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T&M Python for Computer Vision with OpenCV and Deep Learning

WinSys32

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Python for Computer Vision with OpenCV and Deep Learning | 5.67GB

We'll start the course by learning about numerical processing with the NumPy library and how to open and manipulate images with NumPy. Then will move on to using the OpenCV library to open and work with image basics. Then we'll start to understand how to process images and apply a variety of effects, including color mappings, blending, thresholds, gradients, and more.

Then we'll move on to understanding video basics with OpenCV, including working with streaming video from a webcam. Afterwards we'll learn about direct video topics, such as optical flow and object detection. Including face detection and object tracking.

Then we'll move on to an entire section of the course devoted to the latest deep learning topics, including image recognition and custom image classifications. We'll even cover the latest deep learning networks, including the YOLO (you only look once) deep learning network.

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

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