Installation
You can either set up the tool with the provided docker image or build the tool by yourself. Once you have the tool set up, you can open http://localhost:8686 to create your annotation project. Below is a quick way to install dependencies and launch the Scalabel server. After launching the server, you can directly jump to Quick Start.
Note: You only need to do either Step 3 or 4, but not both.
Check out the code
git clone https://github.com/scalabel/scalabel cd scalabel
Prepare the local data directories
bash scripts/setup_local_dir.sh
If you have a local folder of images or point clouds to label, you can move them to
local-data/items
. After launching the server (finishing Step 3 or 4), the url for the images will start with http://localhost:8686/items, assuming the port in the scalabel config is 8686. The url of the example imagelocal-data/items/examples/cat.webp
is http://localhost:8686/items/examples/cat.webp. Any files in the items folder and subfolders will be served. Files atlocal-data/items/{subpath}
are available at{hostname}/items/{subpath}
.Using Docker
Download from dockerhub
docker pull scalabel/www
Launch the server
docker run -it -v "`pwd`/local-data:/opt/scalabel/local-data" -p \ 8686:8686 -p 6379:6379 scalabel/www \ node app/dist/main.js \ --config /opt/scalabel/local-data/scalabel/config.yml \ --max-old-space-size=8192
Depending on your system, you may also have to increase docker’s memory limit (8 GB should be sufficient).
Build the code yourself
This is an alternative to using docker. We assume you have already installed Homebrew if you are using Mac OS X and you have
apt-get
if you are on Ubuntu. The code requires Python 3.7 or above. Please check Installation Tips if you don’t have the right version. We use 3.8 by default. Depending on your OS, run the scriptbash scripts/setup_osx.sh
or
bash scripts/setup_ubuntu.sh
If you are on Ubuntu, you may need to run the script with sudo.
Then you can launch the server using node:
node --max-old-space-size=8192 \ app/dist/main.js --config ./local-data/scalabel/config.yml
Depending on your system, you may also have to increase the memory limit from 8192 (8 GB).
Get labels
The collected labels can be directly downloaded from the project dashboard. The labels follow Scalabel Format. You can visualize the labels by
python3 -m scalabel.vis.labels -l <your_downloaded_label_path.json>