Evaluate project by measuring Segmentation pixelwise AUROC(area under a receiver operating characteristic curve) performance. The Area Under the Curve (AUC) is the measure of the ability of a classifier to distinguish between classes and is used as a summary of the ROC curve. The higher the AUC, the better the performance of the model at distinguishing between the positive and negative classes.

Read more here:

[AUC-ROC Curve in Machine Learning Clearly Explained](https://www.analyticsvidhya.com/blog/2020/06/auc-roc-curve-machine-learning/)

[ML Crash course](https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc)

[Understanding AUCROC](https://towardsdatascience.com/understanding-auc-roc-curve-68b2303cc9c5)

[Lets learn about AUCROC article](https://medium.com/greyatom/lets-learn-about-auc-roc-curve-4a94b4d88152)