import cv2
import numpy as np

def test10():
  img = cv2.imread("result.jpg", cv2.IMREAD_UNCHANGED)
  rows, cols, chn = img.shape
  # 加噪声
  for i in range(5000):
    x = np.random.randint(0, rows)
    y = np.random.randint(0, cols)
    img[x, y, :] = 255
  cv2.imshow("demo", img)
  if cv2.waitKey(0) == 27:
    cv2.destroyWindow("demo")
test10()

import matplotlib.pyplot as plt
import cv2
def test11():
  img = cv2.imread("result.jpg")
  source = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
  # 均值滤波
  result = cv2.blur(source, (5, 5))

  # 显示图像
  title = ["demo1", "demo2"]
  imgs = [source, result]
  for i in range(2):
    plt.subplot(1, 2, i+1)　　　　 plt.imshow(imgs[i], "gray")
    plt.title(title[i])
    plt.xticks([])
    plt.yticks([])
  plt.show()
test11()

import cv2
import matplotlib.pyplot as plt
def test12():
  img = cv2.imread("result.jpg")
  source = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
  # 方框滤波
  result = cv2.boxFilter(source, -2, (5, 5), normalize=1)
  # 显示图像
  title = ["demo1", "demo2"]
  imgs = [source, result]
  for i in range(2):
    plt.subplot(1, 2, i+1), plt.imshow(imgs[i], "gray")
    plt.title(title[i])
    plt.xticks([])
    plt.yticks([])
  plt.show()
test12()

import cv2
import matplotlib.pyplot as plt
def test12():
  img = cv2.imread("result.jpg")
  source = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
  # 高斯滤波
  result = cv2.GaussianBlur(source, (3, 3), 0)
  # 显示图像
  title = ["demo1", "demo2"]
  imgs = [source, result]
  for i in range(2):
    plt.subplot(1, 2, i+1), plt.imshow(imgs[i], "gray")
    plt.title(title[i])
    plt.xticks([])
    plt.yticks([])
  plt.show()
test12()

import cv2
def test13():
  img = cv2.imread("result.jpg")
  # 高斯滤波
  result = cv2.medianBlur(img, 5)
  cv2.imshow("demo1", img)
  cv2.imshow("demo2", result)
  if cv2.waitKey(0) == 27:
    cv2.destroyWindow("demo1")
    cv2.destroyWindow("demo2")
test13()