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 extractPiece(tile, margin=0.05):
imgs = [tile]
w, h, _ = tile.shape
im_gray = cv2.cvtColor(tile, cv2.COLOR_BGR2GRAY)
imgs.append(cv2.cvtColor(im_gray, cv2.COLOR_GRAY2BGR))
# im_gray = im_gray[(h*margin):(h*(1-margin)),
# (w*margin):(w*(1-margin))]
# imgs.append(cv2.cvtColor(im_gray, cv2.COLOR_GRAY2BGR))
# im_gray = cv2.equalizeHist(im_gray)
im_gray = cv2.medianBlur(im_gray, 3)
imgs.append(cv2.cvtColor(im_gray, cv2.COLOR_GRAY2BGR))
bright = np.mean(im_gray)
im_bw = im_gray
im_bw[np.where(im_gray < bright)] = 0
im_bw[np.where(im_gray >= bright)] = 255
imgs.append(cv2.cvtColor(im_bw, cv2.COLOR_GRAY2BGR))
if np.mean(im_bw) < 128:
im_bw = 255 - im_bw
imgs.append(cv2.cvtColor(im_bw, cv2.COLOR_GRAY2BGR))
#_, im_bw = cv2.threshold(im_gray, 50, 250, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
#im_bw = cv2.Canny(im_bw, 0,255, apertureSize=5)
contours, hierarchy = cv2.findContours(im_bw.copy(), cv2.RETR_CCOMP,
cv2.CHAIN_APPROX_TC89_KCOS)
hulls = [cv2.convexHull(c) for c in contours]
ids = ignoreContours(im_bw,
hulls,
max_area_percentage=0.75,
min_area_percentage=0.2)
im_bw = cv2.cvtColor(im_bw, cv2.COLOR_GRAY2BGR)
tmp = im_bw.copy()
for i in ids:
c = np.squeeze(hulls[i], 1)
drawContour(tmp, c, randomColor(), thickness=1)
imgs.append(tmp)
return imgs
