Detectron2 for Active Learning in Object Detection

Usage

Clone the repository with all the submodules:

git clone --recurse-submodules git@github.com:lolipopshock/Detectron2_AL.git

Install dependencies:
1. Installing object detection environment with according to your environment
  - The tested version of pytorch is 1.4.0 with CUDA 10
  - And you must install Detectron2 with version 0.1.1. Newer versions has different APIs.
```
pip install detectron2==0.1.1 \
    -f https://dl.fbaipublicfiles.com/detectron2/wheels/cu100/torch1.4/index.html
```
2. Installing other necessary dependencies:
```
    pip install -r requirements.txt
```
3. Installing UI components
```
cd src/label-studio
pip install -e .
```

Setting up the label-studio server and modeling backend

Initialize the labeling server (If your image folder is ./data)

label-studio init labeling/tk-labeling \
        --input-path=./data \
        --input-format=image-dir \
        --allow-serving-local-files --force \
        --label-config=extra/config.xml \
        --ml-backends http://localhost:9090

And you can start the server via

label-studio start labeling/tk-labeling

Initialize the model backend server

label-studio-ml init labeling/backend_model --script extra/backend_model.py

And similarly, you can start the backend server by

label-studio-ml start labeling/backend_model 
# There's a relative import of the libraries
# So you have to run this command in the project project
# root path to avoid import errors

Start using active learning for annotation