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