.7804844975471497
},
"left_smalltoe": {
"x": 0.5483272606727636,
"y": 0.795229721069336,
"confidence": 0.7149602770805359
},
"left_heel": {
"x": 0.5238838858702359,
"y": 0.7592790985107422,
"confidence": 0.6040292978286743
},
"right_bigtoe": {
"x": 0.03924421036224606,
"y": 0.80625732421875,
"confidence": 0.7193943858146667
},
"right_smalltoe": {
"x": 0.03901440950366558,
"y": 0.7952497100830078,
"confidence": 0.6273979544639587
},
"right_heel": {
"x": 0.11242936120779029,
"y": 0.7620455932617187,
"confidence": 0.8011491894721985
}
}
}
],
"vehicles": [],
"things": []
}
Other container orchestration software, like Kubernetes may also be used, but Docker is the easiest.
- Nvidia GPU and drivers on the Host.
- Docker
- Nvidia Docker Runtime
- docker-compose
git clone https://github.com/lyngon/openpose-api.git
cd openpose-api
docker-compose up -d
In a browser visit http://localhost:8080/docs. Assuming the browser is running on the same machine.
If everything worked, you should see an interactive Swagger documentation wehere you can try out the API.
- Generalize to also run on CPU
- Kubernetes example