# cv2.waitKey(0)
# img_copy = img.copy()
# cv2.drawContours(img_copy, [box], -1, (255, 0, 0), 2)
# cv2.imshow('box', img_copy)
#
# warp = four_point_transform(img, box)
# cv2.imshow('warp image', warp)
# cv2.waitKey(0)
# our_cnt = None
peri = cv2.arcLength(approx_cnt, True)
approx = cv2.approxPolyDP(approx_cnt, 0.02 * peri, True)
if len(approx) == 4:
our_cnt = approx
#
warp = warp(our_cnt, img)
cv2.imshow('warp image', warp)
# cv2.waitKey(0)
# shape, th_digits = detect(box, v)
# digits = cv2.findContours(th_digits.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# digits = imutils.grab_contours(digits)
# cv2.drawContours(warp, digits, -1, (255, 0, 0), 2)
# cv2.imshow('digit', warp)
# cv2.waitKey(0)
#
# digitcnts = []
# for cc in digits:
# (x, y, w, h) = cv2.boundingRect(cc)
# if (w >= 4 and w <= 40) and (h >= 25 and h <= 30):
# digitcnts.append(cc)
def addressDetect(img, maskG):
address = None
maskG_cnt, _, maskG_approx = geom.find_main_contour_approx(maskG)
W = 0
H = 0
if maskG_approx is not None and len(maskG_approx) == 4:
maskG_cnt = max(maskG_cnt, key=cv2.contourArea)
maskG_rect = cv2.minAreaRect(maskG_cnt)
maskG_box = np.int0(cv2.boxPoints(maskG_rect))
W = int(maskG_rect[1][0])
H = int(maskG_rect[1][1])
maskG_size = W * H
if maskG_size >= 1000 and maskG_size < 3000:
peri = cv2.arcLength(maskG_approx, True)
approx = cv2.approxPolyDP(maskG_approx, 0.02 * peri, True)
warp_img = warp(approx, img)
thresh = make_thresh(warp_img)
thresh_cut = []
if thresh.shape[1] >= 45:
for i in range(3):
cut_size = thresh.shape[1] // 3
if i == 2:
cut_img = thresh[:, i * cut_size:]
else:
cut_img = thresh[:, i * cut_size:(i + 1) * cut_size]
thresh_cut.append(cut_img)
digits = []
for i in range(3):
cut_img = thresh_cut[i]
each_cnts, max_cnt, box = geom.find_main_contour_box(cut_img.copy())
(x, y, w, h) = cv2.boundingRect(max_cnt)
# (x, y, w, h) = box
if i == 0:
if w < 8:
digits.append(1)
else:
digits.append(2)
elif i == 1:
digits.append(0)
else:
if w < 8 and h >= 10:
digits.append(1)
elif h >= 10:
roi = cut_img[y:y + h, x:x + w]
(roiH, roiW) = roi.shape
# (dW, dH) = (int(roiW * 0.25), int(roiH * 0.15))
(dH, dW) = (int(roiH * 0.15), int(roiW * 0.2))
dHC = int(roiH * 0.1)
segments = [
((0, 0), (roiW, dH)), # top
((0, dH), (dW, roiH // 2)), # top-left
((roiW - dW, dH), (roiW, roiH // 2)), # top-right
((0, (roiH // 2) - dHC), (roiW, (roiH // 2) + dHC)), # center
((0, roiH // 2), (dW, roiH)), # bottom-left
((roiW - dW, roiH // 2), (roiW, roiH)), # bottom-right
((0, roiH - dH), (roiW, roiH)) # bottom
]
on = [0] * len(segments)
for (segi, ((xA, yA), (xB, yB))) in enumerate(segments):
segROI = roi[yA:yB, xA:xB]
total = cv2.countNonZero(segROI)
area = (xB - xA) * (yB - yA)
if total / float(area) > 0.55:
on[segi] = 1
try:
digit = DIGITS_LOOKUP[tuple(on)]
digits.append(digit)
except:
pass
if len(digits) == 3:
address = '{}{}{}'.format(*digits[:3])
cv2.drawContours(img, [maskG_box], -1, (0, 255, 0), 2)
cv2.putText(img, '{}{}{}'.format(*digits[:3]), (img.shape[1]-100, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
return img, address
maskG_cnt = max(maskG_cnt, key=cv2.contourArea)
maskG_rect = cv2.minAreaRect(maskG_cnt)
W = int(maskG_rect[1][0])
H = int(maskG_rect[1][1])
if cv2.countNonZero(maskG) >= 1000 and (W*H >= 1000) and (W*H < 4000):
cntG, max_cntG, approx_cntG = geom.find_main_contour_approx(maskG)
img_copy = img.copy()
cv2.drawContours(img_copy, max_cntG, -1, (0, 255, 0), 2)
cv2.imshow('Green contours', img_copy)
# cv2.waitKey(0)
peri = cv2.arcLength(approx_cntG, True)
approx = cv2.approxPolyDP(approx_cntG, 0.02*peri, True)
if len(approx) == 4 :
our_cnt = approx
warp_img = warp(our_cnt, img)
cv2.imshow('warp', warp_img)
# cv2.waitKey(0)
warp_gray = cv2.cvtColor(warp_img, cv2.COLOR_BGR2GRAY)
warp_gray = cv2.GaussianBlur(warp_gray, (3,3),0)
thresh = cv2.threshold(warp_gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]
# thresh = cv2.adaptiveThreshold(warp_gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY|cv2.THRESH_OTSU, 3, 2)[1]
th_kernel = np.ones((2,2), np.uint8)
thresh = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, th_kernel)
thresh = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, th_kernel)
cv2.imshow('thresh', thresh)
cv2.waitKey(0)
thresh_cut = []
if thresh.shape[1] < 50 :