Enroll Course: https://www.udemy.com/course/computer-vision-python-ocr-object-detection-quick-starter/
Are you fascinated by how computers can ‘see’ and interpret the world around them? Do you want to dive into the exciting fields of Optical Character Recognition (OCR) and Object Detection using Python, without getting bogged down in complex mathematics? Then look no further than Udemy’s ‘Computer Vision: Python OCR & Object Detection Quick Starter’ course.
This course, the third in a series on Computer Vision, serves as an excellent entry point for beginners. It demystifies powerful applications like Image Recognition, Object Detection, and OCR, enabling computers to classify images, identify multiple objects within them, and even convert text from images into editable formats. From the foundational concepts to practical implementation, this course guides you every step of the way.
The journey begins with an introduction to OCR technology, followed by setting up your development environment with Anaconda. For those new to Python, the course offers essential programming basics, covering assignments, flow control, functions, and data structures. You’ll then learn to install and utilize crucial libraries like Tesseract for OCR, OpenCV for broader computer vision tasks, and Pillow for image manipulation.
The course then transitions to image recognition using Convolutional Neural Networks (CNNs). You’ll explore pre-trained models within Keras, including VGGNet (both 16 and 19), ResNet, Inception, and Xception. These models allow you to classify entire images based on their primary object, and the course provides hands-on coding examples to test their predictions.
Moving beyond single-image classification, the course delves into object detection, where you can identify and locate multiple objects within a single image. You’ll learn about the MobileNet-SSD model for detecting objects and drawing bounding boxes, and even apply this to live webcam feeds and pre-saved videos. For more precise object localization, the course introduces Mask-RCNN, which not only detects objects but also generates masks for their exact shapes, offering a more detailed understanding of the scene. This is also demonstrated with live and saved video inputs.
Finally, the course addresses the trade-off between speed and accuracy in object detection by introducing YOLO (You Only Look Once) and its lighter counterpart, Tiny YOLO. You’ll implement these models for both image and video analysis, comparing their performance to find the optimal balance for your needs.
With all necessary code, images, and libraries provided, and the freedom to use them in your own projects, this course offers immense practical value. Upon completion, you’ll receive a certificate to enhance your professional portfolio. ‘Computer Vision: Python OCR & Object Detection Quick Starter’ is a highly recommended course for anyone looking to quickly gain practical skills in these cutting-edge computer vision techniques.
Enroll Course: https://www.udemy.com/course/computer-vision-python-ocr-object-detection-quick-starter/