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hsv_pic_sample.py
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hsv_pic_sample.py
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""" 图片鼠标取值HSV value camera输出显示 """
import numpy as np
import copy as cp
import cv2
import math
import time
import matplotlib.pyplot as plt
import seaborn as sns
photo_path='1.png'
picture_test = cv2.imread(photo_path)
img = picture_test.copy()
########################################################################
max_record = [0,0,0]
min_record = [255,255,255]
plt_h = []
plt_s = []
plt_v = []
##########################################################################
color_range = {
'yellow_door': [(30 , 190 , 71), (35 , 255 , 103)],
#'yellow_door': [(16 , 100 , 72), (29 , 226 , 185)],
'black_door':[(25, 25, 10), (110, 150, 24)],
'green_hole_chest':[(63 , 87 , 87), (73 , 250 , 177)],
'green_hole_head':[(55 , 113 , 70), (75 , 241 , 144)],
'blue_hole_chest':[(104 , 129 , 133), (113 , 227 , 225)],
'blue_hole_head':[(106 , 113 , 102), (115 , 234 , 191)],
'blue_baf':[(100 , 127 , 52), (112 , 245 , 170)],
'black_dir':[(0, 0, 10), (170 , 180 , 59)],
'gray_white':[(54 , 31 , 79), (80 , 90 , 166)],
'blue_floor':[(104 , 142 , 73), (125 , 249 , 255)],
'green_floor':[(61 , 99 , 72), (80 , 255 , 185)],
'red_floor1':[(0 , 112 , 130), (14 , 207 , 245)],
'red_floor2':[(173 , 145 , 139), (179 , 229 , 252)],
'red_XP1':[(0 , 141 , 114), (4 , 250 , 254)],
'red_XP2':[(177 , 182 , 139), (179 , 229 , 225)],
'color11':[(104 , 141 , 154), (109 , 211 , 231)],
'color22':[(63 , 73 , 88), (83 , 174 , 197)],
'color33':[(0 , 86 , 135), (10 , 163 , 242)],
'ball_red1':[(0 , 129 , 104), (5 , 234 , 193)],
'ball_red2':[(177 , 75 , 122), (179 , 184 , 151)],
'd_red_ball_floor1':[(171 , 71 , 113), (179 , 212 , 215)],
'd_red_ball_floor2':[(0 , 91 , 123), (4 , 204 , 224)],
'ball_red':[(30 , 3, 143), (173 , 44 , 237)],
'blue_hole':[(109 , 35 , 94), (149 , 105 , 141)],
'head_blue_door':[(93 , 95 , 62), (113 , 222 , 197)],
'green_bridge':[(57 , 85 , 112), (81 , 237 , 228)],
'blue_bridge':[(101 , 112 , 126), (111 , 216 , 251)],
'green_bridge_rec':[(62 , 85 , 112), (74 , 201 , 228)],
'blue_bridge_rec':[(101 , 112 , 126), (111 , 216 , 251)],
'kick_ball_rec':[(4 , 38 , 49), (34 , 132 , 157)],
'gray_dir':[(71 , 17 , 111), (85 , 41 , 143)],
'black_line':[(60 , 23 , 25), (122 , 124 , 100)],
'yellow_line':[(29 , 118 , 90), (38 , 209 , 187)],
'test0':[(0 , 155 , 216), (1 , 177 , 232)],
'test1':[(179 , 155 , 216), (180 , 177 , 232)],
'test2':[(179 , 155 , 216), (180 , 177 , 232)]
}
# 新建窗口
cv2.namedWindow("OriginalImg",cv2.WINDOW_NORMAL)
cv2.namedWindow("IMG_HSV",cv2.WINDOW_NORMAL)
cv2.namedWindow("ColorMask",cv2.WINDOW_NORMAL)
cv2.resizeWindow("OriginalImg", 640, 480)
cv2.resizeWindow("IMG_HSV", 640, 480)
cv2.resizeWindow("ColorMask", 640, 480)
def hsv_max(aa,bb):
cc=[bb[0],bb[1],bb[2]]
if aa[0] < 160:
if aa[0]>bb[0]:
cc[0]=aa[0]
if aa[1]>bb[1]:
cc[1]=aa[1]
if aa[2]>bb[2]:
cc[2]=aa[2]
return cc
def hsv_min(aa,bb):
cc=[bb[0],bb[1],bb[2]]
if aa[0] <160:
if aa[0]<bb[0]:
cc[0]=aa[0]
if aa[1]<bb[1]:
cc[1]=aa[1]
if aa[2]<bb[2]:
cc[2]=aa[2]
return cc
def onmouse(event, x, y, flags, param): #标准鼠标交互函数
global max_record,min_record
hsvimg = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
if event==cv2.EVENT_MOUSEMOVE: #当鼠标移动时
if sampling_flag == True:
xy_hsv = hsvimg[y,x]
print(x,y,xy_hsv, "正在采集，w停止采集") #显示鼠标所在像素的数值，注意像素表示方法和坐标位置的不同
plt_h.append(xy_hsv[0])
plt_s.append(xy_hsv[1])
plt_v.append(xy_hsv[2])
max_record = hsv_max(xy_hsv,max_record)
min_record = hsv_min(xy_hsv,min_record)
else:
print(min_record,"min--停止采集, w 开始采集--max",max_record)
print("[(" + str(min_record[0]) + " , " + str(min_record[1]) + " , " + str(min_record[2]) + "), (" + str(max_record[0]) + " , " + str(max_record[1]) + " , " + str(max_record[2]) + ")]," )
# 创建鼠标事件的回调函数
cv2.setMouseCallback("OriginalImg", onmouse)
num = 0
sampling_flag = False
while True:
hsvimg = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
h,s,v = cv2.split(img)
#####################红色用这个#####################################################################################
frame_red0 = cv2.inRange(hsvimg, color_range['test0'][0],color_range['test0'][1]) # 对原图像和掩模(颜色的字典)进行位运算
frame_red1 = cv2.inRange(hsvimg, color_range['test1'][0],color_range['test1'][1])
frame_rea_final=frame_red0+frame_red1
cv2.imshow("ColorMask", frame_rea_final)
cv2.imshow("IMG_HSV",hsvimg)
cv2.imshow("OriginalImg",img)
##################################################################################################################
#####################其他用这个#####################################################################################
# frame_other = cv2.inRange(hsvimg, color_range['test2'][0],color_range['test2'][1]) # 对原图像和掩模(颜色的字典)进行位运算
# cv2.imshow("ColorMask", frame_other)
# cv2.imshow("IMG_HSV",hsvimg)
# cv2.imshow("OriginalImg",img)
##################################################################################################################
k = cv2.waitKey(500)
# 如果按了'q'键，则关闭面板
if k == ord('q'):
break
if k == ord('s'):
num += 1
name = 'photo_save' + str(num) + '.bmp'
print(name)
cv2.imwrite(name,img) #保存图片
if k == ord('w'):
if sampling_flag == True:
sampling_flag = False
print("停止采集")
# 去掉下部分注释可以显示数据分布
# sns.distplot(plt_h, bins = None, kde = False, hist_kws = {'color':'steelblue'}, label = 'h')
# sns.distplot(plt_s, bins = None, kde = False, hist_kws = {'color':'purple'}, label = 's')
# sns.distplot(plt_v, bins = None, kde = False, hist_kws = {'color':'darkgreen'}, label = 'v')
# plt.title('hsv')
# plt.legend()
# plt.show()
else:
sampling_flag = True
print("开始采集")