EVA: Video Annotation Tool

EVA is a web-based tool for efficient annotation of videos and image sequences. It is a re-design of BeaverDam with additional tracking capabilities. The annotation is done on a bounding box level and the labels can be exported in YOLO or Pascal VOC format.

Setup

Windows:

Requirements:

• Python 3.6: https://www.python.org/downloads/ (not version 3.6.7)
• Redis: https://github.com/MicrosoftArchive/redis/releases/download/win-3.2.100/Redis-x64-3.2.100.msi
• Browser: Google-Chrome Version > 49.0, Firefox Version > 45.0
• FFMPEG (optional for video upload): https://ffmpeg.zeranoe.com/builds/
• Microsoft Visual Studio 2015 or later version: https://visualstudio.microsoft.com/downloads/ (to have a cpp-compiler)

Install:

# Clone the repository
git clone https://github.com/Ericsson/eva.git

# Change to the project directory
cd eva

# Upgrade pip
python -m pip install --upgrade pip

# Install virtualenv
pip install virtualenv

# Create a virtual environment
python -m virtualenv venv

# Activate the virtual environment (for Windows)
venv\Scripts\activate.bat

# Install project dependencies
pip install -r requirements.txt

# Prepare the tracker
python manage.py preparetracker

# Apply database migrations
python manage.py migrate

# Collect static files
python manage.py collectstatic

Extract ffmpeg archive and copy ffmpeg.exe, from the bin folder, to the root of the tool\ folder e.g. if you clone the repository as eva place the ffmpeg.exe inside eva\.

Start the app by running the start.bat file. In Chrome or Firefox go to http://127.0.0.1:8000/.

Linux:

Requirements:

• Python 3.6, redis, ffmpeg, g++.
• Browser: Google-Chrome Version > 49.0, Firefox Version > 45.0

Install:

# Clone the repository
git clone https://github.com/Ericsson/eva.git

# Change to the project directory
cd eva

# Install virtualenv using pip3
pip3 install virtualenv

# Create a virtual environment
python3 -m virtualenv venv

# Activate the virtual environment
source venv/bin/activate

# Upgrade pip inside the virtual environment
pip install --upgrade pip

# Install project dependencies
pip install -r requirements.txt

# Prepare the tracker
python manage.py preparetracker

# Apply database migrations
python manage.py migrate

# Collect static files
python manage.py collectstatic

Start the app by running the start.sh file. In Chrome or Firefox go to http://127.0.0.1:8000/.

Docker:

Run using docker-compose

First run the following commands to initialize the tool. These only have to be run once, but if the tool is updated they should be repeated.

# Build the Docker containers
docker-compose build

# Apply database migrations
docker-compose run eva python3 manage.py migrate

# Collect static files
docker-compose run eva python3 manage.py collectstatic

Start the app by running:

docker-compose up

In Chrome or Firefox open the http link: http://127.0.0.1:8000/

Changing parameters:

You can change the parameters of the tracker by editing cfg/KCF_config.yml.

Acknowledgement:

Thanks to Ludwig Thaung for his contribution in building the EVA tool.