def recognize_number(clf, img):
imgs = nc.get_single_numbers(img)
res = 0
for number in imgs:
digit = pred(clf, number)
res = res * 10 + digit[0]
return res
def cut_rects(img, rects):
global img_idx
for i, rect in enumerate(rects):
img2 = get_subimage(img, rect[0], rect[1])
# dist = mc.diff(sub_imgs[i], img2)
# if mc.average(dist) > 20:
if not same_region(sub_imgs[i],img2):
break
imgs = nc.get_single_numbers(img2)
for number in imgs:
cv2.imwrite('data/train/'+str(img_idx)+'.jpg', number)
img_idx += 1
def cut_rects(img, rects):
global img_idx
label_img = op.get_subimage(img, rects[0][0], rects[0][1])
if not op.same_img(sub_imgs[0], label_img):
return
for i, rect in enumerate(rects):
if i == 0:
continue
img2 = op.get_subimage(img, rect[0], rect[1])
# dist = mc.diff(sub_imgs[i], img2)
# if mc.average(dist) > 20:
imgs = nc.get_single_numbers(img2)
for number in imgs:
cv2.imwrite('data/train5/' + str(img_idx) + '.jpg', number)
img_idx += 1
def cut_rects(img, rects):
global img_idx
label_img = op.get_subimage(img, rects[0][0],rects[0][1])
if not op.same_img(sub_imgs[0], label_img):
return
for i, rect in enumerate(rects):
if i==0:
continue
img2 = op.get_subimage(img, rect[0], rect[1])
# dist = mc.diff(sub_imgs[i], img2)
# if mc.average(dist) > 20:
imgs = nc.get_single_numbers(img2)
for number in imgs:
cv2.imwrite('data/train5/'+str(img_idx)+'.jpg', number)
img_idx += 1
