GUI to label frames for training of ACM-dlcdetect
Project description
ACM-traingui
GUI to label frames for training of ACM-dlcdetect, by Arne Monsees
Installation
- Install Anaconda
- Start Anaconda Prompt (Windows) / terminal (linux) and navigate into repository directory
- Create conda environment
conda env create -f https://raw.githubusercontent.com/bbo-lab/ACM-traingui/main/environment.yml
Running
- Start Anaconda Prompt (Windows) / terminal (linux) and navigate into repository directory
- Switch to environment
conda activate bbo_acm-traingui
- Run with
python -m ACM-traingui [options ...]
Options
Assistant mode
Run with python -m ACM-traingui [base data directory]
.
This starts a GUI in drone mode, for the use by assistants with limited options to influence how the program runs and were it saves. This expects the following file structure:
[base data directory]/data/users/{user1,user2,...}/labeling_gui_cfg.py
[base data directory]/users/
{user1,user2,...} will be presented in a selection dialog on startup. Marking results will be placed in [base data directory]/users/
Master mode
Run with python -m ACM-traingui [configdir] --master
.
This starts a GUI in master mode. Only do this if you know what you are doing.
Check mode
Run with python -m ACM-traingui [directory of labels.npz] --check [bbo_calibcam calibration npy]
.
This gives sorted text output of 3d and reprojections errors. Reporjection errors above 5-10px usually indicate errors in labeling and respective frames have to be checked.
Join mode
Run with python -m ACM-traingui [configdir of ACM-dlcdetect] --check [multiple directories containing labels.npz files]
.
This joins all marked labels in the labels.npz files into the labels.npz file in the dlcdetect configuration. Marked labels overwrite existing labels framewise.
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