Computer Vision on the Raspberry Pi 4

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Matt Scarpino

1:43:50

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[1] Introduction

[1] Getting started with computer vision.mp4

00:48

[2] What you should know.mp4

00:39

[3] Using the exercise files.mp4

02:25

[2] 1. Programming Python on the Raspberry Pi 4

[1] Introducing the Raspberry Pi 4.mp4

02:45

[2] Setting up the environment.mp4

03:42

[3] Using the Thonny IDE.mp4

02:36

[3] 2. OpenCV on the Raspberry Pi

[1] Introducing OpenCV.mp4

03:55

[2] NumPy array operations.mp4

03:31

[3] Running a simple image processing example.mp4

04:56

[4] Theory of convolution.mp4

03:22

[5] Convolution in OpenCV.mp4

04:48

[4] 3. Object Detection

[1] Computing image gradients.mp4

03:12

[2] Forming histograms of gradients (HOGs).mp4

03:47

[3] Computing HOGs in OpenCV.mp4

04:07

[4] Understanding Support Vector Machines (SVMs).mp4

04:22

[5] Detecting objects with HOGs and SVMs.mp4

04:57

[5] 4. Understanding Neural Networks

[1] Introducing neural networks.mp4

03:41

[2] Training neural networks.mp4

03:32

[3] Creating neural networks in OpenCV.mp4

03:02

[4] Classifying irises with a neural network.mp4

04:07

[6] 5. Convolutional Neural Networks (CNNs)

[1] Introducing convolutional neural networks (CNNs).mp4

03:28

[2] Creating CNNs with Keras.mp4

03:15

[3] Training CNNs with TensorFlow.mp4

04:19

[4] Executing models with TensorFlow Lite.mp4

02:11

[5] Recognizing objects with the Raspberry Pi.mp4

04:45

[7] 6. The Raspberry Pi HQ Camera

[1] Introducing the picamera package.mp4

02:40

[2] Accessing a Raspberry Pi camera in Python.mp4

03:23

[3] Object detection with a Raspberry Pi camera.mp4

05:02

[4] Object recognition with a Raspberry Pi camera.mp4

05:15

[8] Conclusion

[1] Next steps.mp4

01:18

Description

More and more applications are using computer vision to detect and recognize objects. These applications usually execute on large computers, but developers can save money and power by running them on single-board computers (SBCs). The Raspberry Pi 4 is one of the most popular SBCs available. It's also the first computer in the Raspberry Pi family powerful enough to execute computer vision applications. Also, the software needed to build these applications can be downloaded freely from the Internet. In this course, instructor Matt Scarpino shows programmers how to write and execute computer vision applications on the Raspberry Pi 4. Matt introduces you to using the Thonny IDE, the OpenCV library, and NumPy array operations. He steps through object detection and neural networks, then explores convolutional neural networks (CNNs), including the Keras package and the TensorFlow package. Matt also walks you through what you can do with a Raspberry Pi HQ camera.

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Computer Vision

Raspberry Pi

Matt Scarpino

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Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.