Python OCR & Object Detection Quick Starter 2020-5 – Full Version

Description

Computer Vision: Python OCR & Object Detection, Quick Starter, a preliminary training period for character recognition, visual recognition (OCR), detect object in image and object detection using Python is. This course is the third machine learning training course, it is that the previous volume of this set as Computer Vision: Facial Recognition Quickstart in Python Is released. Use the techniques taught in this course, computers will be able to take a picture to diagnose it perfectly and classify it, or predict the existing object in the picture in what class is used. With the use of OCR etc. can be used texts contained in the image are detected, and these texts to format the reading as a text or a document are converted. Discovery and detection of objects for a wide variety of applications, simple and, of course, a complex like خودران cars is used.

Which Computer Vision: Python OCR & Object Detection course, Quick Starter will learn:

  • Learn OCR with the Tesseract library
  • Learn image recognition with Keras
  • Learn تخشیص object using MobileNet SSD
  • Use the R-CNN, YOLO, Tiny YOLO mask of static

Specification period

Publisher: Udemy
teachers: Abhilash Nelson
French language,
level of study: beginner to advanced,
the number of courses: 49
Duration: 4 hours and 41 minutes

This history lesson, 2020-12:

Computer vision, Python, OCR, object detection, quick start content

Prerequisite course:

A decent setup computer (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 Start

sample movie

Installation guide

After extraction, etc. with the reader, the desired view.

Subtitles: No (Based on the periodic profile of the image taken, this course does not have the subtitle is.)

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): ngaur.com

File size

3.1 GB

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