Computer Vision: YOLO Custom Object Detection with Colab GPU: YOLO: Pre-Trained COCO Dataset and Custom-Trained Coronavirus Object Detection Model with Google Colab GPU Training

Abhilash Nelson

€8.99 ~~€93.99~~

Video Feb 2024 3hrs 59mins 1st Edition

Abhilash Nelson

€8.99 ~~€93.99~~

Video Feb 2024 3hrs 59mins 1st Edition

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Key benefits

Get started with the You Only Look Once (YOLO) object detection method
Build models to recognize objects in images and real-time webcam videos
Learn how to prepare custom datasets to build your own coronavirus detection model

Description

Object detection is the most commonly used application of computer vision, which also helps the computer recognize and classify objects inside an image. This video course will help you learn Python-based object recognition methods and develop custom object detection models. The course begins with an introduction to the You Only Look Once (YOLO) object detection system, Python programming, and Convolutional Neural Networks (CNNs). You will learn object detection by installing Anaconda on your computer and the OpenCV library in Python. Next, you will learn to perform object detection and recognition on a single object in an image and on a real-time webcam video using YOLO pre-trained model and Common Objects in Context (COCO) dataset. Moving ahead, you will learn the pros and cons of using a pre-trained dataset model and a custom dataset trained model. In addition, you will get an overview of the free GPU offered by Google Colab. Toward the end, you will learn to create a custom dataset and train a darknet YOLO model to detect coronavirus from an electron microscope image or video output. By the end of this video course, you will develop the skills required to build object recognition models using predefined and custom datasets.

Who is this book for?

If you are a beginner, a developer, or a computer vision enthusiast who wants to develop models for object recognition using Python, then this course is for you. A basic understanding of Python and object recognition is recommended, but not mandatory, to quickly understand the concepts explained.