def get_contour_from_image(img):
line_yellows = get_range(
img, np.array([10, 100, 180], np.uint8),
np.array([60, 255, 255], np.uint8), cv2.COLOR_BGR2HSV
) # u: 10/110/200 ; 40/255/255 f: 20/110/200 ; 40/255/255
line_whites = get_range(
img, np.array([65, 150, 30], np.uint8),
np.array([255, 255, 180], np.uint8), cv2.COLOR_BGR2HLS
) # u: 80/150/30 ; 255/255/130 f: 80/150/30 ; 255/255/150
line_reds = get_range(img, np.array([150, 0, 0], np.uint8),
np.array([255, 255, 255], np.uint8),
cv2.COLOR_BGR2HLS)
img_gray = cv2.cvtColor(
img, cv2.COLOR_BGR2GRAY) # convert the color image to gray image
contours = get_gray_countour(img_gray)
contour_dump("img3/contours_full" + str(int(time.time() * 10)) + ".jpg",
contours, img)
_, contours = remove_contour(line_yellows, contours, 1)
if len(contours) == 0: return None
# _, contours = remove_contour( line_whites, contours, -1 ) # u: ## f: ~~
if len(contours) == 0: return None
contour_left = contour_largest(contours) # u: largest f: leftest
contour_dump(
"img/contours_extracted" + str(int(time.time() * 10)) + ".jpg",
contour_left, img)
return contour_left
def contour_largest(contours, dump=False, filename=""):
contour_largest = contours[0]
x_largest = 0
for contour in contours:
area = cv2.contourArea(contour)
# print("area = ", area)
if area > x_largest:
contour_largest = contour
x_largest = area
if dump:
contour_dump(filename, contour_largest, img)
return contour_largest
def contour_leftest(contours, dump=False, filename=""):
contour_leftest = contours[0]
x_leftest = sys.maxsize
for contour in contours:
moment_contour = cv2.moments(contour)
if moment_contour['m00']:
moment_contour_x = int(moment_contour['m10'] /
moment_contour['m00'])
if moment_contour_x < x_leftest:
contour_leftest = contour
x_leftest = moment_contour_x
if dump:
contour_dump(filename, contour_leftest, img)
return contour_leftest
def get_contour_from_image( img ): line_yellows = get_yellow( img ) line_whites = get_range( img, np.array([0,160,0], np.uint8), np.array([255,255,255], np.uint8), cv2.COLOR_BGR2HLS) line_reds = get_range( img, np.array([150,0,0], np.uint8), np.array([255,255,255], np.uint8), cv2.COLOR_BGR2HLS) img_gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) # convert the color image to gray image contours = get_gray_countour(img_gray) contour_dump( "img/contours_full" + str(int(time.time()*10)) + ".jpg", contours, img) _, contours = remove_contour( line_yellows, contours, 1 ) if len(contours) == 0: return None _, contours = remove_contour( line_whites, contours, -1 ) if len(contours) == 0: return None contour_left = contour_leftest(contours) contour_dump( "img/contours_extracted" + str(int(time.time()*10)) + ".jpg", contour_left, img) return contour_left
def remove_contour(lines,
contours,
left_direction,
dump=False,
filename=None,
img=None):
# left is 1, other -1
if len(lines) == 0:
print("No target lines")
return 0, contours
to_be_removed = []
ret_contour = []
print("type(contours) = ", type(contours))
print("lines = ", lines)
for contour in contours:
print("type(contour) = ", type(contour))
moment_contour = cv2.moments(contour)
# print("moment_contour['m00'] = ", moment_contour['m00'])
# print("moment_contour['m10'] = ", moment_contour['m10'])
# print("moment_contour['m01'] = ", moment_contour['m01'])
if moment_contour['m00']:
moment_contour_x = int(moment_contour['m10'] /
moment_contour['m00'])
moment_contour_y = int(moment_contour['m01'] /
moment_contour['m00'])
# print("Center at (", moment_contour_x, ", ", moment_contour_y, ")")
fit_value = moment_contour_x * lines[0][0] + lines[0][
1] - moment_contour_y
print("(", "{0:.2f}".format(lines[0][0]), "x+",
"{0:.2f}".format(lines[0][1]), "), at (", moment_contour_x,
", ", moment_contour_y, "), Value = ", fit_value)
if left_direction == 1:
if fit_value * lines[0][0] > 0:
ret_contour.append(contour)
else:
if fit_value * lines[0][0] < 0:
ret_contour.append(contour)
else:
ret_contour.append(contour)
if dump:
if img is None:
raise ValueError('You should input img when you want to dump')
contour_dump(filename, ret_contour, img)
return len(contours) - len(ret_contour), np.asarray(ret_contour)
def get_contour_from_image(img):
line_yellows = get_yellow(img)
line_whites = get_white(img)
line_reds = get_red(img)
img_gray = cv2.cvtColor(
img, cv2.COLOR_BGR2GRAY) # convert the color image to gray image
contours = get_gray_countour(img_gray)
contour_dump("img/contours_full" + str(int(time.time() * 10)) + ".jpg",
contours, img)
_, contours = remove_contour(line_yellows, contours, 1)
if len(contours) == 0: return None
# _, contours = remove_contour( line_whites, contours, -1 )
# if len(contours) == 0: return None
contour_left = contour_largest(contours)
contour_dump(
"img/contours_extracted" + str(int(time.time() * 10)) + ".jpg",
contour_left, img)
return contour_left, len(line_reds)
def get_contour_from_image( img ):
line_yellows = get_yellow( img )
# line_whites = get_white( img )
line_reds = get_red( img )
global redline_cnt
if not line_reds:
redline_cnt = 0
print("no red line")
else:
redline_cnt += 1
# cmd = "redline \n"
# s.write(cmd.encode())
print("red lines:{0}".format(redline_cnt))
if redline_cnt >= 20:
cmd = "/ServoStop/run \n"
s.write(cmd.encode())
return None
img_gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) # convert the color image to gray image
contours = get_gray_countour(img_gray)
# contour_dump( "img/contours_full" + str(int(time.time()*10)) + ".jpg", contours, img)
_, contours = remove_contour( line_yellows, contours, 1 )
if len(contours) == 0: return None
# _, contours = remove_contour( line_whites, contours, -1 )
# if len(contours) == 0: return None
contour_large = contour_largest(contours)
# contour_dump( "img/contours_extracted" + str(int(time.time()*10)) + ".jpg", contour_large, img)
contour_dump( "img/contours_extracted.jpg", contour_large, img)
return contour_large