Challenge Webpage: Summer Challenge on Writer Verification, under NCVPRIPG'23
Blog Post: Winning the NCVPRIPG23 Challenge on Writer Verification
Kaggle Link: Summer Challenge on Writer Verification
Wandb logs: wandb
Team Name: MaSha
Summary Paper: assets/NCVPRIPG23_Writer_Verification.pdf
conda env create -f environment.yml
conda activate ncvp
mkdir -p data/raw
Download and extract the dataset including the val and test CSVs in data/raw
.
The checkpoint for the best trained model can be found at Google Drive. You can download this and store it at a desired location. For downloading, you can use gdown.
mkdir pretrained
cd pretrained
gdown 'https://drive.google.com/uc?id=1848Iu-JKXWSBgFvBN50-l-ZXXKgqkRJf'
python inference.py --ckpt pretrained/model_best_base.pth.tar
All runs have been logged using wandb
To start training, run
python train.py
You might have to change the inputs to wandb.init()
function.
To reproduce the best results, pass the best config
python train.py --config cfgs/best.yml
To disable wandb while training, run
WANDB_MODE=disabled python train.py