Detect Hair Color

Introduction

Our hair is a salient element of our overall appearance and plays a key role in facial analysis. Accurate detection and segmentation of the hair region under unconstrained conditions remains challenging for the following reasons:

• Poor lighting conditions
• Crowded background
• Hairstyle and color variations

The segmentation of the hair region provides cues during the face recognition process and is valuable to many domains like:

• Augmented reality applications, such as hair modeling.
• Biometric recognition applications, such as detecting the presence of a human when their back is turned to the camera.

Objective

This lesson will explore how to exploit a pretrained ONNX model for hair segmentation. We’ll develop a Python utility that detects the color of the segmented hair region.

Dependencies

We’ll be using the following external Python libraries.

Let’s code this utility!

Before exploring the core functions of this utility, let’s get introduced to ONNX. ONNX is an open standard format for neural network model interoperability. It allows the transfer of heavy, trained neural networks from one training tool to another ...