The example of running Pose Estimation using Core ML
Branch: master
Clone or download
Latest commit 962b84e Feb 9, 2019

README.md

PoseEstimation-CoreML

This project is Pose Estimation on iOS with Core ML.
If you are interested in iOS + Machine Learning, visit here you can see various DEMOs.

Jointed Keypoints Concatenated heatmap
poseestimation-demo-joint.gif poseestimation-demo-heatmap.gif

한국어 README

How it works

how_it_works

Video source: https://www.youtube.com/watch?v=EM16LBKBEgI

Requirements

  • Xcode 9.2+
  • iOS 11.0+
  • Swift 4.1

Download model

Get PoseEstimationForMobile's model

Pose Estimation model for Core ML(model_cpm.mlmodel)
☞ Download Core ML model model_cpm.mlmodel or hourglass.mlmodel.

input_name_shape_dict = {"image:0":[1,192,192,3]} image_input_names=["image:0"]
output_feature_names = ['Convolutional_Pose_Machine/stage_5_out:0']

-in https://github.com/edvardHua/PoseEstimationForMobile

Matadata

cpm hourglass
Input shape [1, 192, 192, 3] [1, 192, 192, 3]
Output shape [1, 96, 96, 14] [1, 48, 48, 14]
Input node name image image
Output node name Convolutional_Pose_Machine/stage_5_out hourglass_out_3
Model size 2.6 MB 2.0 MB

Inference Time

cpm hourglass
iPhone X 51 ms 49 ms
iPhone 8+ 49 ms 46 ms
iPhone 6+ 200 ms 180 ms

Get your own model

Or you can use your own PoseEstimation model

Build & Run

1. Prerequisites

1.1 Import pose estimation model

모델 불러오기.png

Once you import the model, compiler generates model helper class on build path automatically. You can access the model through model helper class by creating an instance, not through build path.

1.2 Add permission in info.plist for device's camera access

prerequest_001_plist

2. Dependencies

No external library yet.

3. Code

3.1 Import Vision framework

import Vision

3.2 Define properties for Core ML

// properties on ViewController
typealias EstimationModel = model_cpm // model name(model_cpm) must be equal with mlmodel file name
var request: VNCoreMLRequest!
var visionModel: VNCoreMLModel!

3.3 Configure and prepare the model

override func viewDidLoad() {
    super.viewDidLoad()

    visionModel = try? VNCoreMLModel(for: EstimationModel().model)
	request = VNCoreMLRequest(model: visionModel, completionHandler: visionRequestDidComplete)
	request.imageCropAndScaleOption = .scaleFill
}

func visionRequestDidComplete(request: VNRequest, error: Error?) { 
    /* ------------------------------------------------------ */
    /* something postprocessing what you want after inference */
    /* ------------------------------------------------------ */
}

3.4 Inference 🏃‍♂️

// on the inference point
let handler = VNImageRequestHandler(cvPixelBuffer: pixelBuffer)
try? handler.perform([request])

Performance Test

1. Import the model

You can download cpm or hourglass model for Core ML from edvardHua/PoseEstimationForMobile repo.

2. Fix the model name on PoseEstimation_CoreMLTests.swift

fix-model-name-for-testing

3. Run the test

Hit the ⌘ + U or click the Build for Testing icon.

build-for-testing

See also