Name: Adedamola Ayodeji Sode
Type: User
Company: Diamond Light Source
Bio: Robotics engineer into computer vision, machine learning and sometimes game design. New to GitHub.
What you'll see: Projects, Tutorials, Prototyping.
Location: Didcot, United Kingdom
Adedamola Ayodeji Sode's Projects
Practicing Algorithms and Data Structures for Self Learning
Bend Hackers Guild Website
Working with a CNN for room classfication
Implementations from the free course Deep Reinforcement Learning with Tensorflow
Copy of a dice game website. Replicating the website for learning purposes
Assignment Project for the experimental robotics laboratory course in UniGE
Finetuning Mobile net for monkey breed classifier
Robot simulation for variable pick and place purposes
C++ and PyGame Implementation of the classic ConnectFour game.
Hand tracking using computer vision
Understanding Javascript
stores material for the learning part of centrale nantes master program
A sphinx-based centralized documentation repo for MoveIt
Another personal website to brush up web development skills with more CSS inclusion. A milestone on the pathway of learning web development as a robotics engineer (because why not have cool web apps???).
Practicing using the ssd_mobile net for object detection.
Python and OpenCV implementation of object tracking
My implementation of the original transformer model (Vaswani et al.). I've additionally included the playground.py file for visualizing otherwise seemingly hard concepts. Currently included IWSLT pretrained models.
Taking a course on Robotics Software Engineering
Package for the first assignment of the Research Track 2 course
Documentation implementation of Research track 1 final assignment provided by Dr. Carmine Recchiuto
Deep Learning Model Training for Screw Object Detection
Project encompassing perception, decision making and action, modelled after the NASA Sample Return Challenge. The aim being to program a robot to navigate its environment autonomously and consequently making a map of its environment, while searching for rocks of interest.
Creating an interface to utilize pretrained models to make A.I. assisted labels to make further labelling easier. This is a project spawned from my screw detection project because labelling thousands of images without help sucks. It isn't going to be extremely precise, so this is assisted labelling, not auto labelling, always check the labels.
Used a SMO and SVM algorithm on the wall following robot dataset on Kaggle
Just learning the Tkinter library to make my programs higher level for ease of use.
YOLOv6: a single-stage object detection framework dedicated to industrial applications.