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Book Overview & Buying
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Table Of Contents
Computer Vision: Python OCR and Object Detection Quick Starter
By :
Computer Vision: Python OCR and Object Detection Quick Starter
By:
Overview of this book
This course is a quick starter for anyone who wants to explore optical character recognition (OCR), image recognition, object detection, and object recognition using Python without having to deal with all the complexities and mathematics associated with a typical deep learning process.Starting with an introduction to the OCR technology, you'll get your system ready for Python coding by installing Anaconda packages and the necessary libraries and dependencies.
As you advance, you'll work with convolutional neural networks (CNNs), the Keras library, and pre-trained models such as VGGNet 16 and VGGNet 19, to perform image recognition with the help of sample images. The course then focuses on object recognition and shows you how to use MobileNet-SSD and Mask R-CNN pre-trained models to detect and label objects in a real-time live video from the computer's webcam as well as in a saved video. Toward the end, you'll learn how the YOLO model and the lite version, Tiny YOLO, fasten the process of detecting an object from a single image.
By the end of the course, you'll have developed a solid understanding of OCR and the methods involved and gain the confidence to perform optical character recognition using Python with ease.
All resources and code files for this course are placed here: https://github.com/PacktPublishing/Computer-Vision-Python-OCR-Object-Detection-Quick-Starter
Table of Contents (33 chapters)
Course Introduction and Table of Contents
Introduction to OCR Concepts and Libraries
Setting Up Environment - Anaconda
Python Basics (Optional)
Tesseract OCR Setup
OpenCV Setup
Tesseract Image OCR Implementation
Optional: cv2.imshow() Not Responding Issue Fix
Introduction to CNN - Convolutional Neural Networks - Theory Session
Installing Additional Dependencies for CNN
Introduction to VGGNet Architecture
Image Recognition Using Pre-Trained VGGNet16 Model
Image Recognition Using Pre-Trained VGGNet19 Model
Image Recognition Using Pre-Trained ResNet Model
Image Recognition Using Pre-Trained Inception Model
Image Recognition Using Pre-Trained Xception Model
Introduction to MobileNet-SSD Pre-Trained Model
MobileNet-SSD Object Detection
Mobilenet SSD Real-Time Video
Mobilenet SSD Pre-Saved Video
Mask RCNN Pre-Trained Model Introduction
MaskRCNN Bounding Box Implementation
MaskRCNN Object Mask Implementation
MaskRCNN Real-Time Video
MaskRCNN Pre-saved Video
YOLO Pre-Trained Model Introduction
YOLO Implementation
YOLO Real-Time Video
YOLO Pre-Saved Video
Tiny YOLO Pre-Saved Video
Tiny YOLO Real-Time Video
YOLOv4 - Step 1 - Updating OpenCV Version
YOLOv4 - Step 2 - Object Recognition Implementation
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