def getPerspective(image, points):
yy, xx, _ = image.shape
tmp = np.zeros(image.shape[0:2], np.uint8);
drawContour(tmp, points, (255,), 1)
houghRatio=houghThreshold//hough_threshold_step
grid = None
for i in range(houghRatio):
lines = cv2.HoughLines(tmp, 1, np.pi / 180, houghThreshold-(i * hough_threshold_step))
if lines is None:
continue
lines = [Line(l[0], l[1]) for l in lines[0]]
(horizontal, vertical) = partitionLines(lines)
vertical = filterCloseLines(vertical, horizontal=False)
horizontal = filterCloseLines(horizontal, horizontal=True)
if len(vertical) == 2 and len(horizontal) == 2:
grid = (vertical, horizontal)
break
if grid is None:
return None
if vertical[0].getCenter()[0] > vertical[1].getCenter()[0]:
v2, v1 = vertical
else:
v1, v2 = vertical
if horizontal[0].getCenter()[1] > horizontal[1].getCenter()[1]:
h2, h1 = horizontal
else:
h1, h2 = horizontal
perspective = (h1.intersect(v1),
h1.intersect(v2),
h2.intersect(v2),
h2.intersect(v1))
## Doc ##
#tmp = cv2.cvtColor(tmp, cv2.COLOR_GRAY2BGR)
#drawContour(tmp, points, (0,0,255), 3)
#writeDocumentationImage(tmp, "contour_individual_bw")
#tmp_bw = tmp
#tmp_orig = image.copy()
#for tmp in (tmp_bw, tmp_orig):
# for l in (v1,v2,h1,h2): l.draw(tmp, (0,255,0), 2)
# for p in perspective: drawPoint(tmp, p, (255,0,0), 3)
#writeDocumentationImage(tmp_bw, "contour_lines_bw")
#writeDocumentationImage(tmp_orig, "contour_lines_orig")
## Doc ##
return perspective
def getPerspective(image, points):
yy, xx, _ = image.shape
tmp = np.zeros(image.shape[0:2], np.uint8);
drawContour(tmp, points, (255,), 1)
grid = None
for i in range(houghThreshold/hough_threshold_step):
lines = cv2.HoughLines(tmp, 1, np.pi / 180, houghThreshold-(i * hough_threshold_step))
if lines is None:
continue
lines = [Line(l[0], l[1]) for l in lines[0]]
(horizontal, vertical) = partitionLines(lines)
vertical = filterCloseLines(vertical, horizontal=False)
horizontal = filterCloseLines(horizontal, horizontal=True)
if len(vertical) == 2 and len(horizontal) == 2:
grid = (vertical, horizontal)
break
if grid is None:
return None
if vertical[0].getCenter()[0] > vertical[1].getCenter()[0]:
v2, v1 = vertical
else:
v1, v2 = vertical
if horizontal[0].getCenter()[1] > horizontal[1].getCenter()[1]:
h2, h1 = horizontal
else:
h1, h2 = horizontal
perspective = (h1.intersect(v1),
h1.intersect(v2),
h2.intersect(v2),
h2.intersect(v1))
## Doc ##
#tmp = cv2.cvtColor(tmp, cv2.COLOR_GRAY2BGR)
#drawContour(tmp, points, (0,0,255), 3)
#writeDocumentationImage(tmp, "contour_individual_bw")
#tmp_bw = tmp
#tmp_orig = image.copy()
#for tmp in (tmp_bw, tmp_orig):
# for l in (v1,v2,h1,h2): l.draw(tmp, (0,255,0), 2)
# for p in perspective: drawPoint(tmp, p, (255,0,0), 3)
#writeDocumentationImage(tmp_bw, "contour_lines_bw")
#writeDocumentationImage(tmp_orig, "contour_lines_orig")
## Doc ##
return perspective
def extractGrid(img,
nvertical,
nhorizontal,
threshold1=50,
threshold2=150,
apertureSize=3,
hough_threshold_step=20,
hough_threshold_min=50,
hough_threshold_max=150):
"""Finds the grid lines in a board image.
:param img: board image
:param nvertical: number of vertical lines
:param nhorizontal: number of horizontal lines
:returns: a pair (horizontal, vertical). Both elements are lists with the lines' positions.
"""
w, h, _ = img.shape
close_threshold_v = (w / nvertical) / 4
close_threshold_h = (h / nhorizontal) / 4
im_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thresh, im_bw = cv2.threshold(im_gray, 128, 255,
cv2.THRESH_BINARY | cv2.THRESH_OTSU)
im_canny = cv2.Canny(im_bw,
threshold1,
threshold2,
apertureSize=apertureSize)
for i in range((hough_threshold_max - hough_threshold_min + 1) /
hough_threshold_step):
lines = cv2.HoughLines(
im_canny, 1, np.pi / 180,
hough_threshold_max - (hough_threshold_step * i))
if lines is None:
continue
lines = [Line(l[0], l[1]) for l in lines[0]]
horizontal, vertical = partitionLines(lines)
vertical = filterCloseLines(vertical,
horizontal=False,
threshold=close_threshold_v)
horizontal = filterCloseLines(horizontal,
horizontal=True,
threshold=close_threshold_h)
if len(vertical) >= nvertical and \
len(horizontal) >= nhorizontal:
return (horizontal, vertical)
def extractGrid(
img,
nvertical,
nhorizontal,
threshold1=50,
threshold2=150,
apertureSize=3,
hough_threshold_step=20,
hough_threshold_min=50,
hough_threshold_max=150,
):
"""Finds the grid lines in a board image.
:param img: board image
:param nvertical: number of vertical lines
:param nhorizontal: number of horizontal lines
:returns: a pair (horizontal, vertical). Both elements are lists with the lines' positions.
"""
w, h, _ = img.shape
close_threshold_v = (w / nvertical) / 4
close_threshold_h = (h / nhorizontal) / 4
im_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thresh, im_bw = cv2.threshold(im_gray, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
im_canny = cv2.Canny(im_bw, threshold1, threshold2, apertureSize=apertureSize)
for i in range((hough_threshold_max - hough_threshold_min + 1) / hough_threshold_step):
lines = cv2.HoughLines(im_canny, 1, np.pi / 180, hough_threshold_max - (hough_threshold_step * i))
if lines is None:
continue
lines = [Line(l[0], l[1]) for l in lines[0]]
horizontal, vertical = partitionLines(lines)
vertical = filterCloseLines(vertical, horizontal=False, threshold=close_threshold_v)
horizontal = filterCloseLines(horizontal, horizontal=True, threshold=close_threshold_h)
if len(vertical) >= nvertical and len(horizontal) >= nhorizontal:
return (horizontal, vertical)