Palm Recognition SDK for Windows and Linux - Fully On Premise

Overview

The world's 1st Completely Free and Open Source Palm Recognition SDK from Faceplugin for developers to integrate palm recognition capabilities into applications. Supports real-time, high-accuracy palm recognition with deep learning models.
This is on-premise palm recognition SDK which means everything is processed in your device and NO data leaves it.
You can use this SDK on Windows and Linux.

Please contact us if you need the SDK with higher accuracy.

Key Features

• Real-Time Palm Recognition: Can detect and recognize palm from live video streams. Currently only supports palm recognition from an image.
• High Accuracy: Built with deep learning models trained on large datasets.
• Cross-Platform: Compatible with Windows and Linux.
• Flexible Integration: Easy-to-use APIs for seamless integration into any project.
• Scalable: Works on local devices, cloud, or embedded systems.
• Python SDK: Comprehensive support for Python with extensive documentation and examples.

Applications

This Palm Recognition SDK is ideal for a wide range of applications, including:

• Time Attendance Systems: Monitor arrivals and depatures using palm recognition.
• Security Systems: Access control and surveillance.
• User Authentication: Biometric login and multi-factor authentication.
• Smart Devices: Integration into IoT devices for smart home or office applications.
• Augmented Reality: Enhance AR applications with real-time palm recognition.

Installation

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

create anaconda environment

• conda create -n palm python=3.9

activate env

• conda activate palm

install dependencies

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

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
  

List of our Products

• FaceRecognition-LivenessDetection-Android
• FaceRecognition-LivenessDetection-iOS
• FaceRecognition-LivenessDetection-Javascript
• FaceLivenessDetection-Android
• FaceLivenessDetection-iOS
• FaceLivenessDetection-Linux
• FaceRecognition-LivenessDetection-React
• FaceRecognition-LivenessDetection-Vue
• Face Recognition SDK
• Liveness Detection SDK
• ID Card Recognition

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