The Tensorflow Object Detection API uses a proprietary binary file format called TFRecord. Creating TFRecord files has long been the bane of many developers' existence. While they are very efficient for TensorFlow's deep learning framework to parse, they are quite opaque and are not human readable. They're quite finicky; If something is wrong, it's not easy to find out why.
It's not really possible to create these files by hand. You'll need to use a tool to create them. The most foolproof tool to use is Roboflow because, unlike most one-off shell scripts, Roboflow is a universal converter for computer vision formats.
With Roboflow you can seamlessly convert whatever filetype your annotation tool exports directly into a TFRecord that's ready to use for training your model.
On each page below, you can find links to our guides that show how to plot predictions from the model, and complete other common tasks like detecting small objects with the model.
