Honours

Requirements

pip install -e .

File Structure

scripts/ main.py begins process from initial data to final result apply_ssm.py applies the trained ssm model to data generate_report generates an evaluative

data/ Contains 2 images demonstrating what the data looks like

ssm/ The split-speckle module.

ssn2v/ Contains reminant code of my SSN2V implementation.

n2v/ https://github.com/juglab/n2v

n2n/ https://github.com/NVlabs/noise2noise

n2s/ https://github.com/czbiohub-sf/noise2self

classification/ https://github.com/Sudhandar/ResNet-50-model

Background

FPSS

Preprocessing

Training

Before training, configure the config.yaml files with training content.

py trainers/fpss_trainer.py

Baseline Training

''' py trainers/n2n_trainer.py py trainers/n2s_trainer.py py trainers/n2v_trainer.py '''

N2-FPSS Training