Enroll Course: https://www.udemy.com/course/computer-vision-python-ocr-object-detection-quick-starter/
Are you fascinated by the power of computers to ‘see’ and understand the world around them? Dive into the exciting realm of Computer Vision with Udemy’s ‘Computer Vision: Python OCR & Object Detection Quick Starter’ course. This comprehensive yet accessible course is your perfect entry point into Optical Character Recognition (OCR) and Object Detection, two of the most impactful applications of computer vision.
This course is designed to be a quick starter, bypassing the steep learning curve often associated with deep learning complexities and heavy mathematics. Whether you’re new to Python or looking to expand your skillset, this course provides a solid foundation. It begins with essential Python programming basics, covering assignments, flow control, functions, and data structures, ensuring you’re well-prepared for the practical coding sessions.
The journey into OCR starts with understanding the technology, followed by setting up your development environment with Anaconda. You’ll then install and utilize powerful libraries like Tesseract for OCR, OpenCV for general computer vision tasks, and Pillow for image manipulation. The course guides you through the OCR process with hands-on coding and testing on example images, converting text within images into machine-readable formats.
Moving on to image and object recognition, the course introduces Convolutional Neural Networks (CNNs) and leverages the Keras library. You’ll work with pre-trained models like VGGNet (both VGG16 and VGG19), ResNet, and Inception, learning to classify entire images based on their primary content. This section provides a clear understanding of how these powerful models function without requiring you to train them from scratch.
The course then transitions to the more advanced area of Object Detection, where you’ll learn to identify and locate multiple objects within a single image. You’ll explore the MobileNet-SSD model for efficient detection, understanding its dataset and implementing it to draw bounding boxes and labels around detected objects. The practical application extends to real-time object detection from your webcam and processing pre-saved video files.
For even more sophisticated object recognition, the course delves into Mask-RCNN, which not only detects objects but also generates precise masks outlining their shapes. You’ll implement Mask-RCNN for both image and video analysis, visualizing detailed segmentation masks. The course also addresses the trade-offs between speed and accuracy, introducing YOLO and Tiny YOLO as optimized solutions for real-time performance, allowing you to compare their effectiveness.
All necessary code, images, and libraries are provided, empowering you to use them in your own projects. Upon completion, you’ll receive a certificate to enhance your professional portfolio. If you’re ready to harness the power of computer vision and build intelligent applications, this course is an excellent starting point. Happy learning!
Enroll Course: https://www.udemy.com/course/computer-vision-python-ocr-object-detection-quick-starter/