HSV色彩空间转换

可视化调节

1） 构建代码

import cv2
import numpy as np
def show_one_image(image_path):
    # -*- coding:utf-8 -*-
    """
    功能：读取一张图片，显示出来，转化为HSV色彩空间
         并通过滑块调节HSV阈值，实时显示
    """

    image = cv2.imread(image_path) # 根据路径读取一张图片，opencv读出来的是BGR模式
    cv2.imshow("BGR", image) # 显示图片

    hsv_low = np.array([0, 0, 0])
    hsv_high = np.array([0, 0, 0])
    
    # 下面几个函数，写得有点冗余

    def h_low(value):
        hsv_low[0] = value

    def h_high(value):
        hsv_high[0] = value

    def s_low(value):
        hsv_low[1] = value

    def s_high(value):
        hsv_high[1] = value

    def v_low(value):
        hsv_low[2] = value

    def v_high(value):
        hsv_high[2] = value

    cv2.namedWindow('image',cv2.WINDOW_AUTOSIZE)

    #H low：
    #    0：指向整数变量的可选指针，该变量的值反映滑块的初始位置。
    #  179：表示滑块可以达到的最大位置的值为179，最小位置始终为0。
    #h_low：指向每次滑块更改位置时要调用的函数的指针，指针指向h_low元组，有默认值0。
    #（此函数的原型应为void XXX (int, void *); ，其中第一个参数是轨迹栏位置，第二个参数是用户数据（请参阅下一个参数）。如果回调是NULL指针，则不调用任何回调，而仅更新值。）
    cv2.createTrackbar('H low', 'image', 0, 179, h_low) 
    cv2.createTrackbar('H high', 'image', 0, 179, h_high)
    cv2.createTrackbar('S low', 'image', 0, 255, s_low)
    cv2.createTrackbar('S high', 'image', 0, 255, s_high)
    cv2.createTrackbar('V low', 'image', 0, 255, v_low)
    cv2.createTrackbar('V high', 'image', 0, 255, v_high)

    while True:
        dst = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) # BGR转HSV
        dst = cv2.inRange(dst, hsv_low, hsv_high) # 通过HSV的高低阈值，提取图像部分区域
        cv2.imshow('dst', dst)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    cv2.destroyAllWindows()

执行代码

show_one_image(image_path = "Red_round/37.jpg")

2）不同色彩掩码生成

图片来源：https://www.pianshen.com/article/178932885/

import numpy as np
import collections
  
#定义字典存放颜色分量上下限
#例如：{颜色: [min分量, max分量]}
#{'red': [array([160, 43, 46]), array([179, 255, 255])]}
  
def getColorList():
  dict = collections.defaultdict(list)
  
  # 黑色
  lower_black = np.array([0, 0, 0])
  upper_black = np.array([180, 255, 46])
  color_list = []
  color_list.append(lower_black)
  color_list.append(upper_black)
  dict['black'] = color_list
  
  # #灰色
  # lower_gray = np.array([0, 0, 46])
  # upper_gray = np.array([180, 43, 220])
  # color_list = []
  # color_list.append(lower_gray)
  # color_list.append(upper_gray)
  # dict['gray']=color_list
  
  # 白色
  lower_white = np.array([0, 0, 221])
  upper_white = np.array([180, 30, 255])
  color_list = []
  color_list.append(lower_white)
  color_list.append(upper_white)
  dict['white'] = color_list
  
  #红色
  lower_red = np.array([156, 43, 46])
  upper_red = np.array([180, 255, 255])
  color_list = []
  color_list.append(lower_red)
  color_list.append(upper_red)
  dict['red']=color_list
  
  # 红色2
  lower_red = np.array([0, 43, 46])
  upper_red = np.array([10, 255, 255])
  color_list = []
  color_list.append(lower_red)
  color_list.append(upper_red)
  dict['red2'] = color_list
  
  #橙色
  lower_orange = np.array([11, 43, 46])
  upper_orange = np.array([25, 255, 255])
  color_list = []
  color_list.append(lower_orange)
  color_list.append(upper_orange)
  dict['orange'] = color_list
  
  #黄色
  lower_yellow = np.array([26, 43, 46])
  upper_yellow = np.array([34, 255, 255])
  color_list = []
  color_list.append(lower_yellow)
  color_list.append(upper_yellow)
  dict['yellow'] = color_list
  
  #绿色
  lower_green = np.array([35, 43, 46])
  upper_green = np.array([77, 255, 255])
  color_list = []
  color_list.append(lower_green)
  color_list.append(upper_green)
  dict['green'] = color_list
  
  #青色
  lower_cyan = np.array([78, 43, 46])
  upper_cyan = np.array([99, 255, 255])
  color_list = []
  color_list.append(lower_cyan)
  color_list.append(upper_cyan)
  dict['cyan'] = color_list
  
  #蓝色
  lower_blue = np.array([100, 43, 46])
  upper_blue = np.array([124, 255, 255])
  color_list = []
  color_list.append(lower_blue)
  color_list.append(upper_blue)
  dict['blue'] = color_list
  
  # 紫色
  lower_purple = np.array([125, 43, 46])
  upper_purple = np.array([155, 255, 255])
  color_list = []
  color_list.append(lower_purple)
  color_list.append(upper_purple)
  dict['purple'] = color_list
  
  return dict

import cv2
import numpy as np
import colorList
  
filename='car04.jpg'
  
#处理图片
def get_color(frame):
  print('go in get_color')
  hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
  maxsum = -100
  color = None
  color_dict = getColorList()
  for d in color_dict:
    mask = cv2.inRange(hsv,color_dict[d][0],color_dict[d][1])
    cv2.imwrite(d+'.jpg',mask)
    binary = cv2.threshold(mask, 127, 255, cv2.THRESH_BINARY)[1]
    binary = cv2.dilate(binary,None,iterations=2)
    img, cnts, hiera = cv2.findContours(binary.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    sum = 0
    for c in cnts:
      sum+=cv2.contourArea(c)
    if sum > maxsum :
      maxsum = sum
      color = d
  
  return color
  
  
if __name__ == '__main__':
  frame = cv2.imread(filename)
  print(get_color(frame))

3） 对于2）的更改