Implementation process: synchronously amplify the three channel values of each pixel, while keeping the channel value between 0-255.
map (f, list) applies the function f to the entire list and returns the new list.
np.clip (a, a_min, a_max, out = None) limit the elements in a to the minimum and maximum values
Code path:
/home/pi/Yahboom_Project/Raspbot/1.OpenCV_course/04image_beautification/04_Brightness_enhancement.ipynb
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) + 40
gg = int(g) + 40
rr = int(r) + 40
if bb>255:
bb = 255
if gg>255:
gg = 255
if rr>255:
rr = 255
dst[i,j] = (bb,gg,rr)
# 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) # Set the size and pixels of the drawing area
plt.subplot(121) # The first in a row and two columns
plt.imshow(img)
plt.subplot(122) # The second in a row and two columns
plt.imshow(dst)
plt.show()
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After running the above program, two pictures will be displayed in the jupyterLab control interface, as shown below.
[Original picture] [Brightness enhancement picture]