A collection of widgets intended to serve any person seeking to process microscopy images from start to finish, with no coding necessary. napari-ndev was designed to address the gap between the napari viewer and batch python scripting. Accepts diverse image formats, dimensionality, file size, and maintains key metadata. Allows advanced, arbitrary image processing workflows to be used by novices. User-friendly sparse annotation and batch training of machine learning classifiers. Flexible label measurements, parsing of metadata, and summarization for easily readable datasets. Designed for ease of use, modification, and reproducibility.