Tutorial

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Table Of Contents

1. Premise
- 1.1STEAM and Raspberry Pi
- 1.2About The Documentation
2. Raspberry Pi System Installation and Developmen
- 2.1 Install An Operating System for The Raspberry
- 2.2 Enable SSH Server of Raspberry Pi
  - 2.2.1 Method A: Enable SSH with Peripherals
  - 2.2.2 Method A: Enable SSH without Peripherals
- 2.3 Configure WiFi on Raspberry Pi
  - 2.3.1 Method A: WiFi Connection with Peripherals
  - 2.3.2 Method A: WiFi Connection without Periphera
3 Log In to The Raspberry Pi and Install The App
- 3.1 Log into Raspberry Pi (Windows 10)
- 3.2 Log into Raspberry Pi (Linux or Mac OS)
- 3.3 Log into Raspberry Pi (Windows 8 or Previous V
- 3.4 Download Program of The Raspberry Pi Robot
- 3.5 Install Corresponding Dependent Libraries
- 3.6 Run the Raspberry Pi Robot's Program
4 Assembly and Precautions
- 4.1 Structure Assembly
- 4.2 Tips for Structural Assemblage
- 4.3 Tips for Power Provision
5 Controlling Robot via WEB App
6 Common Problems and Solutions(Q&A)
7 Set The Program to Start Automatically
- 7.1 Set The Specified Program to Run Automatically
- 7.2 Change The Program That Starts Automatically
8 Remote Operation of Raspberry Pi Via MobaXterm
9 How to Control WS2812 RGB LED
10 How to Control The Servo
- 10.1 Control The Steering Gear to Rotate to A Cert
- 10.2 Control The Slow Motion of The Steering Gear
- 10.3 Non-blocking Control
11 How to Control DC Motor
12 Ultrasonic Module
13 Line Tracking
14 Make A Police Light or Breathing Light
- 14.1 Multi-threading Introduction
- 14.2 Realization of Police Lights / Breathing Ligh
- 14.3 Warning Lights or Breathing Lights in Other P
15 Real-Time Video Transmission
16 Automatic Obstacle Avoidance
17 Why OpenCV Uses Multi-threading to Process Vide
- 17.1 Single Thread Processing of Video Frames
- 17.2 Multi-thread Processing of Video Frames
18 OpenCV Learn to Use OpenCV
19 Using OpenCV to Realize Color Recognition and T
- 19.1 Color Recognition and Color Space
- 19.2 Process of Color Identifying and Tracking
- 19.3 Specific Code
- 19.4 HSV Color Component Range in OpenCV
20 Machine Line Tracking Based on OpenCV
- 20.1 Visual Line Inspection Process
- 20.2 Specific Code
21 Create A WiFi Hotspot on The Raspberry Pi
22 Install GUI Dependent Item under Window
- 22.1 Install GUI Dependencies
23 How to Use GUI
24 Control The WS2812 LED via GUI
25 Real-time Video Transmission Based on OpenCV
26 Use OpenCV to Process Video Frames on The PC
27 Enable UART
- 27.1 Mini UART and CPU Core Frequency
- 27.2 Disabling Linux's Use of Console UART
- 27.3 UART Output on GPIO Pins
- 27.4 UARTs and Device Tree
- 27.5 Relevant Differences Between PL011 and Mini U
28 Control Your AWR with An Android Device
Conclusion

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'''

source = cv2.erode(source, None, iterations=6)

'''

Display image

'''

cv2.imshow("Stream", source)

'''

Generally, waitKey () should be used after imshow () to leave time for image drawing, otherwise the window will

appear unresponsive and the image cannot be displayed

'''

cv2.waitKey(1)