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NUWA-HP60C Depth Camera📖
1.ROS1-Depth camera usage course
  • 1. Environment Construction
  • 2. Camera recording video
2.ROS1-ROS+OpenCV application
  • 1.ROS+Opencv Basics
  • 2.Face recognition
  • 3.Harris corner detection
  • 4. Target Tracking Algorithm
  • 5. Contour moment
  • 6. Polygonal Outlines
  • 7. Discrete Fourier Transform Algorithm
  • 8. Edge Detection Algorithm
  • 9. Face Detection Algorithm
  • 10. Optical flow detection algorithm
  • 11. Contour Detection
  • 12. General contour detection
  • 13. Feature point tracking
  • 14.HLS Color Filtering
  • 15. Hough circle detection
  • 16. Hough Line Detection
  • 17.HSV color filtering
  • 18.LK optical flow algorithm
  • 19. Human Detection Algorithm
  • 20. Phase-correlated displacement detection
  • 21. Image pyramid sampling algorithm
  • 22.RGB color filtering
  • 23. Clear background detection algorithm
  • 24. Streamlining the optical flow algorithm
  • 25. Simple Filter
  • 26. Threshold Image Processing
  • 27. Watershed segmentation algorithm
3.ROS1-Mediapipe course
  • 1.Hand detection
  • 2.Posture detection
  • 3.Overall detection
  • 4.Face Mesh
  • 5.Face recognition
  • 6.Face effects
  • 7.Face Detection
  • 8.3D Object Recognition
  • 9.Paintbrush
  • 10.Finger control
  • 11.Gesture Recognition
4.ROS1-Depth camera application course
  • 1. Camera calibration
  • 2. QR code
  • 3. Human Pose Estimation
  • 4. Target detection
  • 5. Point cloud data viewing
  • 6. AR Vision
  • 7.AR QR code tracking
  • 8. Color Tracking
  • 9. Object Tracking
5.ROS1-Linux basic course
  • 1.Introduction to Linux system
  • 2.Ubuntu file system
  • 3.Ubuntu common commands
  • 4.Ubuntu common editors
  • 5.Ubuntu software operation commands
  • 6.Virtual machine installation
  • 7.SSH remote control
  • 8.VNC remote control
  • 9.Transfer files remotely
  • 10.Driver library and communication
  • 11.Static IP and hotspot mode
  • 12.Bind device ID
  • 13.Capacity expansion and resource allocation
  • 14.Update system software sources
  • 15.Set root user password
  • 16.sudo free password
  • 17.Connect to WiFi network
  • 18.View system version
  • 19.Customized service management
  • 20.Back up system image
6.ROS1-OpenCV course
  • 1.Opencv Source CV Introduction
  • 2.Image reading and display
  • 3.Picture writing
  • 4.Picture Quality
  • 5.Pixel Operation
  • 6.Picture scaling
  • 7.Picture cutting
  • 8.Picture translation
  • 9.Picture mirroring
  • 10.Affine transformation
  • 11.Picture rotation
  • 12.Perspective transformation
  • 13.Grayscale processing
  • 14.Image binarization
  • 15.Edge detection
  • 16.Line segment drawing
  • 17.Rectangle and circle drawing
  • 18.Text and picture drawing
7.ROS1 basic course
  • 1.ROS introduction
  • 2.ROS installation
  • 3.ROS common command tools
  • 4.ROS workspace
  • 5.ROS function package
  • 6.ROS node
  • 7.ROS topic publisher
  • 8.ROS topic subscribers
  • 9.ROS service client
  • 10.ROS service server
  • 11.ROS action client
  • 12.ROS action server
  • 13.ROS custom message reception
  • 14.ROS-launch file
  • 15.ROS-TF transformation
  • 16.ROS parameter service
  • 17.ROS-rviz use
  • 18.ROS-rqt tool usage
  • 19.Topic message recording and playback
  • 20.urdf model introduction
  • 21.gazebo introduction
  • 22.ROS distributed communication
8.ROS2-Depth Camera Application Course
  • 1. Use of Depth Camera
  • 2. Camera internal parameter calibration
  • 3. Color tracking
  • 4. KCF Object Tracking
  • 5. ORBSLAM2 Basics
  • 6. ORB_SLAM2 PCL Mapping
  • 7. ORB_SLAM2 Octomap Mapping
9.ROS2-OpenCV course
  • 1. ROS+OpenCV application
  • 2. QR code creation and recognition
  • 3. AR Vision
10.ROS2-Mediapipe course
  • 1.Hand detection
  • 2.Posture detection
  • 3.Overall detection
  • 4.Face Mess
  • 5.Face recognition
11.ROS2 basic course
  • 1.Introduction to ROS2
  • 2.ROS2 install Humble
  • 3.ROS2 development environment
  • 4.ROS2 workspace
  • 5.ROS2 function package
  • 6.ROS2 node
  • 7.ROS2 topic communication
  • 8.ROS2 service communication
  • 9.ROS2 action communication
  • 10.ROS2 custom interface message
  • 11.ROS2 parameter service case
  • 12.ROS2 meta-function package
  • 13.ROS2 distributed communication
  • 14.ROS2 DDS
  • 15.ROS2 time related API
  • 16.ROS2 common command tools
  • 17.ROS2 rviz2 use
  • 18.ROS2 rqt toolbox
  • 19.ROS2 Launch startup file configuration
  • 20.ROS2 recording and playback tool
  • 21.ROS2 URDF model
  • 22.ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
5.Bracket installation video
  • Bracket installation video
Download
  • ROS1_VM
  • ROS2_VM
  • ROS1_Code
  • ROS2_Code
  • DataSheet
  • 3D_Model_File
  • Windows Software
  • ROS2_Basic_VM
Download ZIP

Welcome to NUWA-HP60C Depth Camera repository

17.Rectangle and circle drawing

Rectangle and circle drawing

1. Drawing of rectangle

rectangle(img, pt1, pt2, color, thickness=None, lineType=None, shift=None)

Parameter Description:

img: canvas or carrier image.

pt1, pt2: required parameters. The vertices of the rectangle represent the vertex and the diagonal vertex respectively, that is, the upper left corner and the lower right corner of the rectangle (these two vertices can determine a unique rectangle)

color: required parameter. Used to set the color of the rectangle

thickness: optional parameter. Used to set the width of the rectangular side. When the value is a negative number, it means filling the rectangle.

lineType: optional parameter. Used to set the type of line segment, optional 8 (8 adjacent connecting lines - default), 4 (4 adjacent connecting lines) and cv2.LINE_AA is anti-aliasing

2. Drawing of circles

cv2.circle(img, center, radius, color[,thickness[,lineType]])

Parameter Description:

img: canvas or carrier image

center: is the coordinate of the center of the circle, format: (50,50)

radius: radius

color: color

thickness: Line thickness. Defaults to 1. If -1, fill solid.

lineType: line type. The default is 8, connection type. The following table explains

ParametersDescription
cv2.FILLEDfill
cv2.LINE_44 connection types
cv2.LINE_88 connection type
cv2.LINE_AAAnti-aliasing, this parameter will make the lines smoother

3. Draw an ellipse

cv2.ellipse(img, center, axes, angle, StartAngle, endAngle, color[,thickness[,lineType]])

center: center point of the ellipse, (x, x)

axes: refers to the short radius and long radius, (x, x)

angle: refers to the angle of counterclockwise rotation

StartAngle: The angle of the starting angle of the arc

endAngle: the angle of the arc’s end angle

For img and color, please refer to the description of the circle.

# The fifth parameter refers to the angle at which the drawing starts counterclockwise, and the sixth parameter refers to the angle at which the drawing ends counterclockwise.

# If the 456 parameter is added with a sign, it represents the opposite direction, that is, clockwise.

4. Draw polygons

cv2.polylines(img,[pts],isClosed, color[,thickness[,lineType]])

pts: vertices of the polygon

isClosed: Whether it is closed. (True/False)

Other parameters refer to the drawing parameters of the circle.

  • Start Docker

After entering the Raspberry Pi 5 desktop, open a terminal and run the following command to start the container corresponding to Dofbot:

xxxxxxxxxx
./Docker_Ros.sh

Access Jupyter Lab within Docker:

xxxxxxxxxx
IP:9999 // Example: 192.168.1.11:9999

Code path:/root/Dofbot/4.opencv/3.draw_picture/05_rectangle_circle.ipynb**

import cv2
import numpy as np
newImageInfo = (500,500,3)
dst = np.zeros(newImageInfo,np.uint8)
# 1 2 upper left corner 3 lower right corner 4 5 fill -1 >0 line w
cv2.rectangle(dst,(350,100),(400,270),(0,255,0),3)
# 2 center 3 r
cv2.circle(dst,(250,250),(50),(255,0,0),2)
# 2 center 3 axis 4 angle 5 begin 6 end 7
cv2.ellipse(dst, (256,256), (150,100), 0, 0, 180, (0,255,255), -1)
points = np.array([[150,50], [140,140], [200,170], [250,250], [150,50]], np.int32)
#print(points.shape)
points = points.reshape((-1,1,2))
#print(points.shape)
cv2.polylines(dst,[points],True,(255,255,0))
# cv2.imshow('dst',dst)
     #cv2.waitKey(0)
xxxxxxxxxx
import matplotlib.pyplot as plt
dst = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB)
plt.imshow(dst)
plt.show()

Line segment drawing
Text and picture drawing

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