Learn the basics of computer vision with this comprehensive GitHub project. Includes tutorials and sample code for image processing, object detection, and more. Perfect for beginners looking to dive into the world of CV!
Computer_Vision_Basics is a GitHub project that aims to provide a comprehensive introduction to the field of computer vision. The project includes a variety of tutorials and examples that cover the basics of image processing, object detection, and image recognition.
The project is designed for beginners who are new to the field of computer vision and want to learn about the various techniques and algorithms used in this field. The tutorials are easy to follow and include clear explanations and code snippets to help users understand the concepts.
The project includes a variety of topics such as image processing using OpenCV, object detection using YOLO and Single Shot MultiBox Detector (SSD), and image recognition using convolutional neural networks (CNNs). In addition, the project also covers advanced topics such as deep learning, neural networks and GANs.
The project is implemented using Python and its popular libraries such as TensorFlow, Keras, OpenCV, etc.
The project is actively maintained and new tutorials and examples are added regularly to keep up with the latest developments in the field. If you are new to computer vision and want to learn more about this exciting field, Computer_Vision_Basics is the perfect place to start.