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Course project for SJTU CS385: Machine Learning, advised by Prof. Quanshi Zhang, where I implemented many algorithms from scratch for face recognization and detection.

Python 0.65% Jupyter Notebook 99.35%

face_recognization_detection's Introduction

Face Recognization and Detection

Course project for SJTU CS385: Machine Learning, taught by Prof. Quanshi Zhang

Requirement

numpy
tensorflow

Run

Unzip FDDB-folds.tgz and originalPics.tar.gz into data/

Run python preprocess.py

To do face recognization, run python recognization.py with following arguments

-model: model name, lr/svm/fisher/cnn
-lr: learning rate
-total_epoches: total training epoches
-batch_size: batch size for cnn model
-kernel: kernel type of svm
-langevin: if set, use langevin dynamics
-gpu: gpu device

To do face detection, run python detection.py with following arguments

-model: model name, lr/svm/cnn
-winSize: sliding window size
stride: sliding window stride length
thres_score: threshold of score
thres_iou: threshold of IoU
scales: scale factors, use , to seperate
hw_ratios: height-width ratios, use , to seperate

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