Demo minimum requirement

v0.2 - moved from #9

Each demo will have an independent folder directly under the 'Demos';
For simplicity and ease to convert to notebooks later, avoid sub-folders and separate files for additional functions/classes.

Open accessible data

Each demo should have a 'demo_data.py' script to automatically download demo data;
Preferably, data are hosted in a reliable and efficient (not stored in this repo please) online storage, Kaggle, GitHub and zenodo are all options for non-login access (avoid google drive for known accessibility issues); Relevant data folder structure to utilise the supported loaders can be either pre-arranged in data source or scripted after downloading; Avoid slow and large data set download.

Training

Each demo should have a 'demo_train.py' script; This is accompanied by a config file in the same folder;

Predicting

Each demo should have a 'demo_predict.py' script; Ideally, a pre-trained model will be available for downloading, e.g. the same as your data (not stored in this repo please); Results: Provide at least one piece of numerical metric (Dice, distance error, etc) and one piece of visualisation to show the efficacy of the registration (optimum performance is not required here).

A 'readme.md' file

Briefly describe the clinical application and the need for registration; Acknowledge data source.

Code style

Please restrict using external See general Contribution Guide