def _final_frame(self,
im,
fill,
lcurv,
rcurv,
offset,
font=cv.FONT_HERSHEY_DUPLEX,
scale_font=1,
color_font=(255, 0, 0),
show=False):
fill = prsp.warp(fill, inverse=True)
out = im.copy()
out = cv.addWeighted(out, 0.7, fill, 0.5, 0)
xtxt = 50
lcurv_text = 'Left curvature={0:.01f}m'.format(lcurv)
rcurv_text = 'Right curvature={0:.01f}m'.format(rcurv)
offset_text = 'Offset={0:.02f}m'.format(offset)
out = cv.putText(out, lcurv_text, (xtxt, 30), font, scale_font,
color_font)
out = cv.putText(out, rcurv_text, (xtxt, 60), font, scale_font,
color_font)
out = cv.putText(out, offset_text, (xtxt, 90), font, scale_font,
color_font)
if show == True:
show_images(im, out, 'origin', 'lanes', 'Lanes detected')
return out
def fill_lanes(im, llane, rlane, fill_color=(0, 255, 255), show=False):
y = llane.y
lp = np.array([np.transpose(np.vstack([llane.line, y]))])
rp = np.array([np.flipud(np.transpose(np.vstack([rlane.line, y])))])
points = np.hstack([lp, rp])
fill = np.zeros_like(im)
cv.fillPoly(fill, np.int32([points]), fill_color)
if show == True:
cpy = im.copy()
cpy = cv.addWeighted(cpy, 1, fill, 0.2, 0)
show_images(im, cpy, 'origin', 'filled warp', 'Fill lanes')
return fill
def hls_channel(im, channel='s', thresh=(0, 255), show=False):
i, title = 2, 'saturation'
if channel == 'h':
i, title = 0, 'hue'
elif channel == 'l':
i, title = 1, 'level'
chan = cv.cvtColor(im, cv.COLOR_RGB2HLS)[:, :, i]
chan[(chan < thresh[0]) | (chan > thresh[1])] = 0
if show == True:
title = '{0}, thresh={1}'.format(title, thresh)
show_images(im, chan, 'original', title, 'HLS', cmap2='gray')
return chan
def rgb_channel(im, channel='s', thresh=(0, 255), show=False):
i, title = 0, 'red'
if channel == 'g':
i, title = 1, 'green'
elif channel == 'b':
i, title = 2, 'blue'
chan = np.copy(im[:, :, i])
chan[(chan < thresh[0]) | (chan > thresh[1])] = 0
if show == True:
title = '{0}, thresh={1}'.format(title, thresh)
show_images(im, chan, 'original', title, 'RGB', cmap2='gray')
return chan
def fitlanes(im, show=False):
nonz = np.array(im.nonzero())
(pyl, pxl), (pyr, pxr) = nonzero_points(nonz)
fitl = np.polyfit(pyl, pxl, 2)
fitr = np.polyfit(pyr, pxr, 2)
if show == True:
y_axe = np.linspace(0, im.shape[0] - 1, im.shape[0])
line_l = fitl[0] * y_axe**2 + fitl[1] * y_axe + fitl[2]
line_r = fitr[0] * y_axe**2 + fitr[1] * y_axe + fitr[2]
ps_l = np.array([np.transpose(np.vstack([line_l, y_axe]))])
ps_r = np.array([np.flipud(np.transpose(np.vstack([line_r, y_axe])))])
points = np.hstack([ps_l, ps_r])
draw = np.zeros_like(im).astype(np.uint8)
cv.fillPoly(draw, np.int32([points]), (255, 255, 0))
mix = cv.addWeighted(np.uint8(im), 1, draw, 0.1, 0)
show_images(im, mix, 'origin', 'mix', 'Fit lines')
return fitl, fitr
def abs(im, orient='x', sobel_kernel=3, thresh=(20, 100), show=False):
gray = cv.cvtColor(im, cv.COLOR_RGB2GRAY)
x, y = (1, 0) if orient == "x" else (0, 1)
sobel = cv.Sobel(gray, cv.CV_64F, x, y, ksize=sobel_kernel)
abs = np.absolute(sobel)
scaled = np.uint8(255 * abs / np.max(abs))
tmin, tmax = thresh
binary = np.zeros_like(scaled)
binary[(scaled >= tmin) & (scaled <= tmax)] = 1
if show == True:
show_images(gray,
binary,
'origin',
'sobel',
'sobel thresh',
cmap1='gray',
cmap2='gray')
return binary
def magnitude(im, sobel_kernel=3, thresh=(30, 100), show=False):
gray = cv.cvtColor(im, cv.COLOR_RGB2GRAY)
sobelx = cv.Sobel(gray, cv.CV_64F, dx=1, dy=0, ksize=sobel_kernel)
sobely = cv.Sobel(gray, cv.CV_64F, dx=0, dy=1, ksize=sobel_kernel)
abs = np.sqrt(sobelx**2 + sobely**2)
scaled = np.uint8(255 * abs / np.max(abs))
binary = np.zeros_like(scaled)
tmin, tmax = thresh
binary[(scaled >= tmin) & (scaled <= tmax)] = 1
if show == True:
show_images(gray,
binary,
'origin',
'magnitude',
'Magnitude Thresholding',
cmap1='gray',
cmap2='gray')
return binary
def apply(im, show=False):
s = ColorThresholder.hls_channel(im, channel='s', thresh=(100, 255))
l = ColorThresholder.hls_channel(im, channel='l', thresh=(200, 255))
g = ColorThresholder.rgb_channel(im, channel='g', thresh=(200, 255))
m = SobelMask.magnitude(im, thresh=(15, 255))
#m = np.zeros(s.shape)
since = im.shape[0] - (im.shape[0] // 2)
m[since:, :] = 0
#l = np.zeros(s.shape)
binary = np.zeros(s.shape)
binary[(s > 0) | (l > 0) | (g > 0) | (m > 0)] = 1
if show == True:
combined = (g == m).astype(np.uint8)
binary_color = np.dstack([s, l, combined])
binary_color[binary_color == 1] = 100
show_images(im, binary_color, 'original', 'binary colored',
'Masking image')
show_images(im, binary, 'original', 'binary b&w', 'Masking image')
return binary
def direction(im, sobel_kernel=3, thresh=(.7, 1.3), show=False):
gray = cv.cvtColor(im, cv.COLOR_RGB2GRAY)
sobx = cv.Sobel(gray, cv.CV_64F, 1, 0, ksize=sobel_kernel)
soby = cv.Sobel(gray, cv.CV_64F, 0, 1, ksize=sobel_kernel)
abs_sobx = np.absolute(sobx)
abs_soby = np.absolute(soby)
arctan = np.arctan2(abs_soby, abs_sobx)
tmin, tmax = thresh
binary = np.zeros_like(arctan)
binary[(arctan >= tmin) & (arctan <= tmax)] = 1
if show == True:
show_images(gray,
binary,
'origin',
'direction',
'Direction sobel',
cmap1='gray',
cmap2='gray')
return binary
def _find_lane_points(self,
im,
num_strips=10,
radius=80,
max_radius=100,
peak_diff=60,
show=False):
strip_height = im.shape[0] // num_strips
heights = [None] * num_strips
strips = [None] * num_strips
for i in range(num_strips):
s, e = i * strip_height, (i + 1) * strip_height
heights[-i - 1] = (s, e)
strips[-i - 1] = im[s:e, :]
ly, lx = [[]] * num_strips, [[]] * num_strips
ry, rx = [[]] * num_strips, [[]] * num_strips
nonzeros = np.array(im.nonzero())
peaks = [None] * num_strips
if show == True:
cpy = im.copy()
lpeak, rpeak = 0, 0
for i in range(num_strips):
if i == 0:
lpeak, rpeak = self._find_peaks(im, mode='argmax')
lrad, rrad = max_radius, max_radius
else:
lpeak_prev, rpeak_prev = peaks[i - 1]
lpeak, rpeak = self._find_peaks(strips[i], mode='argmax')
if np.abs(lpeak_prev - lpeak) > peak_diff:
lpeak = lpeak_prev
lrad = max_radius
else:
lrad = radius
if np.abs(rpeak_prev - rpeak) > peak_diff:
rpeak = rpeak_prev
rrad = max_radius
else:
rrad = radius
lbox = ((heights[i][0], lpeak - lrad), (heights[i][1],
lpeak + lrad))
rbox = ((heights[i][0], rpeak - rrad), (heights[i][1],
rpeak + rrad))
peaks[i] = (lpeak, rpeak)
if show == True:
top, bot = lbox[0], lbox[1]
cpy = cv.rectangle(cpy, (top[1], top[0]), (bot[1], bot[0]),
(i + 1, 0, 0), 2)
top, bot = rbox[0], rbox[1]
cpy = cv.rectangle(cpy, (top[1], top[0]), (bot[1], bot[0]),
(i + 1, 0, 0), 2)
(ly[i], lx[i]), (ry[i], rx[i]) = self._nonzero_points(nonzeros,
left=lbox,
right=rbox)
left = (np.concatenate(ly), np.concatenate(lx))
right = (np.concatenate(ry), np.concatenate(rx))
if show == True:
filtered = np.zeros(im.shape[:2])
filtered[left[0], left[1]] = 1
filtered[right[0], right[1]] = 1
show_images(filtered,
cpy,
'filtered',
'regions',
'Found points',
cmap1='gray')
return left, right