delphi-cvat

Decription

Delphi is an interactive system that performs bandwidth-efficient labeling for low-baserate targets. In this repository, we integrate Delphi with CVAT to prune negatives from a given image directory.

Delphi creates the intial filter from a set of labeled data provided by the user. A minimum of 5 images per label (positive & negative) are required to start the filter. Delphi achieves bandwidth effiecieny through early-discard and iterative improvement of classifiers. When the user marks a task as "completed" in CVAT, Delphi retrieves the annotation file from CVAT to expand the labeled set and re-train the classifier.

This is a developing project.

System Architecture

Environment setup

This code has been tested on Ubuntu 16.04, Python 3.7, Pytorch 1.5, CUDA 10.2, GTX 1080 GPUs

• Clone the repository

git clone https://github.com/a4anna/delphi-cvat && cd delphi-cvat
export DELPHI=$PWD

• Setup python environment

conda env create -f environment.yml
conda activate delphi

• Set environment variable

export CVAT_USER={CVAT-USERNAME}
export CVAT_PASS={CVAT-PASSWORD}
export PYTHONPATH=$DELPHI:$PYTHONPATH

Data Directory Structure

+data-root/  
  +labeled/  
    +0/ # labeled negative image directory  
      -000.jpg  
      -501.jpg  
      -*.jpg     
    +1/ # labeled positive image directory  
      -011.jpg  
      -203.jpg  
      -*.jpg  
  +unlabeled/  
    -*.jpg  

Generate proto files

 cd $DELPHI
 python generate_proto.py

How to Run

Launch CVAT

Instructions on how to install and run CVAT can be found here.
Note: Currently, we only support "Tag Annotation".

Modify config.yml

Start Delphi

./run.sh