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.

한국어 README

How it works

Requirements

• Xcode 9.2+
• iOS 11.0+
• Swift 4.1

Download 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":[1,224,224,3]} image_input_names=["image:0"]
output_feature_names = ['Convolutional_Pose_Machine/stage_5_out:0']

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

	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
Inference time on iPhone X	57 mm	33 mm

Build & Run

1. Prerequisites

1.1 Import pose estimation model

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

2. Dependencies

No external library yet.

3. Code

(Ready to publish)

See also

• motlabs/iOS-Proejcts-with-ML-Models
  : The challenge using machine learning model created from tensorflow on iOS
• edvardHua/PoseEstimationForMobile
  : TensorFlow project for pose estimation for mobile