Development environment

Installing a development environment for different operating systems.

Setup the dependencies:

Install necessary dependencies:

Ubuntu 18.04

sudo apt-get update && sudo apt-get --no-install-recommends install -y build-essential curl git redis-server python3-dev python3-pip python3-venv python3-tk libldap2-dev libsasl2-dev pkg-config libavformat-dev libavcodec-dev libavdevice-dev libavutil-dev libswscale-dev libswresample-dev libavfilter-dev

# Install Node.js 16
curl -sL https://deb.nodesource.com/setup_16.x | sudo -E bash -
sudo apt-get install -y nodejs

MacOS 10.15

brew install git python pyenv redis curl openssl node sqlite3 geos

Install Chrome
Install FFmpeg libraries (libav*) version 4.0 or higher.
Install VS Code.
Install the following VScode extensions:
Make sure to use Python 3.9.0 or higher
```
python3 --version
```
Install CVAT on your local host:
```
git clone https://github.com/openvinotoolkit/cvat
cd cvat && mkdir logs keys
python3 -m venv .env
. .env/bin/activate
pip install -U pip wheel setuptools
pip install -r cvat/requirements/development.txt
python manage.py migrate
python manage.py collectstatic
```
Note for Mac users

If you have any problems with installing dependencies from cvat/requirements/*.txt, you may need to reinstall your system python In some cases after system update it can be configured incorrectly and cannot compile some native modules

Make sure Homebrew lib path is in DYLD_LIBRARY_PATH. For Apple Silicon: export DYLD_LIBRARY_PATH=/opt/homebrew/lib:$DYLD_LIBRARY_PATH

Homebrew will install FFMpeg 5.0 by default, which does not work, so you should install 4.X. You can install older 4.X FFMpeg using Homebrew like that:
```
 cd "$(brew --repo homebrew/core)"
 git checkout addd616edc9134f057e33694c420f4900be59db8
 brew unlink ffmpeg
 HOMEBREW_NO_AUTO_UPDATE=1 brew install ffmpeg
 git checkout master
```
On Mac with Apple Silicon (M1) in order to install TensorFlow you will have to edit cvat/requirements/base.txt. Change tensorflow to tensorflow-macos
Create a super user for CVAT:
```
python manage.py createsuperuser
```
Install npm packages for UI (run the following command from CVAT root directory):
```
npm ci
```
Note for Mac users

If you faced with error

Node Sass does not yet support your current environment: OS X 64-bit with Unsupported runtime (57)

Read this article Node Sass does not yet support your current environment
Install Docker Engine and Docker-Compose

Pull OpenPolicyAgent Docker-image (run from CVAT root dir):

sudo docker-compose -f docker-compose.yml -f docker-compose.dev.yml up cvat_opa

Run CVAT

Start npm UI debug server (run the following command from CVAT root directory):
- If you want to run CVAT in localhost:
```
npm run start:cvat-ui
```
- If you want to access CVAT from outside of your host:
```
CVAT_UI_HOST='<YOUR_HOST_IP>' npm run start:cvat-ui
```
Open a new terminal window.
Run VScode from the virtual environment (run the following command from CVAT root directory):
```
source .env/bin/activate && code
```
Inside VScode, Open CVAT root dir
Select server: debug configuration and run it (F5) to run REST server and its workers
Make sure that Uncaught Exceptions option under breakpoints section is unchecked
If you choose to run CVAT in localhost: Select server: chrome configuration and run it (F5) to open CVAT in Chrome
Alternative: If you changed CVAT_UI_HOST just enter <YOUR_HOST_IP>:3000 in your browser.

You have done! Now it is possible to insert breakpoints and debug server and client of the tool.

Note for Windows users

You develop CVAT under WSL (Windows subsystem for Linux) following next steps.

Install WSL using this guide.
Following this guide install Ubuntu 18.04 Linux distribution for WSL.
Run Ubuntu using start menu link or execute next command
```
wsl -d Ubuntu-18.04
```
Run all commands from this installation guide in WSL Ubuntu shell.
You might have to manually start the redis server in wsl before you can start the configuration inside Visual Studio Code. You can do this with sudo service redis-server start. Alternatively you can also use a redis docker image instead of using the redis-server locally.