This tutorial shows how to use different functionalities of the Point Cloud Library (PCL) together with Royale.

This tutorial explains the "sampleOpenCV" which shows how you can use OpenCV with Royale.

This example shows how to detect objects in an image using Royale's Python wrapper and the pre-trained YOLO network

Repository with implementations and comparisons of two advanced object detection models: YOLO and Keras. The goal is to provide a unified platform to explore, test, and compare the performance of these models across diverse datasets and scenarios.

This repository contains implementations and comparisons of various contour detection techniques using OpenCV. The primary objective is to offer a comprehensive platform to explore, test, and compare the performance of these methods in detecting objects from a camera feed.

This project uses ROS (Robot Operating System) and OpenCV to detect objects in images captured by a camera and publishes the results in a ROS topic. It is composed of two main nodes: a node for detecting objects and another for publishing the results.

Repository with implementations and comparisons of two advanced object detection models: YOLO and Faster R-CNN. The goal is to provide a unified platform to explore, test, and compare the performance of these models across diverse datasets and scenarios.