LOST - Label Objects and Save Time
- LOST Trailer: https://youtu.be/alocNFQmVQw
- LOST Single Image Annotation - Pipeline Demo: https://www.youtube.com/watch?v=DfDla2hAfWw
- LOST Multi Image Annotation - Pipeline Demo: https://www.youtube.com/watch?v=Q-IpGtH6Xz0
LOST (Label Object and Save Time) is a flexible web-based framework for semi-automatic image annotation. It provides multiple annotation interfaces for fast image annotation.
LOST is flexible since it allows to run user defined annotation pipelines where different annotation interfaces/ tools and algorithms can be combined in one process.
It is web-based since the whole annotation process is visualized in your browser. You can quickly setup LOST with docker on your local machine or run it on a web server to make an annotation process available to your annotators around the world. LOST allows to organize label trees, to monitor the state of an annotation process and to do annotations inside the browser.
LOST was especially designed to model semi-automatic annotation pipelines to speed up the annotation process. Such a semi-automatic can be achieved by using AI generated annotation proposals that are presented to an annotator inside the annotation tool.
If you feel LOST, please find our full documentation here: https://lost.readthedocs.io.
LOST releases are hosted on DockerHub and shipped in Containers. For a quick setup perform the following steps (these steps have been tested for Ubuntu):
Install docker on your machine or server: https://docs.docker.com/install/
Install docker-compose: https://docs.docker.com/compose/install/
git clone https://github.com/l3p-cv/lost.git
Run quick_setup script:
cd lost/docker/quick_setup/ # python3 quick_setup.py path/to/install/lost python3 quick_setup.py ~/lost
Follow instructions of the quick_setup script, printed in the command line.
We've created a chat room for you. Feel free to contact us directly: https://gitter.im/l3p-cv/lost
|L3P UG||CVG University Jena||Hochschule Fulda|