computer-vision

Welcome to the world of Computer Vision! This GitHub repository, titled "computer-vision," is your gateway to a rich collection of hands-on examples, showcasing key techniques such as object detection, image classification, semantic segmentation, generative models, transfer learning, and the cutting-edge field of foundation models. These examples are implemented using two leading deep learning frameworks, TensorFlow and PyTorch, both highly regarded in the AI community.

Originally created for the "Principles and Design of IoT Systems" module, this repository is also a valuable resource for anyone looking to learn computer vision. You'll embark on a hands-on journey designed to not only teach but inspire experimentation and innovation in this dynamic field.

With the "computer-vision" repository, you'll be equipped to tackle exciting projects, explore new research opportunities, and make meaningful contributions to the ever-evolving landscape of computer vision. The possibilities are vast, and the learning experience is designed to be both exciting and practical.

Here's the repository's structure:

• Week 6: Introduction to Machine Learning
• Week 7: Image Representation, Image Classification, Data Augmentation, and Transfer Learning
• Week 8: Object Detection and Image Annotation
• Week 9: Semantic Segmentation and Foundation Models
• Week 10: Object Tracking and Advanced Topics

Prepare for a rewarding journey as you dive into the captivating world of computer vision! To replicate this repository, you'll need to have Git installed on your computer. Alternatively, you can run most of the code directly on Google Colab. Follow the steps below to clone this repository:

• Open the terminal or command prompt and then navigate to the directory where you want to clone the repository.

• Type the following command:

git clone https://github.com/tahamsi/computer-vision.git

This will clone the entire repository to your computer.

• To ensure that you have the latest version of the repository, type the following command:

git pull

You are fully prepared to delve into the repository and run the examples. Within the repository, you will discover comprehensive instructions for executing each instance and the required data and models.

Upon cloning this repository, a curated assortment of meticulously documented machine vision examples will be at your disposal, serving as a solid foundation for your ongoing experimentation and development. Whether you are an experienced machine learning practitioner or a novice in the field, this repository offers a valuable resource for delving into the captivating realm of computer vision.

Note: You are welcome to use the code in this repository under the MIT License. However, for commercial use, be sure to consider the original licenses of any libraries included.