Computer Vision: Python OCR and Object Detection Quick Starter [Video]
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Free ChapterCourse Introduction and Table of Contents
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Introduction to OCR Concepts and Libraries
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Setting Up Environment - Anaconda
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Python Basics (Optional)
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Tesseract OCR Setup
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OpenCV Setup
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Tesseract Image OCR Implementation
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Optional: cv2.imshow() Not Responding Issue Fix
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Introduction to CNN - Convolutional Neural Networks - Theory Session
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Installing Additional Dependencies for CNN
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Introduction to VGGNet Architecture
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Image Recognition Using Pre-Trained VGGNet16 Model
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Image Recognition Using Pre-Trained VGGNet19 Model
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Image Recognition Using Pre-Trained ResNet Model
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Image Recognition Using Pre-Trained Inception Model
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Image Recognition Using Pre-Trained Xception Model
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Introduction to MobileNet-SSD Pre-Trained Model
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MobileNet-SSD Object Detection
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Mobilenet SSD Real-Time Video
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Mobilenet SSD Pre-Saved Video
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Mask RCNN Pre-Trained Model Introduction
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MaskRCNN Bounding Box Implementation
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MaskRCNN Object Mask Implementation
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MaskRCNN Real-Time Video
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MaskRCNN Pre-saved Video
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YOLO Pre-Trained Model Introduction
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YOLO Implementation
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YOLO Real-Time Video
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YOLO Pre-Saved Video
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Tiny YOLO Pre-Saved Video
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Tiny YOLO Real-Time Video
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YOLOv4 - Step 1 - Updating OpenCV Version
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YOLOv4 - Step 2 - Object Recognition Implementation
About this
video
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
- Publication date:
- October 2020
- Publisher
- Packt
- Duration
- 4 hours 41 minutes
- ISBN
- 9781800567481