I am trying to create a Plant diease detection model for grapes using HERMOS: An Annotated Image Dataset for Visual Detection of Grape Leaf Diseases. It has jpg and xml files. Each xml file has annotation details for each jpg$.$ The data contains four classes of grapevine images; leaves with dead root, leaves with powdery mildew, leaves with downy mildew and healthy leaves. Diseased areas on the leaf pictures were labeled with the "bounding$-$box" method. The dataset contains a total of $914$ images and $13,904$ labels. Labels on the picture are stored in Pascal VOC format in an xml document with the same file name as the picture. I need your help to write the code for me$.$ I want this to be solved through RCNN in a professional way like I can get proper metricces output, visulaization etc. Also, jpg size is not standard so better $256$x$256$ resize could be better.

NOTE$-$ Many expert tried to code this but its half cooked and also wrong. I suggest to try on some sample on hermos: an annotated image dataset for visual detection of grape leaf diseases $($its easily availble on internet$).$ Even you donot want to try it please do not use GPT to finish the code as it will not work. Need a code that actualy runs and show the running epochs, metrics values, graphs etc.