livenessDetection
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Trains and implements liveness detection with video input in Python code
Liveness Detection
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This code trains and implements via video from the pyimagesearch liveness detection blog
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We modified the blog's original shallow CNN model to Resnet50 that can achieve better accuracy
Get this code:
git clone https://github.com/joytsay/livenessDetection.git
cd livenessDetection
Pre-Trained Model and Train/Test Videos:
Download from here and put in root folder (/livenessDetection
)
Setup Environment:
Tested on Windows 10 mini-conda environment via
Miniconda3-latest-Windows-x86_64.exe
Tested on MacOS M2 mini-forge environment via
brew install miniforge
Install Code:
Option 1: Auto run bat files
run 01_XXX.bat files (01~05) sequentially:
01_install.bat
02_gather.bat
03_trainLiveness.bat
04_runLiveness.bat
05_webcam.bat
Option 2: Cmd Line
conda create -n liveness python=3.8
conda activate liveness
pip install -r requirements.txt
# data pre-process
python gather_examples.py -i ./videos/fake.mp4 -o ./dataset/fake -d ./face_detector -c 0.9 -s 1 -f 0
python gather_examples.py -i ./videos/real.mp4 -o ./dataset/real -d ./face_detector -c 0.9 -s 1 -f 0
python gather_examples.py -i ./videos/mask.mp4 -o ./dataset/mask -d ./face_detector -c 0.9 -s 1 -f 0
# train model
python train_liveness.py -d ./dataset -m liveness.model -l le.pickle
# run liveness model on test video
python liveness_demo.py -m liveness.model -l le.pickle -d ./face_detector -c 0.5
press "q" to quit
# run liveness model on web cam
python webcam.py -m liveness.model -l le.pickle -d ./face_detector -c 0.5
Reference
The following link is the original pyimagesearch liveness-detection-with-opencv example code
Find this project useful ? :heart:
- Support it by clicking the :star: button on the upper right of this page. :v:
Credits
- The example has been taken from pyimagesearch liveness-detection-with-opencv example and modified model to Resnet50
License
Copyright (C) 2020 Adrian Rosebrock, PyImageSearch, accessed on March 11, 2019
Contributing to livenessDetection
Just make pull request. Thank you!