Computer Vision: Python OCR & Object Detection Quick Starter 4.4 (19 ratings) Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
What you’ll learn
- Optical Character Recognition with Tesseract Library, Image Recognition using Keras, Object Recognition using MobileNet SSD, Mask R-CNN, YOLO, Tiny YOLO from static image, realtime video and pre-recorded videos using Python
- A decent configuration computer (preferably Windows) and an enthusiasm to dive into the world of OCR, Image and Object Recognition using Python
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.
Image Recognition, Object Detection, Object Recognition and also Optical Character Recognition are among the most used applications of Computer Vision.
Using these techniques, the computer will be able to recognize and classify either the whole image, or multiple objects inside a single image predicting the class of the objects with the percentage accuracy score. Using OCR, it can also recognize and convert text in the images to machine readable format like text or a document.
Object Detection and Object Recognition is widely used in many simple applications and also complex ones like self driving cars.
This course will be a quick starter for people who wants 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 typical Deep Learning process.
Let’s now see the list of interesting topics that are included in this course.
At first we will have an introductory theory session about Optical Character Recognition technology.
Then we will try the ResNet pre-trained model included with the Keras