Python for Computer Vision with OpenCV and Deep Learning

BESTSELLER | Video: AVC AVC 1280×720 | Audio: AAC 48KHz 2ch | Duration: 13.5 Hours | Lec: 87 | 5.41 GB | Genre: eLearning | Language: English | Sub: English

What you’ll learn
Understand basics of NumPy
Manipulate and open Images with NumPy
Use OpenCV to work with image files
Use Python and OpenCV to draw shapes on images and videos
Perform image manipulation with OpenCV, including smoothing, blurring, thresholding, and morphological operations.
Create Color Histograms with OpenCV
Open and Stream video with Python and OpenCV
Detect Objects, including corner, edge, and grid detection techniques with OpenCV and Python
Create Face Detection Software
Segment Images with the Watershed Algorithm
Track Objects in Video
Use Python and Deep Learning to build image classifiers
Work with Tensorflow, Keras, and Python to train on your own custom images.

Requirements
Must have clear understanding of Python Basics
Windows 10 or MacOS or Ubuntu
Must have Install Permissions on Computer
WebCam if you want to learn the video streaming content

Description
This course covers all this and more, including the following topics:

NumPy
Images with NumPy
Image and Video Basics with NumPy
Color Mappings
Blending and Pasting Images
Image Thresholding
Blurring and Smoothing
Morphological Operators
Gradients
Histograms
Streaming video with OpenCV
Object Detection
Template Matching
Corner, Edge, and Grid Detection
Contour Detection
Feature Matching
WaterShed Algorithm
Face Detection
Object Tracking
Optical Flow
Deep Learning with Keras
Keras and Convolutional Networks
Customized Deep Learning Networks
State of the Art YOLO Networks
and much more!

Who is the target audience?
Python Developers interested in Computer Vision and Deep Learning. This course is not for complete python beginners.

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