dodo detector
Object detection for robotics with Python and ROS
During my stay at FEI University Center, I was responsible for integrating object detection techniques into a domestic robot. I worked with libraries such as OpenCV and the TensorFlow Object Detection API as well as ROS, the Robot Operating System. This section provides a centralized collection of resources I’ve created during my years working with computer vision and object detection.
Since you’re here, take a look at the set of Python scripts I provide to help in the creation of TFRecord files and label maps for the TensorFlow Object Detection API, as well as TXT annotation files for YOLOv3. I also authored a brief tutorial on how to train a detection model using the TensorFlow Object Detection API with the help of my scripts.
dodo detector (Python)
dodo detector is a Python package that encapsulates OpenCV object detection via keypoint detection and feature matching, as well as the TensorFlow Object Detection API in a single place. See a simple tutorial here. This code was used in the experiments for the paper (Ferreira et al., 2022).
dodo detector ros (ROS)
I am also the creator of dodo detector ros, a ROS package that allows dodo detector to interface with USB cameras as well as both Kinects v1 and v2, in order to detect objects and place them in a 3D environment using the Kinect point cloud. This code was used to develop Hera (Aquino Junior et al., 2019), a domestic robot that won the 2023 RoboCup, as well as several Latin American robotics competitions.