YOLO is an analytics model running on UbiOps. It is a real-time object detection engine, that can simultaneously recognise multiple objects in an image.

This components uses this analytics model to detect objects in an image and returns the image with labeled bounding boxes around the detected objects and with a list of items and their count.

YOLOv4 uses an extended Convolutional Neural Network architecture. For more information about the underlying Neural Network and further resources, you can read this blog post: https://ubiops.com/how-to-deploy-yolov4-on-ubiops/. It is implemented on UbiOps with ONNX for speedup.

Please read my blogpost about this integration: https://www.outsystems.com/blog/posts/can-low-code-enable-machine-learning/