Computer Vision: Python OCR & Object Detection Quick Starter
Welcome to my new course 'Optical Character Recognition and Object Recognition Quick Start with Python'. This is the third course from my Computer Vision series.
What is Computer Vision?
Computer Vision is an interdisciplinary scientific field that deals with how computers can be made to gain a high-level understanding from digital images or videos.
It involves the development of a theoretical and algorithmic basis to achieve automatic visual understanding. Computer Vision seeks to use the images and videos acquired by the cameras and process them with the use of image processing, pattern recognition, and deep learning so that decisions can be made based on the input that is available.
What is Computer Vision used for?
Computer Vision is one of the most trending fields in the computer science industry and has a wide range of applications across various fields. Some common applications of Computer Vision include:
- Optical Character Recognition and Image Recognition
- Object Detection and Object Recognition
- Facial Recognition and Gesture Recognition
- Self-Driving Cars
- Robotics
- Medical Imaging
- Satellite Imaging
- Surveillance
Course Overview
This course will be a quick starter for people who want to dive into Optical Character Recognition, Image Recognition, and Object Detection using Python without having to deal with all the complexities and mathematics associated with the typical Deep Learning process. The course is titled "Computer Vision: Python OCR & Object Detection Quick Starter."
What is Optical Character Recognition?
Optical Character Recognition or OCR is a process of converting machine-printed or handwritten text into machine-encoded text. OCR has wide applications in the field of data entry, document digitization, and text-to-speech conversion.
The course first introduces the foundational concepts of Optical Character Recognition technology, including how it works and its applications. The first few modules of the course cover the theory and hands-on programming with Tesseract OCR.
What is Image Recognition?
Image Recognition is the ability to identify the contents of an image and often encompasses classification, segmentation, and object detection. Object detection involves locating an object within an image and drawing a bounding box around it.
The course includes an introduction to Convolutional Neural Networks(CNN) and how these neural networks can be used for Image Recognition. It also walks you through the installation of the Keras library, which will be used for Image Recognition models.
The course includes modules to introduce the built-in pre-trained models that are included in Keras. Models include VGGNet, ResNet, Inception, and Xception, among others.
What is Object Detection?
Object Detection is the process of recognizing and locating an object within an image or video. Object detection goes beyond Image Recognition in that it can detect and label multiple objects present in a single image.
The course includes modules to implement Object Detection using MobileNet-SSD pre-trained models and the Mask-RCNN pre-trained Model from real-time webcam video and pre-saved video files. Moreover, it includes the YOLO model for object detection from a single image and a real-time webcam.
Course Content and Approach
The course comprises various learning modules and programs to improve your understanding. These modules are designed to provide foundational knowledge and hands-on experience so that you can develop your own OCR, Object Detection, and Object Recognition code.
The course includes a step-by-step approach in which the instructor will guide you through the essential programming concepts, libraries, and dependencies to enable you to implement these Computer Vision applications. The course will walk you through sample test cases to ensure that you grasp each concept before moving to the next one.
The course is ideal for individuals who want to learn the practical implementation of Computer Vision and how it pertains to the field of OCR, Object Detection, and Object Recognition.
The Instructor
The instructor has over 20 years of experience in Computer Vision and has designed this course in a way that is easy to understand and implement.
The instructor takes a hands-on teaching approach that provides students with the necessary coding skills to develop their own applications using Python. With the instructor's guidance and mentorship, students will be able to implement OCR, Object Detection, and Object Recognition in their own projects with ease.
Course Feedback and Reviews
The course has a high rating aggregate of 4.64465 and has been reviewed by 447 students.
Students who have taken this course have found it to be very helpful, especially for beginners who have little experience with Python programming language and Computer Vision. The program's simple approach and practical examples have made it very easy for students to grasp the concepts of OCR, Object Detection, and Object Recognition.
Course Resources and Materials
The course includes all the necessary resources and materials that you will need to complete each module. These resources are uploaded and shared in a folder that will be provided to students upon registration.
You are free to use the content, code, and libraries in your own projects with no questions asked. Upon the completion of this course, you will receive a course completion certificate that you can add to your resume or portfolio.
The Bottom Line
The Computer Vision: Python OCR & Object Detection Quick Starter course is an excellent starting point for anyone who wishes to learn about and implement Computer Vision techniques in their projects.
The course is designed and taught by an expert in the field, and each module is designed to provide hands-on experience to ensure that you develop the necessary skills to implement OCR, Object Detection, and Object Recognition with Python.
Upon completion of the course, you will have the necessary skills to develop your own OCR, Object Detection, and Object Recognition applications and take the first step towards a rewarding career in Computer Vision.
