def auto_lane(img):
polyfit = Polyfit()
img = cv2.resize(img,dsize=(320,180))
lower_black = np.array([0,0,0])
upper_black = np.array([180,255,70])
frame = warp(img)
cv2.imshow('frame',frame)
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, lower_black, upper_black)
cv2.imwrite('./mask.jpg',mask)
cv2.imshow('frame:',mask)
cv2.waitKey(1)
# frame = combined_threshold(frame)
try:
left_fit, right_fit, vars = polyfit.poly_fit_skip(mask)
if left_fit =='None' and right_fit == 'None':
result,offset,Radius = img,0,10000
cv2.imshow('re', cv2.resize(img, dsize=(640, 320)))
cv2.waitKey(1)
elif left_fit !='None' and right_fit == 'None' or left_fit !='None' and right_fit != 'None' :
result,offset,Radius = draw(img, mask, left_fit, right_fit,para = 277,meter = 30)
cv2.imshow('re',cv2.resize(result,dsize=(640,320)))
cv2.waitKey(1)
else:
print '-----1----unexcept error--------1----'
result,offset,Radius = img,0,10000
except:
print '---------unexcept error------------'
result,offset,Radius = img,0,10000
return result,offset,Radius
def draw_lane(img_arr):
polyfit = Polyfit()
combined_output = combined_threshold(img_arr)
warped = warp(combined_output)
left_fit, right_fit, vars = polyfit.poly_fit_skip(warped)
# print(left_fit,right_fit)
result = draw(img_arr, warped, left_fit, right_fit)
return result,left_fit,right_fit
def auto_lane(img, n):
polyfit = Polyfit()
img = cv2.resize(img, dsize=(320, 180))
frame = warp(img)
cv2.imshow('warped', frame)
# mask_flag = hsv(frame)
# dec_flag = dec_lane(mask_flag)
# mask = sobel(frame)
# corner_det(mask,frame)
mask = hsv(frame)
print(mask[2])
cv2.waitKey(1)
#mask = cv2.GaussianBlur(frame,(5,5),0)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2))
mask = cv2.erode(mask, kernel)
mask = cv2.dilate(mask, kernel)
cv2.imwrite('./image1/' + str(n) + '.jpg', hsv(img))
cv2.imwrite('./mask.jpg', mask)
cv2.imshow('frame:', mask)
cv2.waitKey(1)
# frame = combined_threshold(frame)
try:
left_fit, right_fit, vars = polyfit.poly_fit_skip(mask)
if left_fit == 'None' and right_fit == 'None':
result, offset, Radius = img, 'None', 10000
cv2.imshow('re', cv2.resize(img, dsize=(640, 320)))
cv2.waitKey(1)
elif left_fit != 'None' and right_fit == 'None' or left_fit != 'None' and right_fit != 'None':
result, offset, Radius = draw(img, mask, left_fit, right_fit)
cv2.imshow('re', cv2.resize(result, dsize=(640, 320)))
cv2.waitKey(1)
else:
result, offset, Radius = img, 0, 10000
except:
result, offset, Radius = img, 0, 10000
'''offset --------------------'''
if offset == 'None':
offset = 'None'
else:
offset = offset + 24.00
return result, offset, Radius
def auto_lane(img):
polyfit = Polyfit()
img = cv2.resize(img,dsize=(320,180))
frame = warp(img)
cv2.imshow('warped',frame)
mask_flag = hsv(frame)
dec_flag = dec_lane(mask_flag)
print 'dec_lane flag = ',dec_flag
mask = sobel(frame)
#mask = hsv(frame)
#mask = canny(frame,50,150)
#mask = cv2.GaussianBlur(frame,(5,5),0)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(2,2))
mask = cv2.erode(mask,kernel)
mask = cv2.dilate(mask,kernel)
cv2.imshow('mask',mask)
cv2.waitKey(1)
# frame = combined_threshold(frame)
try:
left_fit, right_fit, vars = polyfit.poly_fit_skip(mask)
if left_fit =='None' and right_fit == 'None':
result,offset,Radius = img,'None',10000
cv2.imshow('re', cv2.resize(img, dsize=(640, 320)))
cv2.waitKey(1)
elif left_fit !='None' and right_fit == 'None' or left_fit !='None' and right_fit != 'None' :
result,offset,Radius = draw(img, mask, left_fit, right_fit)
cv2.imshow('re',cv2.resize(result,dsize=(640,320)))
cv2.waitKey(1)
else:
print '-----1----unexcept error--------1----'
result,offset,Radius = img,0,10000
except:
print '---------unexcept error------------'
result,offset,Radius = img,0,10000
'''offset --------------------'''
if offset == 'None':
offset = 'None'
else:
offset = offset
return result,offset,Radius
def auto_lane(img):
polyfit = Polyfit()
img = cv2.resize(img, dsize=(320, 180))
cv2.imwrite('./resize.jpg', img)
warped = warp(img)
mask = abs_threshold(warped)
# mask = hsv(warped)
# frame = combined_threshold(frame)
left_fit, right_fit, vars = polyfit.poly_fit_skip(mask)
if left_fit == 'None' or right_fit == 'None':
result, offset, Radius = None, None, None
cv2.imshow('re', cv2.resize(img, dsize=(853, 480)))
cv2.waitKey(0)
return result, offset, Radius
else:
result, offset, Radius = draw(img, mask, left_fit, right_fit)
cv2.imshow('re', cv2.resize(result, dsize=(853, 480)))
cv2.waitKey(0)
cv2.imwrite("./res.jpg", result)
return result, offset, Radius
def auto_lane(img):
polyfit = Polyfit()
img = cv2.resize(img, dsize=(320, 180))
lower_black = np.array([0, 0, 0])
upper_black = np.array([180, 255, 70])
frame = warp(img)
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, lower_black, upper_black)
cv2.imshow('mask', mask)
# frame = combined_threshold(frame)
left_fit, right_fit, vars = polyfit.poly_fit_skip(mask)
if left_fit == 'None' or right_fit == 'None':
result, offset, Radius = None, None, None
cv2.imshow('re', cv2.resize(img, dsize=(853, 480)))
cv2.waitKey(0)
return result, offset, Radius
else:
result, offset, Radius = draw(img, mask, left_fit, right_fit)
cv2.imshow('re', cv2.resize(result, dsize=(853, 480)))
cv2.waitKey(0)
return result, offset, Radius
def auto_lane(img):
polyfit = Polyfit()
img = cv2.resize(img, dsize=(320, 180))
#light recongise
GreenLight, RedLight, SpeedLimit, HireSign = recongise(img)
GreenLight = main(img)
frame = warp(img)
mask = hsv(frame)
# dec_flag = dec_lane(mask)
#mask = canny(frame,50,150)
#mask = cv2.GaussianBlur(frame,(5,5),0)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2))
mask = cv2.erode(mask, kernel)
mask = cv2.dilate(mask, kernel)
cv2.imshow('mask', mask)
cv2.waitKey(1)
try:
left_fit, right_fit, vars = polyfit.poly_fit_skip(mask)
if left_fit == 'None' and right_fit == 'None':
result, offset, Radius, k_error = img, 'None', 10000, 0
## cv2.imshow('re', cv2.resize(img, dsize=(640, 320)))
## cv2.waitKey(1)
elif left_fit != 'None' and right_fit == 'None' or left_fit != 'None' and right_fit != 'None':
result, offset, Radius, k_error = draw(img, mask, left_fit,
right_fit)
## cv2.imshow('re',cv2.resize(result,dsize=(640,320)))
cv2.waitKey(1)
else:
result, offset, Radius, k_error = img, 0, 10000, 0
except:
result, offset, Radius, k_error = img, 0, 10000, 0
'''offset --------------------'''
'''--------------------------lanetype--------------------------'''
'''zhixian:1..wandao:2...zhijiaowan: 3'''
if offset == 'None':
offset = 'None'
else:
offset = offset
if abs(k_error) < 0.06:
cur_mode = 1 #wandao
elif abs(k_error) >= 0.06:
cur_mode = 2 #zhidao
elif k_error == 'None':
cur_mode = last_mode #keeping
'''cornerflage'''
corner_flag = corner_det(mask, img)
if corner_flag == 0:
pass
if corner_flag == 1:
cur_mode = 3
last_mode = cur_mode
Lane_type = cur_mode
'''-----------SpeedLimit----------'''
SpeedLimit = 0
'''-----------RedLight------------'''
RedLight = 0
'''-----------GreenLight----------'''
GreenLight = 0
'''-----------HireSign------------'''
HireSign = 0
'''-----------StopSign------------'''
StopSign = 0
cv2.imshow('result', result)
cv2.waitKey(1)
return result, offset, Radius, Lane_type, SpeedLimit, RedLight, GreenLight, HireSign, StopSign
if off_center<0:
print("Offset to right:",abs(off_center),str("m"))
center_messages = "Offset to right: : " + str(abs(off_center))+str("m")
return center_messages
if off_center>0:
print("Offset to left:",abs(off_center),str("m"))
center_messages = "Offset to left:" + str(abs(off_center))+str("m")
return center_messages
if off_center == 0:
print("On the center:",abs(off_center),str("m"))
center_messages = "On the center:" + str(abs(off_center))+str("m")
return center_messages
if __name__ == "__main__":
# x,y =
######计算距离
x,y=197,894
flag,alpha,n,m,raw,colum = direction_calculate(x,y)
if flag == 1 :
distance = distance_calculate(n,m,raw,colum)
print(flag,alpha,distance)
else:
pass
#####计算偏离中心的距离
img_arr =cv2.imread("./input/test6.jpg")
polyfit = Polyfit()
combined_output = combined_threshold(img_arr)
warped = perspective_1(combined_output)
left_fit, right_fit, vars = polyfit.poly_fit_skip(warped)
offset = off_center(img_arr,left_fit,right_fit)
return result, left_fit, right_fit
if __name__ == "__main__":
# polyfit = Polyfit()
# original_video = './video.mp4'
# cap = cv2.VideoCapture(original_video)
# n = 0
# while (1):
# n = n+1
# ret,img = cap.read()
# img = cv2.resize(img,dsize=(320,180))
# frame = warp(img)
# cv2.imshow('warp',frame)
# frame = combined_threshold(frame)
# left_fit, right_fit, vars = polyfit.poly_fit_skip(frame)
# result = draw(img, frame, left_fit, right_fit)
# cv2.imshow('re', result)
# cv2.waitKey(1)
#1280 720
polyfit = Polyfit()
img = cv2.imread('./101.jpg')
frame = warp(img)
frame = combined_threshold(frame)
left_fit, right_fit, vars = polyfit.poly_fit_skip(frame)
result = draw(img, frame, left_fit, right_fit)
cv2.imshow('re', result)
cv2.waitKey(0)