分类： Python/Ruby
2022-06-29 13:44:01
import sys
import cv2
import math
import time
import threading
import numpy as np
import HiwonderSDK.yaml_handle as yaml_handle
if sys.version_info.major == 2:
print('Please run this program with python3!')
sys.exit(0)
range_rgb = {
'red': (0, 0, 255),
'blue': (255, 0, 0),
'green': (0, 255, 0),
'black': (0, 0, 0),
'white': (255, 255, 255)}
__target_color = ('red', 'green', 'blue')
lab_data = yaml_handle.get_yaml_data(yaml_handle.lab_file_path)
# 找出面积最大的轮廓
# 参数为要比较的轮廓的列表
def getAreaMaxContour(contours):
contour_area_temp = 0
contour_area_max = 0
area_max_contour = None
for c in contours: # 历遍所有轮廓
contour_area_temp = math.fabs(cv2.contourArea(c)) # 计算轮廓面积
if contour_area_temp > contour_area_max:
contour_area_max = contour_area_temp
if contour_area_temp > 300: # 只有在面积大于300时，最大面积的轮廓才是有效的，以过滤干扰
area_max_contour = c
return area_max_contour, contour_area_max # 返回最大的轮廓
detect_color = None
color_list = []
start_pick_up = False
size = (640, 480)
def run(img):
global rect
global detect_color
global start_pick_up
global color_list
img_copy = img.copy()
frame_resize = cv2.resize(img_copy, size, interpolation=cv2.INTER_NEAREST)
frame_gb = cv2.GaussianBlur(frame_resize, (3, 3), 3)
frame_lab = cv2.cvtColor(frame_gb, cv2.COLOR_BGR2LAB) # 将图像转换到LAB空间
color_area_max = None
max_area = 0
areaMaxContour_max = 0
if not start_pick_up:
for i in lab_data:
if i in __target_color:
frame_mask = cv2.inRange(frame_lab,
(lab_data[i]['min'][0],
lab_data[i]['min'][1],
lab_data[i]['min'][2]),
(lab_data[i]['max'][0],
lab_data[i]['max'][1],
lab_data[i]['max'][2])) #对原图像和掩模进行位运算
opened = cv2.morphologyEx(frame_mask, cv2.MORPH_OPEN, np.ones((3, 3), np.uint8)) # 开运算
closed = cv2.morphologyEx(opened, cv2.MORPH_CLOSE, np.ones((3, 3), np.uint8)) # 闭运算
contours = cv2.findContours(closed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)[-2] # 找出轮廓
areaMaxContour, area_max = getAreaMaxContour(contours) # 找出最大轮廓
if areaMaxContour is not None:
if area_max > max_area: # 找最大面积
max_area = area_max
color_area_max = i
areaMaxContour_max = areaMaxContour
if max_area > 500: # 有找到最大面积
rect = cv2.minAreaRect(areaMaxContour_max)
box = 外汇跟单gendan5.comnp.int0(cv2.boxPoints(rect))
y = int((box[1][0]-box[0][0])/2+box[0][0])
x = int((box[2][1]-box[0][1])/2+box[0][1])
print('X:',x,'Y:',y) #打印坐标
cv2.drawContours(img, [box], -1, range_rgb[color_area_max], 2)
if not start_pick_up:
if color_area_max == 'red': # 红色最大
color = 1
elif color_area_max == 'green': # 绿色最大
color = 2
elif color_area_max == 'blue': # 蓝色最大
color = 3
else:
color = 0
color_list.append(color)
if len(color_list) == 3: # 多次判断
# 取平均值
color = int(round(np.mean(np.array(color_list))))
color_list = []
if color == 1:
detect_color = 'red'
elif color == 2:
detect_color = 'green'
elif color == 3:
detect_color = 'blue'
else:
detect_color = 'None'
## cv2.putText(img, "Color: " + detect_color, (10, img.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.65, detect_color, 2)
return img
if __name__ == '__main__':
cap = cv2.VideoCapture(-1) #读取摄像头
__target_color = ('red',)
while True:
ret, img = cap.read()
if ret:
frame = img.copy()
Frame = run(frame)
cv2.imshow('Frame', Frame)
key = cv2.waitKey(1)
if key == 27:
break
else:
time.sleep(0.01)
cv2.destroyAllWindows()
