Development environment - Cvat

Setup the dependencies:

Install necessary dependencies:

Ubuntu 22.04/20.04

bash

sudo apt-get update && sudo apt-get --no-install-recommends install -y build-essential curl git python3-dev python3-pip python3-venv python3-tk libldap2-dev libsasl2-dev libgeos-dev cargo

bash

# Install Node.js 20
curl -fsSL https://deb.nodesource.com/setup_20.x | sudo bash -
sudo apt-get install -y nodejs
sudo npm -g install corepack # ensure corepack is installed

MacOS 10.15

bash

brew install git python pyenv redis curl openssl node sqlite3 geos rust

Arch Linux

bash

# Update the system and AUR (you can use any other AUR helper of choice) first:
sudo pacman -Syyu
pikaur -Syu

bash

# Install the required dependencies:
sudo pacman -S base-devel curl git redis cmake gcc python python-pip tk libldap libsasl pkgconf ffmpeg geos openldap rust

bash

# CVAT supports only Python 3.10, so install it if you don’t have it:
pikaur -S python310

bash

# Install Node.js and npm
sudo pacman -S nodejs-lts-gallium npm
sudo npm -g install corepack # ensure corepack is installed

Migration to Yarn Modern

We have updated our Yarn version from Classic (1.x) to Modern. If you are still using CVAT with Yarn Classic you need to first migrate:

bash

# If yarn --version shows 1.x
# remove old yarn
sudo npm uninstall -g yarn

# Ensure corepack is installed
sudo npm install -g corepack

# Enable new yarn
yarn --version # should show 4.x

Install Chrome
Install VS Code.
Install the following VScode extensions:
Make sure to use Python 3.10.0 or higher
bash
```
python3 --version
```
Install CVAT on your local host:
bash
```
git clone https://github.com/cvat-ai/cvat
cd cvat && mkdir logs keys
python3 -m venv .env
. .env/bin/activate
pip install -U pip wheel setuptools
pip install --no-binary lxml,xmlsec -r cvat/requirements/development.txt -r dev/requirements.txt
```
Note that the .txt files in the cvat/requirements directory have pinned dependencies intended for the main target OS/Python version (the one used in the main Dockerfile). If you're unable to install those dependency versions, you can substitute the corresponding .in files instead. That way, you're more likely to be able to install the dependencies, but their versions might not correspond to those used in production.

{{% alert title="Note for Mac users" color="primary" %}} 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:
bash
```
cd "$(brew --repo homebrew/core)"
git checkout addd616edc9134f057e33694c420f4900be59db8
brew unlink ffmpeg
HOMEBREW_NO_AUTO_UPDATE=1 brew install ffmpeg
git checkout master
```
if you are still facing error Running setup.py install for av ... error, you may try more radical variant
bash
```
cd "$(brew --repo homebrew/core)"
git checkout addd616edc9134f057e33694c420f4900be59db8
brew uninstall ffmpeg --force
HOMEBREW_NO_AUTO_UPDATE=1 brew install ffmpeg
git checkout master
```
If you faced with error Failed building wheel for h5py, you may need install hdf5
bash
```
brew install hdf5
export HDF5_DIR="$(brew --prefix hdf5)"
pip install --no-binary=h5py h5py
```
If you faced with error OSError: Could not find library geos_c or load any of its variants ['libgeos_c.so.1', 'libgeos_c.so']. You may fix this using
bash
```
sudo ln -s /opt/homebrew/lib/libgeos_c.dylib /usr/local/lib
```
{{% /alert %}}

{{% alert title="Note for Arch Linux users" color="primary" %}} Because PyAV as of version 10.0.0 already works with FFMPEG5, you may consider changing the av version requirement in /cvat/cvat/requirements/base.txt to 10.0.0 or higher.

Perform this action before installing cvat requirements from the list mentioned above. {{% /alert %}}
Install Docker Engine and Docker Compose
Start service dependencies:
bash
```
docker compose -f docker-compose.yml -f docker-compose.dev.yml up -d --build \
  cvat_opa cvat_db cvat_redis_inmem cvat_redis_ondisk cvat_server
```
Note: this runs an extra copy of the CVAT server in order to supply rules to OPA. If you update the OPA rules, rerun this command to recreate the server image and container.

Note: to stop these services, use docker compose -f docker-compose.yml -f docker-compose.dev.yml down. You can add -v to remove the data, as well.

Apply migrations and create a super user for CVAT:

bash

python manage.py migrate
python manage.py migrateredis
python manage.py collectstatic
python manage.py syncperiodicjobs
python manage.py createsuperuser

Install npm packages for UI (run the following command from CVAT root directory):
bash
```
corepack enable yarn
yarn --immutable
```
{{% alert title="Note for Mac users" color="primary" %}} 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 {{% /alert %}}

Run CVAT

Start npm UI debug server (run the following command from CVAT root directory):
- If you want to run CVAT in localhost:
  sh
```
yarn run start:cvat-ui
```
- If you want to access CVAT from outside of your host:
  sh
```
CVAT_UI_HOST='<YOUR_HOST_IP>' CVAT_UI_PORT='<YOUR_PORT>' yarn run start:cvat-ui
```
Open a new terminal window.
Run VScode from the virtual environment (run the following command from CVAT root directory):
sh
```
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.

{{% alert title="Note for Mac users" color="primary" %}} You may have a permission denied problem starting the server because AirPlay Receiver running on port 5000/7000.

Turn off AirPlay Receiver: Go to System Settings → General → AirDrop & Handoff → Untick Airplay Receiver. {{% /alert %}}

You have done! Now it is possible to insert breakpoints and debug server and client of the tool. Instructions for running tests locally are available {{< ilink "/docs/contributing/running-tests" "here" >}}.

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
powershell
```
wsl -d Ubuntu-18.04
```
Install the VS Code extension for WSL, which helps you to open VS Code correctly inside WSL. You can find the extension here.
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.

Note for Mac users

You might have to manually start the redis server. You can do this with redis-server. Alternatively you can also use a redis docker image instead of using the redis-server locally.

Note for Arch Linux users

You need to start redis and docker services manually in order to begin debugging/running tests:
bash
```
sudo systemctl start redis.service
sudo systemctl start docker.service
```

CVAT Analytics Ports

In case you cannot access analytics, check if the following ports are open:

yml

cvat_vector:
    ports:
      - '8282:80'

  cvat_clickhouse:
    ports:
      - '8123:8123'

In addition, you can completely disable analytics if you don't need it by deleting the following data from launch.json:

json

  "DJANGO_LOG_SERVER_HOST": "localhost",
  "DJANGO_LOG_SERVER_PORT": "8282"

Analytics on GitHub: Analytics Components