def get_ratio(img,
x_wheel_left, y_wheel_left, x_wheel_right, y_wheel_right,
last_ratio,
column_factor, row_factor,
correction):
image = im.load_image(str(img))
height = len(image)
width = len(image[0])
intersections = convert_to_pairs(image, height, width, column_factor, row_factor)
print intersection
for intersection in intersections:
new_intersection = []
if is_odd(len(intersection)):
return last_ratio
left_white_lines = []
for i in xrange(0,len(intersections[0])/2):
new_point = (intersections[0][2*i], intersections[0][2*i+1])
left_white_lines.append(new_point)
top_white_lines = []
for i in xrange(len(intersections[2])/2):
new_point = (intersections[2][2*i], intersections[2][2*i+1])
top_white_lines.append(new_point)
right_white_lines = []
for i in xrange(len(intersections[1])/2):
new_point = (intersections[1][-2*i-1], intersections[1][-2*i])
right_white_lines.append(new_point)
bottom_white_lines = []
for i in xrange(0,len(intersections[3])/2):
new_point = (intersections[3][-2*i-1], intersections[3][-2*i])
bottom_white_lines.append(new_point)
# + top_white_lines
white_lines = left_white_lines + right_white_lines + bottom_white_lines
destination = choose_path(white_lines)
x_right = destination[0][0]
y_right = destination[0][1]
x_left = destination[1][0]
y_left = destination[1][1]
left_distance = np.sqrt((x_left - x_wheel_left)**2 + (y_left - y_wheel_left)**2)
right_distance= np.sqrt((x_right - x_wheel_right)**2 + (y_right - y_wheel_right)**2)
ratio = right_distance/left_distance
last_ratio = correction*ratio
#print 'Ratio: ' + str(correction*ratio)
return correction*ratio
def get_ratio(img, x_wheel_left, y_wheel_left, x_wheel_right, y_wheel_right,
last_ratio, column_factor, row_factor, correction):
image = im.load_image(str(img))
height = len(image)
width = len(image[0])
intersections = convert_to_pairs(image, height, width, column_factor,
row_factor)
print intersection
for intersection in intersections:
new_intersection = []
if is_odd(len(intersection)):
return last_ratio
left_white_lines = []
for i in xrange(0, len(intersections[0]) / 2):
new_point = (intersections[0][2 * i], intersections[0][2 * i + 1])
left_white_lines.append(new_point)
top_white_lines = []
for i in xrange(len(intersections[2]) / 2):
new_point = (intersections[2][2 * i], intersections[2][2 * i + 1])
top_white_lines.append(new_point)
right_white_lines = []
for i in xrange(len(intersections[1]) / 2):
new_point = (intersections[1][-2 * i - 1], intersections[1][-2 * i])
right_white_lines.append(new_point)
bottom_white_lines = []
for i in xrange(0, len(intersections[3]) / 2):
new_point = (intersections[3][-2 * i - 1], intersections[3][-2 * i])
bottom_white_lines.append(new_point)
# + top_white_lines
white_lines = left_white_lines + right_white_lines + bottom_white_lines
destination = choose_path(white_lines)
x_right = destination[0][0]
y_right = destination[0][1]
x_left = destination[1][0]
y_left = destination[1][1]
left_distance = np.sqrt((x_left - x_wheel_left)**2 +
(y_left - y_wheel_left)**2)
right_distance = np.sqrt((x_right - x_wheel_right)**2 +
(y_right - y_wheel_right)**2)
ratio = right_distance / left_distance
last_ratio = correction * ratio
#print 'Ratio: ' + str(correction*ratio)
return correction * ratio
def is_redundant_point(tuple1, tuple2):
return (fuzzyequal(tuple1[0], tuple2[0], group_factor)
or fuzzyequal(tuple1[1], tuple2[1], group_factor))
def fuzzyequal(x, y, epsilon):
return (abs(x - y) < epsilon)
def choose_path(white_lines):
return white_lines[0]
start = time.time()
for k in xrange(1, 10):
t0 = time.time()
image = im.load_image('picture_' + str(k) + '.jpg')
height = len(image)
width = len(image[0])
t1 = time.time()
a = Image.open('picture_' + str(k) + '.jpg')
t2 = time.time()
get_ratio(image, x_wheel_left, y_wheel_left, x_wheel_right, y_wheel_right,
last_ratio, column_factor, row_factor, correction, k, a)
t3 = time.time()
print t3 - t2 + t1 - t0
end = time.time()
top_row_intersections = im.fast_check_row(top_row, image, left_column, right_column)
bottom_row_intersections = im.fast_check_row(bottom_row, image, left_column, right_column)
return (left_column_intersections, right_column_intersections, top_row_intersections, bottom_row_intersections)
def is_redundant_point(tuple1, tuple2):
return (fuzzyequal (tuple1[0], tuple2[0], group_factor) or fuzzyequal (tuple1[1], tuple2[1], group_factor))
def fuzzyequal(x, y, epsilon):
return (abs(x-y) < epsilon)
def choose_path(white_lines):
return white_lines[0]
start = time.time()
for k in xrange(1,10):
t0 = time.time()
image = im.load_image('picture_' + str(k) + '.jpg')
height = len(image)
width = len(image[0])
t1 = time.time()
a = Image.open('picture_' + str(k) + '.jpg')
t2 = time.time()
get_ratio(image,
x_wheel_left, y_wheel_left, x_wheel_right, y_wheel_right,
last_ratio,
column_factor, row_factor,
correction, k, a)
t3 = time.time()
print t3-t2+t1-t0
end = time.time()