Showing posts from November, 2018

How to train custom objects in YOLOv2

This article is based on [1]. We wanna a way to train the object tags that we are interested. Darknet has a Windows version that is ported by AlexeyAB [2]. First of all, we need to build darknet.exe from AlexeyAB to help us train and test data. Go to build/darknet, using VS 2015 to open darknet.sln, and config it to x64 solution platform. Rebuild solution! It should be success to generate darknet.exe. Then, we need to label objects from images that are used for training data. I use BBox label tool to help me label objects' coordinates in images for training data. (python ./ This tool's image root folder is at ./Images, we can create a sub-folder ( 002 ) and insert 002 to let this tool load all *.jpg files from there. We will mark labels in this tool to help us generate objects' region to mark where objects are. The outputs are the image-space coordinate in images and stored at ./Labels/002 . However, the format of this coordinate is different from YOLOv2, YOLOv2