Computer Vision: Python OCR & Object Detection Quick Starter

Computer Vision Python OCR Object Detection Quick Starter

Description

Computer Vision: Python OCR & Object Detection Quick Starter is an introductory training course for visual character recognition (OCR), image object detection and object detection using Python. This course is the third course of the machine learning training series, the previous course of this series is titled Computer Vision: Face Recognition Quick Starter in Python It has been published. By using the techniques taught in this course, computers will be able to fully recognize and classify an image or to predict what class the object in the image belongs to. By using OCR, you can recognize the texts in the image and convert these texts into a readable format such as text or a document. Object detection and recognition is widely used in all kinds of simple and complex applications such as self-driving cars.

What you will learn in the Computer Vision: Python OCR & Object Detection Quick Starter course:

  • Learning OCR using the Tesseract library
  • Learning image recognition using Keras
  • Learning object allocation using MobileNet SSD
  • Using Mask R-CNN, YOLO, Tiny YOLO from static

Course details

Publisher: Udemy
Instructors: Abhilash Nelson
English language
Training level: introductory to advanced
Number of courses: 49
Duration: 4 hours and 41 minutes

Course topics in 2020-12:

Course prerequisites:

A decent computer configuration (preferably Windows) and an enthusiasm to dive into the world of OCR, Image and Object Recognition using Python

Pictures

Computer Vision Python OCR Object Detection Quick Starter

Sample video

Installation guide

After Extract, view with your favorite Player.

Subtitle: No (based on the course specifications in the picture, this course does not have subtitles.)

Quality: 720p

download link

Download part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 1 GB

Download part 4 – 148 MB

Password file(s): www.downloadly.ir

Size

3.1 GB

4.7/5 – (3743 points)

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