Splitting data into train, validation, and test splits is essential to building good computer vision models. Today, we are announcing in-app changes to Roboflow that make it even easier to manage your train test splits as you are working through the computer vision workflow.
Keeping track of images and their corresponding annotations is a challenge. Knowing which annotations map to which class, viewing image metadata, and seeing which images correspond to a training, validation,
With Roboflow Pro, you can now remap and omit class labels within Roboflow as a preprocessing step for your dataset version. Class management is a powerful tool to get the most out of your training data and your hard earned class label annotations.
Roboflow improves datasets without any user effort. This includes dropping zero-pixel bounding boxes and cropping out-of-frame bounding boxes to be in-line with the edge of an image. Roboflow also notifies
We've seen tremendous interest in Roboflow from the research community. Faculty and students from institutions ranging from California to Malta to Taiwan have been using Roboflow to accelerate their computer