zpykillcc / software_ai

Software_AI

Installation

Requirements

• Nvidia device with CUDA, example for Ubuntu 20.04 (if you have no nvidia device, delete this line from setup.py
• Python 3.7+
• Cython
• PyTorch 1.11+, for users who want to use 1.5 < PyTorch < 1.11, please switch to the pytorch<1.11 branch by: git checkout "pytorch<1.11"; for users who want to use PyTorch < 1.5, please switch to the pytorch<1.5 branch by: git checkout "pytorch<1.5"
• torchvision 0.12.0+
• numpy
• python-package setuptools >= 40.0, reported by this issue
• Linux, Windows user check here

• 配置conda环境

conda create -n myconda python=3.8
conda activate alphapose
pip3 install torch torchvision --extra-index-url https://download.pytorch.org/whl/cu113

• 安装

# 1. install
export PATH=/usr/local/cuda/bin/:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64/:$LD_LIBRARY_PATH
pip install cython
sudo apt-get install libyaml-dev
pip install -r requirements.txt
python3 ./AlphaPose/setup.py build develop --user

# 2. Install PyTorch3D (Optional, only for visualization)
conda install -c fvcore -c iopath -c conda-forge fvcore iopath
conda install -c bottler nvidiacub
pip install git+ssh://[email protected]/facebookresearch/pytorch3d.git@stable

• 安装ffmpeg

sudo apt-get install ffmpeg

• 安装facenet依赖

pip install -r requirements.txt

Models

Alphapose

1. Download the object detection model manually: yolov3-spp.weights(Google Drive | Baidu pan). Place it into AlphaPose/detector/yolo/data.
2. (Optional) If you want to use YOLOX as the detector, you can download the weights here, and place them into AlphaPose/detector/yolox/data. We recommend yolox-l and yolox-x.
3. Download our pose models. Place them into AlphaPose/pretrained_models. All models and details are available in our Model Zoo.
4. For pose tracking, please refer to our tracking docments for model download

FaceNet

在https://github.com/zpykillcc/facenet 可以找到mtcnn和facenet模型放入recgnize/model_check_point

框架

• flask接受前端请求，调用Alphapose模块和recgnize模块进行姿势识别的人脸识别
• Alphapose使用pytorch
• FaceNet使用tensorflow

使用

flask run -p 6006

端口6006