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Raspbot📖
1.First Trial and Installation
  • 1.1 Installation video
  • 1.2 First Trial
2.Remote control course
  • 2.1 APP control car
  • 2.2 IR control car
3.Preparation
  • 3.1 Preparation
  • 3.2 Run a code on JupyterLab
  • 3.5 TF card expand capacity
4.OpenCV Basic course
A.Getting started with OpenCV
  • 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
  • 6.Picture Rotation
  • 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
E.OpenCV machine learning
  • 1.KNN recognition of handwritten numbers
  • 2.CNN recognition of handwritten numbers
  • 3.SVM recognition of handwritten numbers
5.Hardware Control course
  • 5.1 Drive buzzer
  • 5.2 Drive motor
  • 5.3 Drive servo
  • 5.4 Ultrasonic ranging
  • 5.5 Ultrasonic avoid
  • 5.6 Ultrasonic+IR avoid
  • 5.7 Tracking
  • 5.8 Restricting
  • 5.9 Drive LED
  • 5.10 IR control test
  • 5.11 IR control car
6.AI vision course
  • 6.1 Driver camera
  • 6.2 Color recognition
  • 6.3 HSV value test
  • 6.4 Camera color tracking
  • 6.5 Car color tracking
  • 6.6 Tensorflow object recognition
  • 6.7 QR code recognition
  • 6.8 QR code control
  • 6.9 Face detection
  • 6.10 Face tracking
  • 6.11 Autopilot
7.Battery and charging
  • Battery and charging
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  • Code
  • Download image
  • Instruction manual
  • More Annex
Download ZIP
FAQ
  • 1、Raspbot-Raspberry Pi 4b version desktop connection WiFi method
  • 2、Can't connect your home WiFi
  • 3、How to check IIC function on Raspbot
  • 4、Gesture recognition cannot work normally.
  • 5、How to write image file into SD card

Welcome to Raspbot repository

4.Drawing line segment


When using OpenCV to process an image, sometimes, we need to draw line segments, rectangles, etc. on the image. OpenCV uses function line (dst, pt1, pt2, color, thickness = None, lineType = None, shift = None) to draw line segments.

Parameter Description

l dst: output image.

l pt1, pt2: required parameters, pt1 is the starting point, pt2 is the ending point.

l color: required parameters, be used to set color of line segment.

l Thickness: optional parameters, be used to set weight of line segment.

lineType: optional parameters, be used to set the type of line segment, 8 (8 adjacent connection line-default), 4 (4 adjacent connection line) and cv2.LINE_AA are anti-aliased

Code path:

/home/pi/Yahboom_Project/1.OpenCV_course/03IP_Draw_text_line_segments/ 04_Drawing line segment.ipynb

import cv2
import numpy as np
import matplotlib.pyplot as plt
 
newImageInfo = (600, 600, 3)
dst = np.zeros(newImageInfo,np.uint8)
 
# line
# Drawing line segment 1 dst 2 begin 3 end 4 color
cv2.line(dst, (100,100), (450,300), (0,0,255))
# 5 line w
cv2.line(dst, (100,200), (400,200), (0,255,255), 10)
# 6 line type
cv2.line(dst, (100,300), (400,300), (0,255,0), 10, cv2.LINE_AA)
 
cv2.line(dst, (200,150), (50,250), (25,100,255))
cv2.line(dst, (50,250), (400,380), (25,100,255))
cv2.line(dst, (400,380), (200,150), (25,100,255))
 
# cv2.imshow('dst',dst)
# cv2.waitKey(0)
dst = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB)
plt.imshow(dst)
    plt.show()

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

image.png 



Edge detection
Drawing rectangle circle

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