Skip to content

Latest commit

 

History

History
107 lines (64 loc) · 1.9 KB

INSTALL.md

File metadata and controls

107 lines (64 loc) · 1.9 KB

Installing QANet

This document covers how to install QANet, its dependencies (including Pytorch), and the COCO dataset.

  • For general information about QANet, please see README.md.

Requirements:

  • NVIDIA GPU, Linux, Python3.6
  • Pytorch-1.6, various standard Python packages and the COCO API; Instructions for installing these dependencies are found below

Notes:

  • PytorchEveryThing has been tested extensively with CUDA >= 10.1.243 and cuDNN 7.5.1.

Python3.6

To install Python3.6 and soft link to python.

  1. Add source:
sudo apt-get install python-software-properties

sudo apt-get install software-properties-common

sudo add-apt-repository ppa:fkrull/deadsnakes

sudo apt-get update
  1. Install python3.6:
sudo apt-get install python3.6

sudo apt-get install python3.6-dev

sudo apt-get install python3.6-tk
  1. Soft link to python and check (you can use python2 for python2.7):
sudo rm -r /usr/bin/python

sudo ln -s /usr/bin/python3.6 /usr/bin/python

python3 -V
  1. Install pip3 and upgrade (if you want to user pip to install packages for python2, please use pip2):
sudo apt-get install python3-pip

sudo pip3 install --upgrade pip

Note: If some packages cannot be installed, you can go into /usr/local/lib/python3.6/dist-packages/ or /usr/lib/python3/dist-packages/ or /usr/lib/python3.6/ to delete the old version by sudo.

  1. Wrapper opencv to python:
sudo pip3 install opencv-python

Pytorch and torchvision

Install Pytorch with CUDA support.

  1. Install Pytorch-1.6.0:
sudo pip3 install torch==1.6.0
  1. Install torchvision:
sudo pip3 install torchvision==0.7.0

QANet

  1. Clone the QANet repository:
git clone https://github.com/soeaver/QANet.git
  1. Install the requirements.txt:
cd QANet
sudo pip3 install -r requirements.txt
  1. Set up QANet:
cd QANet
sh make.sh