Palm Recognition SDK

Code

GitHub - Faceplugin-ltd/Palm-Recognition: The worlds's 1st free and open source palm recognition SDK for Windows and Linux (Palm detection, ROI extraction, Template extraction, Template mathcing)GitHub

Overview

World's First Palm Recognition SDK for Any RGB Camera – On-Premise, Real-Time, and High Accuracy

Introducing the world’s first Palm Recognition SDK that works seamlessly with images captured by any standard RGB camera. Designed for developers, this powerful SDK enables easy integration of real-time, high-accuracy palm recognition into your applications using advanced deep learning models.

Unlike cloud-based solutions, our SDK is fully on-premise, ensuring that all data is processed locally on your server — delivering maximum data privacy and security. No internet connection is required, and no biometric data ever leaves your machine.

Perfect for secure authentication, access control, and enterprise-grade biometric solutions.

Setup

Please download anaconda on your computer and install it. We used Windows machine without GPU for testing

1. Create anaconda environment

conda create -n palm python=3.9

1. Activate the environment

conda activate palm

1. Install dependencies

pip install torch torchvision torchaudio
pip install opencv-python
pip install tqdm
pip install scikit-image
pip install mediapipe

1. Compare two palm images in the test_images directory

python main.py

APIs and Parameters

• classify_hand(mp_hands, hand_landmarks, image_width): determine if the hand is left hand or right hand

• extract_roi(hands, mp_hands, img_path): extract region of interest from the palm image for template matching

• extract_features(mp_hands, hands, path: str): extract template from the plam image specified by the path parameter

• compare_two_images(mp_hands, hands, image_path1, image_path2, similarity_threshold=0.8): compare two hand images to determine if they are the same hand or not.