# BuildMyFaceModel
基于MobileFaceNet的静默活体检测系统的设计与实现
1、下载代码
2、实验环境
Windows 10（64位）
CPU：AMD Ryzen 7 5800H
RAM：16G
GPU：NVIDIA RTX3060
开发工具：IntelliJ IDEA以及PyCharm
相关配置及版本：
Chrome 90.0.4430.212
SpringBoot 2.2.6
Java JDK8
MyBatis 2.1.1
Mysql 8.0.25
Python 3.8
pytorch 1.7.1
torchvision 0.8.2
numpy 1.18.5
tensorboard 2.4.1
pandas 1.2.3
cuda 11.0.2
cudnn 11.2
torch 1.8.1
torchvision 0.9.1
3、模型训练命令
python train.py
4、模型测试命令
python test.py
5、运行检测模块命令
python detect.py --source 0
基于Python+MobileFaceNet的静默活体检测系统的设计与实现
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2024-05-15
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基于Python+MobileFaceNet的静默活体检测系统的设计与实现 （117个子文件） 
events.out.tfevents.1622733592.LAPTOP-HETSK9TT.8288.0 2KB events.out.tfevents.1622695852.LAPTOP-HETSK9TT.2468.0 40B Dockerfile 821B
1_byz.jpg 785KB 1_tty.jpg 300KB 1_ouyandidi.jpg 47KB 1_zxd.jpg 11KB 1_zxd.jpg 11KB 001.jpg 7KB README.md 958B
0.mp4 519KB yolov5s.pt 14.11MB best.pt 13.71MB 21.pth 7.78MB 4_0_0_80x80_MiniFASNetV1SE.pth 1.77MB 2.7_80x80_MiniFASNetV2.pth 1.76MB datasets.py 43KB general.py 24KB functional.py 20KB plots.py 18KB detect_cost_test.py 16KB wandb_utils.py 16KB common.py 15KB detect.py 15KB MiniFASNet.py 12KB torch_utils.py 12KB yolo.py 12KB transform.py 11KB loss.py 9KB metrics.py 9KB autoanchor.py 7KB facenet.py 6KB experimental.py 5KB google_utils.py 5KB export.py 4KB test.py 4KB train.py 3KB predict_net.py 2KB activations.py 2KB compute_two_face.py 2KB generate_patches.py 2KB metric.py 2KB config.py 2KB anti_spoof_test.py 1KB generate_celebA_Spoof_test_pair.py 1KB resume.py 1KB utility.py 990B dataset.py 929B log_dataset.py 894B analyse_time_cost.py 733B generate_test_data.py 442B loss.py 402B demo.py 342B __init__.py 95B __init__.py 85B datasets.cpython-36.pyc 33KB datasets.cpython-38.pyc 33KB general.cpython-36.pyc 19KB general.cpython-38.pyc 19KB functional.cpython-36.pyc 18KB functional.cpython-38.pyc 18KB plots.cpython-36.pyc 16KB plots.cpython-38.pyc 16KB transform.cpython-36.pyc 12KB transform.cpython-38.pyc 12KB MiniFASNet.cpython-36.pyc 12KB torch_utils.cpython-38.pyc 11KB torch_utils.cpython-36.pyc 11KB MiniFASNet.cpython-38.pyc 11KB metrics.cpython-36.pyc 7KB metrics.cpython-38.pyc 7KB autoanchor.cpython-36.pyc 6KB autoanchor.cpython-38.pyc 6KB facenet.cpython-38.pyc 6KB facenet.cpython-36.pyc 5KB google_utils.cpython-38.pyc 3KB google_utils.cpython-36.pyc 3KB predict_net.cpython-38.pyc 2KB predict_net.cpython-36.pyc 2KB metric.cpython-36.pyc 2KB metric.cpython-38.pyc 2KB generate_patches.cpython-38.pyc 1KB utility.cpython-38.pyc 1KB loss.cpython-36.pyc 800B loss.cpython-38.pyc 797B __init__.cpython-36.pyc 281B __init__.cpython-38.pyc 266B __init__.cpython-36.pyc 243B __init__.cpython-38.pyc 228B __init__.cpython-36.pyc 148B __init__.cpython-38.pyc 133B userdata.sh 1KB mime.sh 780B
yolo_cost.txt 2KB face_cost.txt 2KB all_cost.txt 2KB spoof_cost.txt 2KB additional_requirements.txt 105B anchors.yaml 3KB yolov5-p7.yaml 2KB共 117 条
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