Easy to use small framework for faster model development and visualization
- clone the repo
 - create conda environment (conda env create -f env_specs.yml)
 - choose or define a model (
models/your_model.py) - choose or define a dataset_loader
 - modify 
constants.py - run model
 - run tensorboard (tensorboard --logdir=runs) to see the results
 
- Refactor and improve backbone functionality
 - Add examples (MixNet, EfficientNet, gans etc) and improve documentation
 - Add multiple models and layers
 - Add more image enhancement techniques
 - Add or facilitate more complex image visualization methods (matplotlib ... facets)
 - Add python "artisan" for easier use