INSTALL.md

Installation

This document contains detailed instructions for installing the necessary dependencies for LLB. The instrustions have been tested on an Ubuntu 16.04 system.

Requirements

• Conda installation with Python 3.7. If not already installed, install from https://www.anaconda.com/distribution/.
• Nvidia GPU.

Step-by-step instructions

Create and activate a conda environment

conda create --name LLB python=3.7
conda activate LLB

Install PyTorch

Install PyTorch with cuda10.

conda install pytorch torchvision cudatoolkit=10.0 -c pytorch

Note:

• It is possible to use any PyTorch supported version of CUDA (not necessarily v10).
• For more details about PyTorch installation, see https://pytorch.org/get-started/previous-versions/.

Install matplotlib, pandas, tqdm, opencv, scikit-image, visdom, tikzplotlib, gdown, and tensorboad

conda install matplotlib pandas tqdm
pip install opencv-python visdom tb-nightly scikit-image tikzplotlib

Install the coco and lvis toolkits

conda install cython
pip install pycocotools
pip install lvis

Install jpeg4py

In order to use jpeg4py for loading the images instead of OpenCV's imread(), install jpeg4py in the following way,

sudo apt-get install libturbojpeg
pip install jpeg4py 

Note: The first step (sudo apt-get install libturbojpeg) can be optionally ignored, in which case OpenCV's imread() will be used to read the images. However the second step is a must.

In case of issues, we refer to https://github.com/ajkxyz/jpeg4py.

Setup the environment

Create the default environment setting files.

# Environment settings for pytracking. Saved at pytracking/evaluation/local.py
python -c "from pytracking.evaluation.environment import create_default_local_file; create_default_local_file()"

# Environment settings for ltr. Saved at ltr/admin/local.py
python -c "from ltr.admin.environment import create_default_local_file; create_default_local_file()"

You can modify these files to set the paths to datasets, results paths etc.