When to Use Contrast as a Preprocessing Step

Adding contrast to images is a simple yet powerful technique to improve our computer vision models. But why? When considering how to add contrast to images and why we add contrast to images in computer vision, we must start with the basics. What is contrast? How contrast preprocessing improve our…

When Should I Auto-Orient My Images?

The recommended Roboflow setting is "Auto-Orient: Enabled"When should you auto-orient your images?The short answer: almost always.When an image is captured, it contains metadata that dictates the orientation by which it should be displayed relative to how the pixels are arranged on disk. This directive (stored in the…

Breaking Down Roboflow's Health Check Dimension Insights

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 users of potential areas requiring attention like severely underrepresented classes (as was present in the original hard hat object detection…

The Difference Between Missing and Null Annotations

A discussion of missing versus null annotations and how VOC XML and COCO JSON handle them. Preparing data for computer vision models is a tedious task. Even assuming training images are appropriately representative for inference, managing annotations quickly becomes a challenge. In some annotation formats (PASCAL VOC XML, YOLO DarkNet)…

How to Create a Synthetic Dataset for Computer Vision

Synthetic datasets are increasingly being used to train computer vision models in domains ranging from self driving cars to mobile apps. The appeals of synthetic data are alluring: you can rapidly generate a vast amount of diverse, perfectly labeled images for very little cost and without ever leaving the comfort…

Introducing Image Preprocessing and Augmentation Previews

Knowing how an image preprocessing step or augmentation is going to appear before you write the code for it is essential. Is it worth it to figure out the right amount of brightness? Will rotation increase variability appropriately? Roboflow is introducing features to take out the guesswork: preprocessing and augmentation…

How Flip Augmentation Improves Model Performance

Flipping an image (and its annotations) is a deceivingly simple technique that can improve model performance in substantial ways. Our models are learning what collection of pixels and the relationship between those collections of pixels denote an object is in-frame. But machine learning models (like convolutional neural networks) have a…