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Rider Pi Robot📖
0.Quick Start
  • 0. Notes (Must Read)new
  • 1.APP control experience
  • 2.Web page image transmission controlnew
  • 3.Manual
1.RPi Basic course
  • 1.SSH remote login
  • 2.VNC remote login desktop
  • 3. Remote file transfer
  • 4. JupyterLab environment construction and use
  • 5. Write system image
  • 6. Connect to WiFi
  • 7. Close startup programs(MustRead)
  • 8. Raspberry Pi system expansion
2.Car basic control course
  • 1. Car screen display control
  • 2. Car recording audio
  • 3. Car plays audio
  • 4. Car recording video
  • 5. Car plays video
  • 6. RGB light control
  • 7. Car attitude angle reading
  • 8. Read the battery level of the car
3.Car motion control
  • 1. Car forward and backward
  • 2. Car rotation movement
  • 3. Adjust car height
  • 4. Adjust car posture
  • 5. Car self-stabilization mode
  • 6. Car squats and shakes
4.Open Source CV
A. Getting started with OpenCV
  • 1. Introduction to OpenCV
  • 2. OpenCV image reading and display
  • 3. OpenCV image writing
  • 4. OpenCV Image Quality
  • 5.OpenCV pixel operations
B. OpenCV geometric transformation
  • 1. Image scaling
  • 2. Image cutting
  • 3. Image translation
  • 4. Image mirroring
  • 5. Affine Transformation
  • 6. Image Rotation
  • 7. Perspective Transformation
C. OpenCV image processing and drawing text segments
  • 1. Grayscale processing
  • 2. Image Binarization
  • 3. Edge Detection
  • 4. Line drawing
  • 5. Rectangle and circle drawing
  • 6. Text and picture drawing
D. Image beautification
  • 1. Color Image Histogram
  • 2. Histogram Equalization
  • 3. Image repair
  • 4. Brightness enhancement
  • 5. Skin whitening
  • 6. Gaussian mean filtering
  • 7. Median Filter
5.AI Visual recognition course
  • 1. Camera driver tutorial
  • 2. Color recognition
  • 3. HSV value test
  • 4. Object Recognition
  • 5. QR code recognition
  • 6. Human face mask
  • 7. License Plate Recognition
  • 8. Human Pose Estimation
  • 9. Object Detection
  • 10.Yolo detection
  • 11. Face Detection
  • 12. Face effects
  • 13. 3D Object Recognition
  • 14. Paintbrush
  • 15. Finger recognition
  • 16. Gesture Recognition
  • 17.Facial Recognitionnew
  • 18.Emotion Recognitionnew
  • 19.Motion Detectionnew
6.AI Visual interaction course
  • 1. Color tracking
  • 2. Color follows
  • 3. QR code recognition action
  • 4. Face tracking
  • 5. Finger control
  • 6. Gesture following
  • 7. Gesture control car
  • 8. Human Body Followingnew
7. AI Large Model Interaction
  • 0.Principles of Large AI Models
  • 1.Large model premise use configuration
  • 2.Q&A(For cm5)
  • 3.Q&A and ChatGPT(For cm4)
  • 4.Speech recognition
  • 5.Picture to Text
  • 6.Embodied intelligence
Download
  • APP(iOS/Android)
  • System_File
  • Code
  • Hareware_Info
  • AI_Model_File
  • 3D_Model_File
  • Instruction_Manual
Download ZIP

Welcome to Rider Pi Robot repository

5. Skin whitening

5. Skin whitening

5. Skin whitening5.1. Skin whitening5.2 Actual effect display

5.1. Skin whitening

OpenCV implements the function of skin whitening for images. The principle of implementation is basically the same as the principle of "1.20 OpenCV image brightness enhancement", but here we do not need to process the r value, just follow this formula, p = p(x)*1.4+ y, where p(x) represents the b channel or g channel, and y represents the value to be increased or decreased. Similarly, after adding the value, we need to judge the value.

5.2 Actual effect display

Source code path:

/home/pi/Rider-pi_class/4.Open Source CV/D.Image_Enhancement/05_Skin_Smoothing_and_Whitening.ipynb

​x
#图片的美白公式:p = P*1.4(a)+ b; Image whitening formula: p = P*1.4(a)+ b;
import cv2
import numpy as np
import matplotlib.pyplot as plt
​
img = cv2.imread('yahboom.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
#cv2.imshow('src',img)
dst = np.zeros((height,width,3),np.uint8)
for i in range(0,height):
    for j in range(0,width):
        (b,g,r) = img[i,j]
        bb = int(b*1.3) + 10
        gg = int(g*1.2) + 15
​
        if bb>255:
            bb = 255
        if gg>255:
            gg = 255
​
        dst[i,j] = (bb,gg,r)
# cv2.imshow('dst',dst)
# cv2.waitKey(0)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
dst = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB)
plt.figure(figsize=(14, 6), dpi=100) #设置绘图区域的大小和像素 Set the size and pixels of the drawing area
plt.subplot(121)  # 一行二列第一个  The first row and second column
plt.imshow(img)
plt.subplot(122)  # 一行二列第二个 The second row, second column
plt.imshow(dst)
plt.show()

xxxxxxxxxx
​
import cv2
import matplotlib.pyplot as plt
​
img = cv2.imread('yahboom.jpg',1)
#cv2.imshow('src',img)
dst = cv2.bilateralFilter(img,15,35,35)
# cv2.imshow('dst',dst)
# cv2.waitKey(0)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
dst = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB)
plt.figure(figsize=(14, 6), dpi=100) #设置绘图区域的大小和像素 Set the size and pixels of the drawing area
plt.subplot(121)  # 一行二列第一个 The first row and second column
plt.imshow(img)
plt.subplot(122)  # 一行二列第二个 The second row, second column
plt.imshow(dst)
plt.show()

Brightness enhancement
Gaussian mean filtering

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