Opencv learning notes II - basic image operations

1. POI Area ： Region of interest

2. Edge fill

3. Numerical operation

import cv2
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
from PIL import Image

image1 = mpimg.imread('1.jpg')
image2 = mpimg.imread('2.jpg')

plt.imshow(image1)

plt.imshow(image2)

Image addition

image3 = image1+image2
plt.imshow(image3)

Image cropping

plt.imshow(image1[100:-100, 100:-100, :]);

Image zoom

fx and fy Represents the zoom factor

image4 = cv2.resize(image1, (0, 0), fx=3, fy=1)
plt.imshow(image4);

4. Image threshold

ret, dst = cv2.threshold(src, thresh, maxval, type)

• src: The input image , Only single channel images
• dst： Output chart
• thresh： threshold
• maxval： The value when the pixel value exceeds or is less than the threshold
• type： The type of binarization
  • cv2.THRESH_BINARY Over threshold value maxval, Otherwise take 0
  • cv2.THRESH_BINARY_INV THRESH_BINARY The reversal of
  • cv2.THRESH_TRUNC Greater than the threshold set the threshold , The rest remains the same
  • cv2.THRESH_TOZERO Greater than the threshold unchanged , The rest is set to 0
  • cv2.THRESH_TOZERO_INV THRESH_TOZERO The reversal of

image1_gray = image1[:,:,0]
res, thresh1 = cv2.threshold(image1_gray, 127, 255, cv2.THRESH_BINARY)
res, thresh2 = cv2.threshold(image1_gray, 127, 255, cv2.THRESH_BINARY_INV)
res, thresh3 = cv2.threshold(image1_gray, 127, 255, cv2.THRESH_TRUNC)
res, thresh4 = cv2.threshold(image1_gray, 127, 255, cv2.THRESH_TOZERO)
res, thresh5 = cv2.threshold(image1_gray, 127, 255, cv2.THRESH_TOZERO_INV)

titles = ['Original Image', 'BINARY', 'BINARY_INV', 'TRUNC', 'TOZERO', 'TOZERO_INV']
images = [image1_gray, thresh1, thresh2, thresh3, thresh4, thresh5]
for i in range(6):
    plt.subplot(2,3,i+1)
    plt.imshow(images[i], 'gray')
    plt.title(titles[i])
    plt.xticks([])
    plt.yticks([])
plt.show()