python下对hsv颜色空间进行量化操作

#-*-coding:utf-8-*-
import cv2
import numpy as np
from datetime import datetime
from matplotlib import pyplot as plt

def colors(imagepath):
  img = cv2.imread(imagepath)
  hsv = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
  nhsv = np.zeros(hsv.shape[:2], dtype=np.uint8)
  t2 = datetime.now()
  for i in range(hsv.shape[0]):
    for j in range(hsv.shape[1]):
      nhsv[i][j] = quantilize(hsv[i][j])
  print datetime.now() - t2
  hist = cv2.calcHist([nhsv], [0], None, [72], [0,71]) # 40x faster than np.histogramfaster than np.histogram
  plt.plot(hist,color = 'r')
  plt.xlim([0, 72])
  plt.show()

def quantilize(value):
  '''hsv直方图量化
  value : [21, 144, 23] h, s, v
  opencv中，h-[0,180], s-[0,255], v-[0,255]
  '''
  # 
  value[0] = value[0] * 2
  hlist = [20, 40, 75, 155, 190, 270, 290, 316, 360]
  svlist = [21, 178, 255]
  for i in range(len(hlist)):
    if value[0] <= hlist[i]:
      h = i % 8
      break
  for i in range(len(svlist)):
    if value[1] <= svlist[i]:
      s = i
      break
  for i in range(len(svlist)):
    if value[2] <= svlist[i]:
      v = i
      break
  return 9 * h + 3 * s + v

#-*-coding:utf-8-*-
import cv2
import numpy as np
from datetime import datetime
from matplotlib import pyplot as plt

hlist = [20, 40, 75, 155, 190, 270, 290, 316, 360]
svlist = [21, 178, 255]

def quantilize(h, s, v):
  '''hsv直方图量化'''
  # value : [21, 144, 23] h, s, v
  h = h * 2
  for i in range(len(hlist)):
    if h <= hlist[i]:
      h = i % 8
      break
  for i in range(len(svlist)):
    if s <= svlist[i]:
      s = i
      break
  for i in range(len(svlist)):
    if v <= svlist[i]:
      v = i
      break
  return 9 * h + 3 * s + v

quantilize_ufunc = np.frompyfunc(quantilize, 3, 1) # 自定义ufunc函数，即将quantilize函数转化为ufunc函数，其输入参数为３个，输出参数为１个。

def colors(img):
  hsv = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
  nhsv = quantilize_ufunc(hsv[:,:,0], hsv[:,:,1], hsv[:,:,2]).astype(np.uint8) # 由于frompyfunc函数返回结果为对象，所以需要转换类型
  hist = cv2.calcHist([nhsv], [0], None, [72], [0,71]) # 40x faster than np.histogram
  hist = hist.reshape(1, hist.shape[0]).astype(np.int32).tolist()[0]
  return hist

if __name__ == '__main__':
  img_path = path + 'test.jpg'
  img = cv2.imread(img_path)
  colors(img)