metadata

name: K-POP
license: mit
metrics:
  - MAE
  - PLCC
  - SRCC
  - R2
tags:
  - focus-prediction
  - microscopy
  - pytorch

K-POP: Predicting Distance to Focal Plane for Kato-Katz Prepared Microscopy Slides Using Deep Learning

Description

TODO

How to run

TODO

Install dependencies

# clone project
git clone https://github.com/YourGithubName/your-repo-name
cd your-repo-name

# [OPTIONAL] create conda environment
conda create -n myenv python=3.8
conda activate myenv

# install pytorch according to instructions
# https://pytorch.org/get-started/

# install requirements
pip install -r requirements.txt

Train model with default configuration

# train on CPU
python train.py trainer.gpus=0

# train on GPU
python train.py trainer.gpus=1

Train model with chosen experiment configuration from configs/experiment/

python train.py experiment=experiment_name.yaml

You can override any parameter from command line like this

python train.py trainer.max_epochs=20 datamodule.batch_size=64