def apply_crop(self, text_box_pnts, crop_cfg):
"""
Random crop text box height top or bottom, we don't need image information in this step, only change box pnts
:param text_box_pnts: bbox of text [left-top, right-top, right-bottom, left-bottom]
:param crop_cfg:
:return:
croped_text_box_pnts
"""
height = abs(text_box_pnts[0][1] - text_box_pnts[3][1])
scale = float(height) / float(self.out_height)
croped_text_box_pnts = text_box_pnts
if prob(0.5):
top_crop = int(random.randint(crop_cfg.top.min, crop_cfg.top.max) * scale)
self.dmsg("top crop %d" % top_crop)
croped_text_box_pnts[0][1] += top_crop
croped_text_box_pnts[1][1] += top_crop
else:
bottom_crop = int(random.randint(crop_cfg.bottom.min, crop_cfg.bottom.max) * scale)
self.dmsg("bottom crop %d " % bottom_crop)
croped_text_box_pnts[2][1] -= bottom_crop
croped_text_box_pnts[3][1] -= bottom_crop
return croped_text_box_pnts
def gen_img(self):
word, font, word_size = self.pick_font()
# Background's height should much larger than raw word image's height,
# to make sure we can crop full word image after apply perspective
bg = self.gen_bg(width=word_size[0] * 8, height=word_size[1] * 8)
word_img, char_pnts, text_box_pnts, word_color = self.draw_text_on_bg_char_pts(
word, font, bg)
if self.cfg.line.enable and prob(self.cfg.line.fraction):
word_img, text_box_pnts = self.liner.apply(word_img, text_box_pnts,
word_color)
word_img, img_pnts_transformed, char_pnts_transformed = \
self.apply_perspective_transform(word_img, char_pnts,
max_x=self.cfg.perspective_transform.max_x,
max_y=self.cfg.perspective_transform.max_y,
max_z=self.cfg.perspective_transform.max_z,
gpu=self.gpu)
if self.debug:
word_img = draw_box(word_img, img_pnts_transformed, (0, 255, 0))
word_img = draw_box(word_img, char_pnts_transformed, (0, 0, 255))
# _, crop_bbox = self.crop_img(word_img, char_pnts_transformed)
# word_img = draw_bbox(word_img, crop_bbox, (255, 0, 0))
else:
word_img, char_pnts_transformed = self.crop_img(
word_img, char_pnts_transformed)
if self.cfg.noise.enable and prob(self.cfg.noise.fraction):
word_img = np.clip(word_img, 0., 255.)
word_img = self.noiser.apply(word_img)
blured = False
if self.cfg.blur.enable and prob(self.cfg.blur.fraction):
blured = True
word_img = self.apply_blur_on_output(word_img)
if not blured:
if self.cfg.prydown.enable and prob(self.cfg.prydown.fraction):
word_img = self.apply_prydown(word_img)
word_img = np.clip(word_img, 0., 255.)
return word_img, word, char_pnts_transformed
def gen_img(self):
word = self.corpus.get_sample()
font, word_size = self.pick_font(word)
# Background's height should much larger than raw word image's height,
# to make sure we can crop full word image after apply perspective
bg = self.gen_bg(width=word_size[0] * 8, height=word_size[1] * 8)
word_img, text_box_pnts, word_color = self.draw_text_on_bg(
word, font, bg)
if self.texteffect.line and prob(self.textstate.line):
word_img, text_box_pnts = self.liner.apply(word_img, text_box_pnts,
word_color)
word_img, img_pnts_transformed, text_box_pnts_transformed = \
self.apply_perspective_transform(word_img, text_box_pnts, max_x=25, max_y=25, max_z=5, gpu=self.gpu)
if self.debug:
word_img = draw_box(word_img, img_pnts_transformed, (0, 255, 0))
word_img = draw_box(word_img, text_box_pnts_transformed,
(0, 0, 255))
_, crop_bbox = self.crop_img(word_img, text_box_pnts_transformed)
word_img = draw_bbox(word_img, crop_bbox, (255, 0, 0))
else:
word_img, crop_bbox = self.crop_img(word_img,
text_box_pnts_transformed)
if self.texteffect.noise and prob(self.textstate.noise):
word_img = np.clip(word_img, 0., 255.)
word_img = self.noiser.apply(word_img)
blured = False
if self.texteffect.blur and prob(self.textstate.blur):
blured = True
word_img = self.apply_blur_on_output(word_img)
if not blured:
if self.texteffect.prydown and prob(self.textstate.prydown):
word_img = self.apply_prydown(word_img)
word_img = np.clip(word_img, 0., 255.)
return word_img, word
def get_sample(self):
if self.char_freq_counted():
if prob(BalanceCorpus.LESS_CHAR_FRACTION):
# 找到低频词所在的位置，从这个位置截取文字段
key = random.choice(self.less_chars_index_keys)
index = random.choice(self.less_chars_index[key])
num_prefix_chars = random.choice(range(0, self.length))
start = max(index - num_prefix_chars, 0)
else:
start = np.random.randint(0, len(self.corpus) - self.length)
else:
start = np.random.randint(0, len(self.corpus) - self.length)
word = self.corpus[start:start + self.length]
return word
def apply_blur_on_output(self, img):
if prob(0.5):
return self.apply_gauss_blur(img, [3, 5])
else:
return self.apply_norm_blur(img)
def gen_bg(self, width, height):
if prob(0.5):
bg = self.gen_rand_bg(int(width), int(height))
else:
bg = self.gen_bg_from_image(int(width), int(height))
return bg
def apply_under_line(self, word_img, text_box_pnts, word_color,word,font,):
y_offset = random.choice([1,2,3,4,5,6])
text_box_pnts[2][1] += y_offset
text_box_pnts[3][1] += y_offset
#print(word, font)
line_color = word_color + random.randint(0, 10)
# plt.figure('befor line')
# plt.imshow(word_img)
# plt.show()
#if prob(0.5): #0.5的概率是虚线下划线
leftBottomX, leftBottomY = text_box_pnts[3][0], text_box_pnts[3][1]
rightBottomX, rightBottomY = text_box_pnts[2][0], text_box_pnts[2][1]
#divded = len(word)
chars_size = []
leftBottomX_tmp = leftBottomX
if prob(0): #0.3概率为部分虚线或者实线下划线
word_split = re.split('\.|,|。|？|！|\n| |；|、|;|"：|。"|，"|!"',word)
if len(word_split)>0:
sub_word_index_list_in_word = []
for i in range(np.random.randint(len(word_split))): # 随机挑选n个word
a = np.random.randint(len(word_split)) #选取n个word的index
sub_word_index_list_in_word_sub =[(i.start(),i.end())for i in re.finditer(word_split[a],word)]
sub_index = np.random.randint(len(sub_word_index_list_in_word_sub))
sub_word_index_list_in_word.append(sub_word_index_list_in_word_sub[sub_index])
# if a not in random_word_index_list:
# random_word_index_list.append(a)
# else:
# continue
thickness = np.random.randint(1, 3)
for i in range(len(word)):
size = font.getsize(word[i])
chars_size.append(size)
if word[i]!= ' ':
if len(sub_word_index_list_in_word)!=0:
for index in sub_word_index_list_in_word:
if i >index[0]-1 and i <index[1]+1:
if prob(0): #部分虚线
draw_leftBottomX_tmp = leftBottomX_tmp+2
draw_rightBottomX_tmp = leftBottomX_tmp + size[0] - 2
else:
draw_leftBottomX_tmp = leftBottomX_tmp
draw_rightBottomX_tmp = leftBottomX_tmp + size[0]
dst = cv2.line(word_img, (draw_leftBottomX_tmp , leftBottomY ),
(draw_rightBottomX_tmp, leftBottomY ),
color=line_color,
thickness=thickness,
lineType=cv2.LINE_AA)
leftBottomX_tmp = leftBottomX_tmp + size[0]
# print(leftBottomX_tmp)
# plt.figure('after line')
# plt.imshow(word_img)
# plt.show()
else: #全部虚线或者实线下划线
thickness = np.random.randint(1, 3)
for i in range(len(word)):
size = font.getsize(word[i])
chars_size.append(size)
# print(size)
# xStep = (rightBottomX - leftBottomX) // divded
# yStep = (rightBottomY - leftBottomY) // divded
# for i in range(0, divded - 1):
# print('draw cor',leftBottomX_tmp,leftBottomY)
if prob(0):#0.5概率是全部虚线
draw_leftBottomX_tmp = leftBottomX_tmp + 2
draw_rightBottomX_tmp = leftBottomX_tmp + size[0] - 2
if word[i] != ' ':
dst = cv2.line(word_img, (draw_leftBottomX_tmp, leftBottomY),
(draw_rightBottomX_tmp, leftBottomY),
color=line_color,
thickness=thickness,
lineType=cv2.LINE_AA)
else: #全部实线
draw_leftBottomX_tmp = leftBottomX_tmp
draw_rightBottomX_tmp = leftBottomX_tmp + size[0]
dst = cv2.line(word_img, (draw_leftBottomX_tmp, leftBottomY),
(draw_rightBottomX_tmp, leftBottomY),
color=line_color,
thickness=thickness,
lineType=cv2.LINE_AA)
leftBottomX_tmp = leftBottomX_tmp + size[0]
# plt.figure('22222')
# plt.imshow(word_img)
# plt.show()
return dst, text_box_pnts
def apply_blur_on_output(self, img):
# 我这里分别进行测试。
if prob(0.5):
return self.apply_gauss_blur(img)
else:
return self.apply_norm_blur(img)
