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Raspberry Pi 4B📖
1.Preparation before use
  • 1.1 Download image
  • 1.2 Write image into SD card
  • 1.3 Start up Raspberry Pi
  • 1.4 Linux common commands
  • 1.5 Precautions
2.Basic course
  • 2.1 Log into Raspberry Pi system
  • 2.2 Change password and root account
  • 2.3 Remote transfer file
  • 2.4 Backup image file
  • 2.5 Fixing Raspberry Pi IP
  • 2.6 Set screen keep on
  • 2.7 Get Pi temperature
  • 2.8 Connect WIFI
  • 2.9 Modify Pi time
  • 2.10 Set the boot self-starting program
3.Expand course
  • 3.1 Serial port communicates with external devices
  • 3.2 2.Serial port login Pi
  • 3.3 Configured as a router
  • 3.4 Install Jupyter Lab
  • 3.5 Install Jupyter Widgets
  • 3.6 More Detail for Widgets
  • 3.7 Install OpenCV
  • 3.8 Install Tensorflow
4.Programming course
C language
  • 1.Development environment
  • 2.Print Hello World
  • 3.Pin output level
  • 4.Read pin level
  • 5.PWM output
Python language
  • 1.Development environment
  • 2.Print basic usage
  • 3.Pin output level
  • 4.Read pin level
  • 5.PWM output
5.AI vision course
A.Getting started with OpenCV
  • 6.Picture Rotation
  • 1.Introduction of OpenCV
  • 2.OpenCV image read and display
  • 3.OpenCV image write
  • 4.OpenCV image quality
  • 5.OpenCV pixel operation
B.OpenCV Geometric transformat
  • 1.Picture Zoom
  • 2.Picture Cut
  • 3.Picture Shift
  • 4.Picture Mirroring
  • 5.Affine Map
  • 7.Perspective Transformation
C.OpenCV picture processing
  • 1.Grayscale processing
  • 2.Image Binarization
  • 3.Edge detection
  • 4.Drawing line segment
  • 5.Drawing rectangle circle
  • 6.Drawing text picture
D.OpenCV image beautification
  • 1.Histogram of color pictures
  • 2.Histogram equalization
  • 3.Image restoration
  • 4.Brightness enhancement
  • 5.Skin whitening
  • 6.Gaussian mean filtering
  • 7.Median filtering
F.AI Advanced Course (Ubuntu system)
  • 1. QR code
  • 2. Human posture estimation
  • 3. Target detection
  • 4. Mediapipe development
  • 5. yolov4-tiny
E.Install TensorFlow
  • Install TensorFlow
6.ROS1 coursenew
Basic Course
  • 1.ROS introduction
  • 2.Project file structure
  • 3.Common commands and tools
  • 4.Publisher
  • 5.Subscribers
  • 6.Customize topic messages and use
  • 7.Client
  • 8.Server
  • 9.Custom service messages and usage
  • 10.TF release and monitoring
Visual Image Processing
  • 1. AR vision
  • 2. AR QR code
  • 3. ROS+Opencv foundation
  • 4. ROS+Opencv application
  • 5. MediaPipe development
7.ROS2 coursenew
Docker Course
  • 1.Overview and installation
  • 2.Common commands
  • 3.Understand and publish images
  • 4.Hardware interaction data processing
  • 5.Enter docker container
  • 6.Update docker images
Basic Course
  • 1.Introduction to ROS2
  • 2.Commands and tools
  • 3.ROS2 Topic communications
  • 4.ROS2 service communications
  • 5.ROS2launch file starts
OpenCV Course
  • 1.OpenCV Basic Course
  • 2.ROS+opencv application
  • 3.QR code recognition
  • 4.AR Vision
  • 5.Mediapipe
8.Accessories installation
  • 1. Installation of heat sink
  • 2. Wiring of cooling fan
  • 3. Double fan armor case Installation
  • 4. Argon NEO aluminum case installation
  • 5. Argon ONE aluminum alloy case installation
  • 6. Metal shell with built-in fan installation
  • 7. Acrylic case with cooling fan installation
  • 8. White-red ABS protective case installation
Download
  • Tools
  • C_code
  • Python code
  • ROS System
Download ZIP

Welcome to Raspberry Pi 4B repository

6.Drawing text picture

Drawing text picture

Function: cv2.putText(img, str, origin, font, size,color,thickness)

The parameters are: picture, need add text, upper left corner coordinates (integer), font, size of font, color, thickness of font.

Code:

import cv2 
import numpy as np
 
img = cv2.imread('yahboom.jpg',1)
font = cv2.FONT_HERSHEY_SIMPLEX
 
cv2.rectangle(img,(200,100),(500,400),(0,255,0),3)
# 1 dst 2need add text 3coordinate 4 5 size of font 6 color 7 thickness 8 line type
cv2.putText(img,'Yahboom',(250,50),font,1,(200,200,0),2,cv2.LINE_AA)
# cv2.imshow('src',img)
# cv2.waitKey(0)

import matplotlib.pyplot as plt
 
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
plt.imshow(img)
plt.show()

After running the following program, a picture will be displayed in the jupyterLab control interface, as shown below.

image.png 



Drawing rectangle circle
Histogram of color pictures

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