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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

1.Picture Zoom


Picture Zoom

In OpenCV, the function to achieve picture zoom:

cv2.resize(InputArray src, OutputArray dst, Size, fx, fy, interpolation)

Code:

About parameter:

InputArray src

Input picture

OutputArray dst

Output picture

Size

Size of output picture

fx, fy

Zoom factor along x-axis and y-axis

interpolation

Interpolation method

The interpolation method used by the interpolation option:

INTER_NEAREST

Nearest neighbor interpolation

INTER_LINEAR

Bilinear interpolation(default setting)

INTER_AREA

Using the pixel region relationship to complete to re-sampling

INTER_CUBIC

Bicubic interpolation of 4x4 pixel neighborhood

INTER_LANCZOS4

Lanczos interpolation of 8x8 pixel neighborhood

 Note:

1.Size format: (width, height)

2.The default interpolation method: bilinear interpolation

# 1 load 2 info 3 resize 4 check
import cv2
import matplotlib.pyplot as plt  #2D drawing library for Python
 
# Read the original picture
img = cv2.imread('yahboom.jpg')
# Print out the picture size
print(img.shape)
# Assign the image height and width to x and y respectively
x, y = img.shape[0:2]
 
# Display original picture
# cv.imshow('OriginalPicture', img)
 
# Zoom to the original half, the output size format is (width, height)
img_test1 = cv2.resize(img, (int(y / 2), int(x / 2)))
# cv2.imshow('resize0', img_test1)
# cv2.waitKey()
 
# Nearest neighbor interpolation to zoom
# Zoom to the original quarter
img_test2 = cv2.resize(img, (0, 0), fx=0.25, fy=0.25, interpolation=cv2.INTER_NEAREST)
# cv.imshow('resize1', img_test2)
# cv.waitKey()
# cv.destroyAllWindows()
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
dst1 = cv2.cvtColor(img_test1, cv2.COLOR_BGR2RGB)
dst2 = cv2.cvtColor(img_test2, cv2.COLOR_BGR2RGB)
 
# Display original picture
plt.imshow(img)
plt.show()

After the program is executed, we can see that the image is 800 * 800. As shown below.

image.png 

# Display zoom 1/2
plt.imshow(dst1)
plt.show()

After the program is executed, we can see that the image is 400 * 400. zoom 1/2 As shown below.

image.png 

# Display zoom 1/4 Nearest neighbor interpolation to zoom
plt.imshow(dst2)
plt.show()

After the program is executed, we can see that the image is 200 * 200, zoom 1/4. As shown below.

image.png 

Next, we will introduce matplotlib: 2D plotting library for Python

Tutorial: https://www.runoob.com/numpy/numpy-matplotlib.html

import numpy as np 
from matplotlib import pyplot as plt 
 
x = np.arange(1,11) 
y =  2 * x +  5 
plt.title("Matplotlib demo") 
plt.xlabel("x axis caption") 
plt.ylabel("y axis caption") 
plt.plot(x,y) 
plt.show()

image.png 



OpenCV pixel operation
Picture Cut

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