Data from: A pilot computer-vision model trained to identify slide-mounted scale insect pests from the family Rhizoecidae

Includes the species test folder, unique identifiers for images, model prediction and confidence scores, prediction accuracy, group, and additional notes on specimen condition.</p><p dir="ltr">S2 Table. Total number of Rhizoecidae images from the USNM, CDFA, and FSCA collections captured with the Glissando slide scanner.</p><p dir="ltr">S1 Appendix. Python scripts and a list of all used libraries and their versions.

This directory holds all python code and Jupyter Notebooks needed to train, validate, and perform inferencing.</p><p dir="ltr">S2 Appendix. Details on training parameters and augmentations. This directory contains the directories generated by BioEncoder natively or that were added during the development process.</p><p dir="ltr">S3 Appendix.

R code for analysis of model confidence by prediction category. Uses S1 Table as the data matrix.</p><p dir="ltr">S4 Appendix. CNN model training results.

This directory includes training data, inference, logs, metrics, plots, runs, and weights.</p>