from PIL import Image
import numpy as np
import cv2

img_L = np.array(Image.open('test.png').convert("L"))
img_RGB = np.array(Image.open('test.png').convert("RGB"))

# temp = {}
# for i in range(img_L.shape[0]):
#   for j in range(img_L.shape[1]):
#     if not temp.get(int(img_L[i][j])):
#       temp[int(img_L[i][j])] = list(img_RGB[i][j])
# print(temp)

#這里得到灰度像素值0對(duì)應(yīng)(0,0,0),62對(duì)應(yīng)(19,69,139)
color_0_0_0 = np.where(img_L == 0)[0].shape[0]
color_19_69_139 = np.where(img_L == 62)[0].shape[0]

pixel_sum = img_L.shape[0] * img_L.shape[1]

print("0_0_0 像素個(gè)數(shù)：{} 占比：%{}".format(color_0_0_0,color_0_0_0/pixel_sum*100))
print("19_69_139 像素個(gè)數(shù)：{} 占比：%{}".format(color_19_69_139,color_19_69_139/pixel_sum*100))

import cv2 as cv
import matplotlib.pyplot as plt
import numpy as np
def statistics():
  src = cv.imread("D:/matplotlib/0.jpg")
  cv.imshow("q",src)
  h,w,ch = np.shape(src)
  gray = cv.cvtColor(src,cv.COLOR_BGR2GRAY)
  cv.imshow("gray",gray)
  hest = np.zeros([256],dtype = np.int32)
  for row in range(h):
    for col in range(w):
      pv = gray[row,col]
      hest[pv] +=1
  plt.plot(hest,color = "r")
  plt.xlim([0,256])
  plt.show()
  cv.waitKey(0)
  cv.destroyAllWindows()
statistics()

import cv2 as cv
import matplotlib.pyplot as plt
import numpy as np
def statistics():
  src = cv.imread("D:/matplotlib/0.jpg")
  cv.imshow("q",src)
  h,w,ch = np.shape(src)
  #讀取圖像屬性
  gray = cv.cvtColor(src,cv.COLOR_BGR2GRAY)
  #將圖像轉(zhuǎn)換成灰度圖，
  cv.imshow("gray",gray)
  hest = np.zeros([256],dtype = np.int32)
  #建立空白數(shù)組
  for row in range(h):
    for col in range(w):
      pv = gray[row,col]
      hest[pv] +=1
      #統(tǒng)計(jì)不同像素值出現(xiàn)的頻率
  plt.plot(hest,color = "r")
  plt.xlim([0,256])
  plt.show()
  #畫出統(tǒng)計(jì)圖
  cv.waitKey(0)
  cv.destroyAllWindows()
statistics()