آموزش پروژه های پیشرفته بینایی کامپوتری

Gain a working knowledge of advanced machine learning
Python’s wealth of powerful packages along with its clear syntax make state-of-the art computer vision and machine learning accessible to developers with a variety of backgrounds. This video course will equip you with the tools and skills to utilize the latest and greatest algorithms in computer vision, making applications that weren’t possible until recent years.
In this course, you’ll continue to use TensorFlow and extend it to generate full captions from images. Later, you’ll see how to read text from license plates from real-world images using Google’s Tesseract Software. Finally, you’ll see how to track human body poses using “DeeperCut” within TensorFlow.
At the end of this course, you’ll develop an application that can estimate human poses within images and will be able to take on the world with best practices in computer vision with machine learning.
The code bundle for this video course is available at - https://github.com/PacktPublishing/Advanced-Computer-Vision-Projects
Style and Approach
A project-based approach that will enable you to rapidly deploy advanced machine learning computer vision solutions in your work.
Released: Friday, August 31, 2018
Image Captioning with TensorFlow
The Course Overview
Image Captioning Introduction
Google Brain im2txt Captioning Model
Running Our Captioning Code in Jupyter
Retraining the Model
Reading License Plates with OpenCV
Steps to Read License Plates
Plate Utility Functions
Finding Plate Characters
Finding and Reading License Plates
Human Pose Estimation with TensorFlow
Pose Estimation with DeeperCut and ArtTrack
Single-Person Pose Detection
Multi-Person Pose Detection
Videos and Retraining