907 lines
35 KiB
Python
907 lines
35 KiB
Python
# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
import math
|
|
import cv2
|
|
import numpy as np
|
|
|
|
__all__ = ['PGProcessTrain']
|
|
|
|
|
|
class PGProcessTrain(object):
|
|
def __init__(self,
|
|
character_dict_path,
|
|
max_text_length,
|
|
max_text_nums,
|
|
tcl_len,
|
|
batch_size=14,
|
|
min_crop_size=24,
|
|
min_text_size=4,
|
|
max_text_size=512,
|
|
**kwargs):
|
|
self.tcl_len = tcl_len
|
|
self.max_text_length = max_text_length
|
|
self.max_text_nums = max_text_nums
|
|
self.batch_size = batch_size
|
|
self.min_crop_size = min_crop_size
|
|
self.min_text_size = min_text_size
|
|
self.max_text_size = max_text_size
|
|
self.Lexicon_Table = self.get_dict(character_dict_path)
|
|
self.pad_num = len(self.Lexicon_Table)
|
|
self.img_id = 0
|
|
|
|
def get_dict(self, character_dict_path):
|
|
character_str = ""
|
|
with open(character_dict_path, "rb") as fin:
|
|
lines = fin.readlines()
|
|
for line in lines:
|
|
line = line.decode('utf-8').strip("\n").strip("\r\n")
|
|
character_str += line
|
|
dict_character = list(character_str)
|
|
return dict_character
|
|
|
|
def quad_area(self, poly):
|
|
"""
|
|
compute area of a polygon
|
|
:param poly:
|
|
:return:
|
|
"""
|
|
edge = [(poly[1][0] - poly[0][0]) * (poly[1][1] + poly[0][1]),
|
|
(poly[2][0] - poly[1][0]) * (poly[2][1] + poly[1][1]),
|
|
(poly[3][0] - poly[2][0]) * (poly[3][1] + poly[2][1]),
|
|
(poly[0][0] - poly[3][0]) * (poly[0][1] + poly[3][1])]
|
|
return np.sum(edge) / 2.
|
|
|
|
def gen_quad_from_poly(self, poly):
|
|
"""
|
|
Generate min area quad from poly.
|
|
"""
|
|
point_num = poly.shape[0]
|
|
min_area_quad = np.zeros((4, 2), dtype=np.float32)
|
|
rect = cv2.minAreaRect(poly.astype(
|
|
np.int32)) # (center (x,y), (width, height), angle of rotation)
|
|
box = np.array(cv2.boxPoints(rect))
|
|
|
|
first_point_idx = 0
|
|
min_dist = 1e4
|
|
for i in range(4):
|
|
dist = np.linalg.norm(box[(i + 0) % 4] - poly[0]) + \
|
|
np.linalg.norm(box[(i + 1) % 4] - poly[point_num // 2 - 1]) + \
|
|
np.linalg.norm(box[(i + 2) % 4] - poly[point_num // 2]) + \
|
|
np.linalg.norm(box[(i + 3) % 4] - poly[-1])
|
|
if dist < min_dist:
|
|
min_dist = dist
|
|
first_point_idx = i
|
|
for i in range(4):
|
|
min_area_quad[i] = box[(first_point_idx + i) % 4]
|
|
|
|
return min_area_quad
|
|
|
|
def check_and_validate_polys(self, polys, tags, im_size):
|
|
"""
|
|
check so that the text poly is in the same direction,
|
|
and also filter some invalid polygons
|
|
:param polys:
|
|
:param tags:
|
|
:return:
|
|
"""
|
|
(h, w) = im_size
|
|
if polys.shape[0] == 0:
|
|
return polys, np.array([]), np.array([])
|
|
polys[:, :, 0] = np.clip(polys[:, :, 0], 0, w - 1)
|
|
polys[:, :, 1] = np.clip(polys[:, :, 1], 0, h - 1)
|
|
|
|
validated_polys = []
|
|
validated_tags = []
|
|
hv_tags = []
|
|
for poly, tag in zip(polys, tags):
|
|
quad = self.gen_quad_from_poly(poly)
|
|
p_area = self.quad_area(quad)
|
|
if abs(p_area) < 1:
|
|
print('invalid poly')
|
|
continue
|
|
if p_area > 0:
|
|
if tag == False:
|
|
print('poly in wrong direction')
|
|
tag = True # reversed cases should be ignore
|
|
poly = poly[(0, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2,
|
|
1), :]
|
|
quad = quad[(0, 3, 2, 1), :]
|
|
|
|
len_w = np.linalg.norm(quad[0] - quad[1]) + np.linalg.norm(quad[3] -
|
|
quad[2])
|
|
len_h = np.linalg.norm(quad[0] - quad[3]) + np.linalg.norm(quad[1] -
|
|
quad[2])
|
|
hv_tag = 1
|
|
|
|
if len_w * 2.0 < len_h:
|
|
hv_tag = 0
|
|
|
|
validated_polys.append(poly)
|
|
validated_tags.append(tag)
|
|
hv_tags.append(hv_tag)
|
|
return np.array(validated_polys), np.array(validated_tags), np.array(
|
|
hv_tags)
|
|
|
|
def crop_area(self,
|
|
im,
|
|
polys,
|
|
tags,
|
|
hv_tags,
|
|
txts,
|
|
crop_background=False,
|
|
max_tries=25):
|
|
"""
|
|
make random crop from the input image
|
|
:param im:
|
|
:param polys: [b,4,2]
|
|
:param tags:
|
|
:param crop_background:
|
|
:param max_tries: 50 -> 25
|
|
:return:
|
|
"""
|
|
h, w, _ = im.shape
|
|
pad_h = h // 10
|
|
pad_w = w // 10
|
|
h_array = np.zeros((h + pad_h * 2), dtype=np.int32)
|
|
w_array = np.zeros((w + pad_w * 2), dtype=np.int32)
|
|
for poly in polys:
|
|
poly = np.round(poly, decimals=0).astype(np.int32)
|
|
minx = np.min(poly[:, 0])
|
|
maxx = np.max(poly[:, 0])
|
|
w_array[minx + pad_w:maxx + pad_w] = 1
|
|
miny = np.min(poly[:, 1])
|
|
maxy = np.max(poly[:, 1])
|
|
h_array[miny + pad_h:maxy + pad_h] = 1
|
|
# ensure the cropped area not across a text
|
|
h_axis = np.where(h_array == 0)[0]
|
|
w_axis = np.where(w_array == 0)[0]
|
|
if len(h_axis) == 0 or len(w_axis) == 0:
|
|
return im, polys, tags, hv_tags, txts
|
|
for i in range(max_tries):
|
|
xx = np.random.choice(w_axis, size=2)
|
|
xmin = np.min(xx) - pad_w
|
|
xmax = np.max(xx) - pad_w
|
|
xmin = np.clip(xmin, 0, w - 1)
|
|
xmax = np.clip(xmax, 0, w - 1)
|
|
yy = np.random.choice(h_axis, size=2)
|
|
ymin = np.min(yy) - pad_h
|
|
ymax = np.max(yy) - pad_h
|
|
ymin = np.clip(ymin, 0, h - 1)
|
|
ymax = np.clip(ymax, 0, h - 1)
|
|
if xmax - xmin < self.min_crop_size or \
|
|
ymax - ymin < self.min_crop_size:
|
|
continue
|
|
if polys.shape[0] != 0:
|
|
poly_axis_in_area = (polys[:, :, 0] >= xmin) & (polys[:, :, 0] <= xmax) \
|
|
& (polys[:, :, 1] >= ymin) & (polys[:, :, 1] <= ymax)
|
|
selected_polys = np.where(
|
|
np.sum(poly_axis_in_area, axis=1) == 4)[0]
|
|
else:
|
|
selected_polys = []
|
|
if len(selected_polys) == 0:
|
|
# no text in this area
|
|
if crop_background:
|
|
txts_tmp = []
|
|
for selected_poly in selected_polys:
|
|
txts_tmp.append(txts[selected_poly])
|
|
txts = txts_tmp
|
|
return im[ymin: ymax + 1, xmin: xmax + 1, :], \
|
|
polys[selected_polys], tags[selected_polys], hv_tags[selected_polys], txts
|
|
else:
|
|
continue
|
|
im = im[ymin:ymax + 1, xmin:xmax + 1, :]
|
|
polys = polys[selected_polys]
|
|
tags = tags[selected_polys]
|
|
hv_tags = hv_tags[selected_polys]
|
|
txts_tmp = []
|
|
for selected_poly in selected_polys:
|
|
txts_tmp.append(txts[selected_poly])
|
|
txts = txts_tmp
|
|
polys[:, :, 0] -= xmin
|
|
polys[:, :, 1] -= ymin
|
|
return im, polys, tags, hv_tags, txts
|
|
|
|
return im, polys, tags, hv_tags, txts
|
|
|
|
def fit_and_gather_tcl_points_v2(self,
|
|
min_area_quad,
|
|
poly,
|
|
max_h,
|
|
max_w,
|
|
fixed_point_num=64,
|
|
img_id=0,
|
|
reference_height=3):
|
|
"""
|
|
Find the center point of poly as key_points, then fit and gather.
|
|
"""
|
|
key_point_xys = []
|
|
point_num = poly.shape[0]
|
|
for idx in range(point_num // 2):
|
|
center_point = (poly[idx] + poly[point_num - 1 - idx]) / 2.0
|
|
key_point_xys.append(center_point)
|
|
|
|
tmp_image = np.zeros(
|
|
shape=(
|
|
max_h,
|
|
max_w, ), dtype='float32')
|
|
cv2.polylines(tmp_image, [np.array(key_point_xys).astype('int32')],
|
|
False, 1.0)
|
|
ys, xs = np.where(tmp_image > 0)
|
|
xy_text = np.array(list(zip(xs, ys)), dtype='float32')
|
|
|
|
left_center_pt = (
|
|
(min_area_quad[0] - min_area_quad[1]) / 2.0).reshape(1, 2)
|
|
right_center_pt = (
|
|
(min_area_quad[1] - min_area_quad[2]) / 2.0).reshape(1, 2)
|
|
proj_unit_vec = (right_center_pt - left_center_pt) / (
|
|
np.linalg.norm(right_center_pt - left_center_pt) + 1e-6)
|
|
proj_unit_vec_tile = np.tile(proj_unit_vec,
|
|
(xy_text.shape[0], 1)) # (n, 2)
|
|
left_center_pt_tile = np.tile(left_center_pt,
|
|
(xy_text.shape[0], 1)) # (n, 2)
|
|
xy_text_to_left_center = xy_text - left_center_pt_tile
|
|
proj_value = np.sum(xy_text_to_left_center * proj_unit_vec_tile, axis=1)
|
|
xy_text = xy_text[np.argsort(proj_value)]
|
|
|
|
# convert to np and keep the num of point not greater then fixed_point_num
|
|
pos_info = np.array(xy_text).reshape(-1, 2)[:, ::-1] # xy-> yx
|
|
point_num = len(pos_info)
|
|
if point_num > fixed_point_num:
|
|
keep_ids = [
|
|
int((point_num * 1.0 / fixed_point_num) * x)
|
|
for x in range(fixed_point_num)
|
|
]
|
|
pos_info = pos_info[keep_ids, :]
|
|
|
|
keep = int(min(len(pos_info), fixed_point_num))
|
|
if np.random.rand() < 0.2 and reference_height >= 3:
|
|
dl = (np.random.rand(keep) - 0.5) * reference_height * 0.3
|
|
random_float = np.array([1, 0]).reshape([1, 2]) * dl.reshape(
|
|
[keep, 1])
|
|
pos_info += random_float
|
|
pos_info[:, 0] = np.clip(pos_info[:, 0], 0, max_h - 1)
|
|
pos_info[:, 1] = np.clip(pos_info[:, 1], 0, max_w - 1)
|
|
|
|
# padding to fixed length
|
|
pos_l = np.zeros((self.tcl_len, 3), dtype=np.int32)
|
|
pos_l[:, 0] = np.ones((self.tcl_len, )) * img_id
|
|
pos_m = np.zeros((self.tcl_len, 1), dtype=np.float32)
|
|
pos_l[:keep, 1:] = np.round(pos_info).astype(np.int32)
|
|
pos_m[:keep] = 1.0
|
|
return pos_l, pos_m
|
|
|
|
def generate_direction_map(self, poly_quads, n_char, direction_map):
|
|
"""
|
|
"""
|
|
width_list = []
|
|
height_list = []
|
|
for quad in poly_quads:
|
|
quad_w = (np.linalg.norm(quad[0] - quad[1]) +
|
|
np.linalg.norm(quad[2] - quad[3])) / 2.0
|
|
quad_h = (np.linalg.norm(quad[0] - quad[3]) +
|
|
np.linalg.norm(quad[2] - quad[1])) / 2.0
|
|
width_list.append(quad_w)
|
|
height_list.append(quad_h)
|
|
norm_width = max(sum(width_list) / n_char, 1.0)
|
|
average_height = max(sum(height_list) / len(height_list), 1.0)
|
|
k = 1
|
|
for quad in poly_quads:
|
|
direct_vector_full = (
|
|
(quad[1] + quad[2]) - (quad[0] + quad[3])) / 2.0
|
|
direct_vector = direct_vector_full / (
|
|
np.linalg.norm(direct_vector_full) + 1e-6) * norm_width
|
|
direction_label = tuple(
|
|
map(float,
|
|
[direct_vector[0], direct_vector[1], 1.0 / average_height]))
|
|
cv2.fillPoly(direction_map,
|
|
quad.round().astype(np.int32)[np.newaxis, :, :],
|
|
direction_label)
|
|
k += 1
|
|
return direction_map
|
|
|
|
def calculate_average_height(self, poly_quads):
|
|
"""
|
|
"""
|
|
height_list = []
|
|
for quad in poly_quads:
|
|
quad_h = (np.linalg.norm(quad[0] - quad[3]) +
|
|
np.linalg.norm(quad[2] - quad[1])) / 2.0
|
|
height_list.append(quad_h)
|
|
average_height = max(sum(height_list) / len(height_list), 1.0)
|
|
return average_height
|
|
|
|
def generate_tcl_ctc_label(self,
|
|
h,
|
|
w,
|
|
polys,
|
|
tags,
|
|
text_strs,
|
|
ds_ratio,
|
|
tcl_ratio=0.3,
|
|
shrink_ratio_of_width=0.15):
|
|
"""
|
|
Generate polygon.
|
|
"""
|
|
score_map_big = np.zeros(
|
|
(
|
|
h,
|
|
w, ), dtype=np.float32)
|
|
h, w = int(h * ds_ratio), int(w * ds_ratio)
|
|
polys = polys * ds_ratio
|
|
|
|
score_map = np.zeros(
|
|
(
|
|
h,
|
|
w, ), dtype=np.float32)
|
|
score_label_map = np.zeros(
|
|
(
|
|
h,
|
|
w, ), dtype=np.float32)
|
|
tbo_map = np.zeros((h, w, 5), dtype=np.float32)
|
|
training_mask = np.ones(
|
|
(
|
|
h,
|
|
w, ), dtype=np.float32)
|
|
direction_map = np.ones((h, w, 3)) * np.array([0, 0, 1]).reshape(
|
|
[1, 1, 3]).astype(np.float32)
|
|
|
|
label_idx = 0
|
|
score_label_map_text_label_list = []
|
|
pos_list, pos_mask, label_list = [], [], []
|
|
for poly_idx, poly_tag in enumerate(zip(polys, tags)):
|
|
poly = poly_tag[0]
|
|
tag = poly_tag[1]
|
|
|
|
# generate min_area_quad
|
|
min_area_quad, center_point = self.gen_min_area_quad_from_poly(poly)
|
|
min_area_quad_h = 0.5 * (
|
|
np.linalg.norm(min_area_quad[0] - min_area_quad[3]) +
|
|
np.linalg.norm(min_area_quad[1] - min_area_quad[2]))
|
|
min_area_quad_w = 0.5 * (
|
|
np.linalg.norm(min_area_quad[0] - min_area_quad[1]) +
|
|
np.linalg.norm(min_area_quad[2] - min_area_quad[3]))
|
|
|
|
if min(min_area_quad_h, min_area_quad_w) < self.min_text_size * ds_ratio \
|
|
or min(min_area_quad_h, min_area_quad_w) > self.max_text_size * ds_ratio:
|
|
continue
|
|
|
|
if tag:
|
|
cv2.fillPoly(training_mask,
|
|
poly.astype(np.int32)[np.newaxis, :, :], 0.15)
|
|
else:
|
|
text_label = text_strs[poly_idx]
|
|
text_label = self.prepare_text_label(text_label,
|
|
self.Lexicon_Table)
|
|
|
|
text_label_index_list = [[self.Lexicon_Table.index(c_)]
|
|
for c_ in text_label
|
|
if c_ in self.Lexicon_Table]
|
|
if len(text_label_index_list) < 1:
|
|
continue
|
|
|
|
tcl_poly = self.poly2tcl(poly, tcl_ratio)
|
|
tcl_quads = self.poly2quads(tcl_poly)
|
|
poly_quads = self.poly2quads(poly)
|
|
|
|
stcl_quads, quad_index = self.shrink_poly_along_width(
|
|
tcl_quads,
|
|
shrink_ratio_of_width=shrink_ratio_of_width,
|
|
expand_height_ratio=1.0 / tcl_ratio)
|
|
|
|
cv2.fillPoly(score_map,
|
|
np.round(stcl_quads).astype(np.int32), 1.0)
|
|
cv2.fillPoly(score_map_big,
|
|
np.round(stcl_quads / ds_ratio).astype(np.int32),
|
|
1.0)
|
|
|
|
for idx, quad in enumerate(stcl_quads):
|
|
quad_mask = np.zeros((h, w), dtype=np.float32)
|
|
quad_mask = cv2.fillPoly(
|
|
quad_mask,
|
|
np.round(quad[np.newaxis, :, :]).astype(np.int32), 1.0)
|
|
tbo_map = self.gen_quad_tbo(poly_quads[quad_index[idx]],
|
|
quad_mask, tbo_map)
|
|
|
|
# score label map and score_label_map_text_label_list for refine
|
|
if label_idx == 0:
|
|
text_pos_list_ = [[len(self.Lexicon_Table)], ]
|
|
score_label_map_text_label_list.append(text_pos_list_)
|
|
|
|
label_idx += 1
|
|
cv2.fillPoly(score_label_map,
|
|
np.round(poly_quads).astype(np.int32), label_idx)
|
|
score_label_map_text_label_list.append(text_label_index_list)
|
|
|
|
# direction info, fix-me
|
|
n_char = len(text_label_index_list)
|
|
direction_map = self.generate_direction_map(poly_quads, n_char,
|
|
direction_map)
|
|
|
|
# pos info
|
|
average_shrink_height = self.calculate_average_height(
|
|
stcl_quads)
|
|
pos_l, pos_m = self.fit_and_gather_tcl_points_v2(
|
|
min_area_quad,
|
|
poly,
|
|
max_h=h,
|
|
max_w=w,
|
|
fixed_point_num=64,
|
|
img_id=self.img_id,
|
|
reference_height=average_shrink_height)
|
|
|
|
label_l = text_label_index_list
|
|
if len(text_label_index_list) < 2:
|
|
continue
|
|
|
|
pos_list.append(pos_l)
|
|
pos_mask.append(pos_m)
|
|
label_list.append(label_l)
|
|
|
|
# use big score_map for smooth tcl lines
|
|
score_map_big_resized = cv2.resize(
|
|
score_map_big, dsize=None, fx=ds_ratio, fy=ds_ratio)
|
|
score_map = np.array(score_map_big_resized > 1e-3, dtype='float32')
|
|
|
|
return score_map, score_label_map, tbo_map, direction_map, training_mask, \
|
|
pos_list, pos_mask, label_list, score_label_map_text_label_list
|
|
|
|
def adjust_point(self, poly):
|
|
"""
|
|
adjust point order.
|
|
"""
|
|
point_num = poly.shape[0]
|
|
if point_num == 4:
|
|
len_1 = np.linalg.norm(poly[0] - poly[1])
|
|
len_2 = np.linalg.norm(poly[1] - poly[2])
|
|
len_3 = np.linalg.norm(poly[2] - poly[3])
|
|
len_4 = np.linalg.norm(poly[3] - poly[0])
|
|
|
|
if (len_1 + len_3) * 1.5 < (len_2 + len_4):
|
|
poly = poly[[1, 2, 3, 0], :]
|
|
|
|
elif point_num > 4:
|
|
vector_1 = poly[0] - poly[1]
|
|
vector_2 = poly[1] - poly[2]
|
|
cos_theta = np.dot(vector_1, vector_2) / (
|
|
np.linalg.norm(vector_1) * np.linalg.norm(vector_2) + 1e-6)
|
|
theta = np.arccos(np.round(cos_theta, decimals=4))
|
|
|
|
if abs(theta) > (70 / 180 * math.pi):
|
|
index = list(range(1, point_num)) + [0]
|
|
poly = poly[np.array(index), :]
|
|
return poly
|
|
|
|
def gen_min_area_quad_from_poly(self, poly):
|
|
"""
|
|
Generate min area quad from poly.
|
|
"""
|
|
point_num = poly.shape[0]
|
|
min_area_quad = np.zeros((4, 2), dtype=np.float32)
|
|
if point_num == 4:
|
|
min_area_quad = poly
|
|
center_point = np.sum(poly, axis=0) / 4
|
|
else:
|
|
rect = cv2.minAreaRect(poly.astype(
|
|
np.int32)) # (center (x,y), (width, height), angle of rotation)
|
|
center_point = rect[0]
|
|
box = np.array(cv2.boxPoints(rect))
|
|
|
|
first_point_idx = 0
|
|
min_dist = 1e4
|
|
for i in range(4):
|
|
dist = np.linalg.norm(box[(i + 0) % 4] - poly[0]) + \
|
|
np.linalg.norm(box[(i + 1) % 4] - poly[point_num // 2 - 1]) + \
|
|
np.linalg.norm(box[(i + 2) % 4] - poly[point_num // 2]) + \
|
|
np.linalg.norm(box[(i + 3) % 4] - poly[-1])
|
|
if dist < min_dist:
|
|
min_dist = dist
|
|
first_point_idx = i
|
|
|
|
for i in range(4):
|
|
min_area_quad[i] = box[(first_point_idx + i) % 4]
|
|
|
|
return min_area_quad, center_point
|
|
|
|
def shrink_quad_along_width(self,
|
|
quad,
|
|
begin_width_ratio=0.,
|
|
end_width_ratio=1.):
|
|
"""
|
|
Generate shrink_quad_along_width.
|
|
"""
|
|
ratio_pair = np.array(
|
|
[[begin_width_ratio], [end_width_ratio]], dtype=np.float32)
|
|
p0_1 = quad[0] + (quad[1] - quad[0]) * ratio_pair
|
|
p3_2 = quad[3] + (quad[2] - quad[3]) * ratio_pair
|
|
return np.array([p0_1[0], p0_1[1], p3_2[1], p3_2[0]])
|
|
|
|
def shrink_poly_along_width(self,
|
|
quads,
|
|
shrink_ratio_of_width,
|
|
expand_height_ratio=1.0):
|
|
"""
|
|
shrink poly with given length.
|
|
"""
|
|
upper_edge_list = []
|
|
|
|
def get_cut_info(edge_len_list, cut_len):
|
|
for idx, edge_len in enumerate(edge_len_list):
|
|
cut_len -= edge_len
|
|
if cut_len <= 0.000001:
|
|
ratio = (cut_len + edge_len_list[idx]) / edge_len_list[idx]
|
|
return idx, ratio
|
|
|
|
for quad in quads:
|
|
upper_edge_len = np.linalg.norm(quad[0] - quad[1])
|
|
upper_edge_list.append(upper_edge_len)
|
|
|
|
# length of left edge and right edge.
|
|
left_length = np.linalg.norm(quads[0][0] - quads[0][
|
|
3]) * expand_height_ratio
|
|
right_length = np.linalg.norm(quads[-1][1] - quads[-1][
|
|
2]) * expand_height_ratio
|
|
|
|
shrink_length = min(left_length, right_length,
|
|
sum(upper_edge_list)) * shrink_ratio_of_width
|
|
# shrinking length
|
|
upper_len_left = shrink_length
|
|
upper_len_right = sum(upper_edge_list) - shrink_length
|
|
|
|
left_idx, left_ratio = get_cut_info(upper_edge_list, upper_len_left)
|
|
left_quad = self.shrink_quad_along_width(
|
|
quads[left_idx], begin_width_ratio=left_ratio, end_width_ratio=1)
|
|
right_idx, right_ratio = get_cut_info(upper_edge_list, upper_len_right)
|
|
right_quad = self.shrink_quad_along_width(
|
|
quads[right_idx], begin_width_ratio=0, end_width_ratio=right_ratio)
|
|
|
|
out_quad_list = []
|
|
if left_idx == right_idx:
|
|
out_quad_list.append(
|
|
[left_quad[0], right_quad[1], right_quad[2], left_quad[3]])
|
|
else:
|
|
out_quad_list.append(left_quad)
|
|
for idx in range(left_idx + 1, right_idx):
|
|
out_quad_list.append(quads[idx])
|
|
out_quad_list.append(right_quad)
|
|
|
|
return np.array(out_quad_list), list(range(left_idx, right_idx + 1))
|
|
|
|
def prepare_text_label(self, label_str, Lexicon_Table):
|
|
"""
|
|
Prepare text lablel by given Lexicon_Table.
|
|
"""
|
|
if len(Lexicon_Table) == 36:
|
|
return label_str.lower()
|
|
else:
|
|
return label_str
|
|
|
|
def vector_angle(self, A, B):
|
|
"""
|
|
Calculate the angle between vector AB and x-axis positive direction.
|
|
"""
|
|
AB = np.array([B[1] - A[1], B[0] - A[0]])
|
|
return np.arctan2(*AB)
|
|
|
|
def theta_line_cross_point(self, theta, point):
|
|
"""
|
|
Calculate the line through given point and angle in ax + by + c =0 form.
|
|
"""
|
|
x, y = point
|
|
cos = np.cos(theta)
|
|
sin = np.sin(theta)
|
|
return [sin, -cos, cos * y - sin * x]
|
|
|
|
def line_cross_two_point(self, A, B):
|
|
"""
|
|
Calculate the line through given point A and B in ax + by + c =0 form.
|
|
"""
|
|
angle = self.vector_angle(A, B)
|
|
return self.theta_line_cross_point(angle, A)
|
|
|
|
def average_angle(self, poly):
|
|
"""
|
|
Calculate the average angle between left and right edge in given poly.
|
|
"""
|
|
p0, p1, p2, p3 = poly
|
|
angle30 = self.vector_angle(p3, p0)
|
|
angle21 = self.vector_angle(p2, p1)
|
|
return (angle30 + angle21) / 2
|
|
|
|
def line_cross_point(self, line1, line2):
|
|
"""
|
|
line1 and line2 in 0=ax+by+c form, compute the cross point of line1 and line2
|
|
"""
|
|
a1, b1, c1 = line1
|
|
a2, b2, c2 = line2
|
|
d = a1 * b2 - a2 * b1
|
|
|
|
if d == 0:
|
|
print('Cross point does not exist')
|
|
return np.array([0, 0], dtype=np.float32)
|
|
else:
|
|
x = (b1 * c2 - b2 * c1) / d
|
|
y = (a2 * c1 - a1 * c2) / d
|
|
|
|
return np.array([x, y], dtype=np.float32)
|
|
|
|
def quad2tcl(self, poly, ratio):
|
|
"""
|
|
Generate center line by poly clock-wise point. (4, 2)
|
|
"""
|
|
ratio_pair = np.array(
|
|
[[0.5 - ratio / 2], [0.5 + ratio / 2]], dtype=np.float32)
|
|
p0_3 = poly[0] + (poly[3] - poly[0]) * ratio_pair
|
|
p1_2 = poly[1] + (poly[2] - poly[1]) * ratio_pair
|
|
return np.array([p0_3[0], p1_2[0], p1_2[1], p0_3[1]])
|
|
|
|
def poly2tcl(self, poly, ratio):
|
|
"""
|
|
Generate center line by poly clock-wise point.
|
|
"""
|
|
ratio_pair = np.array(
|
|
[[0.5 - ratio / 2], [0.5 + ratio / 2]], dtype=np.float32)
|
|
tcl_poly = np.zeros_like(poly)
|
|
point_num = poly.shape[0]
|
|
|
|
for idx in range(point_num // 2):
|
|
point_pair = poly[idx] + (poly[point_num - 1 - idx] - poly[idx]
|
|
) * ratio_pair
|
|
tcl_poly[idx] = point_pair[0]
|
|
tcl_poly[point_num - 1 - idx] = point_pair[1]
|
|
return tcl_poly
|
|
|
|
def gen_quad_tbo(self, quad, tcl_mask, tbo_map):
|
|
"""
|
|
Generate tbo_map for give quad.
|
|
"""
|
|
# upper and lower line function: ax + by + c = 0;
|
|
up_line = self.line_cross_two_point(quad[0], quad[1])
|
|
lower_line = self.line_cross_two_point(quad[3], quad[2])
|
|
|
|
quad_h = 0.5 * (np.linalg.norm(quad[0] - quad[3]) +
|
|
np.linalg.norm(quad[1] - quad[2]))
|
|
quad_w = 0.5 * (np.linalg.norm(quad[0] - quad[1]) +
|
|
np.linalg.norm(quad[2] - quad[3]))
|
|
|
|
# average angle of left and right line.
|
|
angle = self.average_angle(quad)
|
|
|
|
xy_in_poly = np.argwhere(tcl_mask == 1)
|
|
for y, x in xy_in_poly:
|
|
point = (x, y)
|
|
line = self.theta_line_cross_point(angle, point)
|
|
cross_point_upper = self.line_cross_point(up_line, line)
|
|
cross_point_lower = self.line_cross_point(lower_line, line)
|
|
##FIX, offset reverse
|
|
upper_offset_x, upper_offset_y = cross_point_upper - point
|
|
lower_offset_x, lower_offset_y = cross_point_lower - point
|
|
tbo_map[y, x, 0] = upper_offset_y
|
|
tbo_map[y, x, 1] = upper_offset_x
|
|
tbo_map[y, x, 2] = lower_offset_y
|
|
tbo_map[y, x, 3] = lower_offset_x
|
|
tbo_map[y, x, 4] = 1.0 / max(min(quad_h, quad_w), 1.0) * 2
|
|
return tbo_map
|
|
|
|
def poly2quads(self, poly):
|
|
"""
|
|
Split poly into quads.
|
|
"""
|
|
quad_list = []
|
|
point_num = poly.shape[0]
|
|
|
|
# point pair
|
|
point_pair_list = []
|
|
for idx in range(point_num // 2):
|
|
point_pair = [poly[idx], poly[point_num - 1 - idx]]
|
|
point_pair_list.append(point_pair)
|
|
|
|
quad_num = point_num // 2 - 1
|
|
for idx in range(quad_num):
|
|
# reshape and adjust to clock-wise
|
|
quad_list.append((np.array(point_pair_list)[[idx, idx + 1]]
|
|
).reshape(4, 2)[[0, 2, 3, 1]])
|
|
|
|
return np.array(quad_list)
|
|
|
|
def rotate_im_poly(self, im, text_polys):
|
|
"""
|
|
rotate image with 90 / 180 / 270 degre
|
|
"""
|
|
im_w, im_h = im.shape[1], im.shape[0]
|
|
dst_im = im.copy()
|
|
dst_polys = []
|
|
rand_degree_ratio = np.random.rand()
|
|
rand_degree_cnt = 1
|
|
if rand_degree_ratio > 0.5:
|
|
rand_degree_cnt = 3
|
|
for i in range(rand_degree_cnt):
|
|
dst_im = np.rot90(dst_im)
|
|
rot_degree = -90 * rand_degree_cnt
|
|
rot_angle = rot_degree * math.pi / 180.0
|
|
n_poly = text_polys.shape[0]
|
|
cx, cy = 0.5 * im_w, 0.5 * im_h
|
|
ncx, ncy = 0.5 * dst_im.shape[1], 0.5 * dst_im.shape[0]
|
|
for i in range(n_poly):
|
|
wordBB = text_polys[i]
|
|
poly = []
|
|
for j in range(4): # 16->4
|
|
sx, sy = wordBB[j][0], wordBB[j][1]
|
|
dx = math.cos(rot_angle) * (sx - cx) - math.sin(rot_angle) * (
|
|
sy - cy) + ncx
|
|
dy = math.sin(rot_angle) * (sx - cx) + math.cos(rot_angle) * (
|
|
sy - cy) + ncy
|
|
poly.append([dx, dy])
|
|
dst_polys.append(poly)
|
|
return dst_im, np.array(dst_polys, dtype=np.float32)
|
|
|
|
def __call__(self, data):
|
|
input_size = 512
|
|
im = data['image']
|
|
text_polys = data['polys']
|
|
text_tags = data['ignore_tags']
|
|
text_strs = data['texts']
|
|
h, w, _ = im.shape
|
|
text_polys, text_tags, hv_tags = self.check_and_validate_polys(
|
|
text_polys, text_tags, (h, w))
|
|
if text_polys.shape[0] <= 0:
|
|
return None
|
|
# set aspect ratio and keep area fix
|
|
asp_scales = np.arange(1.0, 1.55, 0.1)
|
|
asp_scale = np.random.choice(asp_scales)
|
|
if np.random.rand() < 0.5:
|
|
asp_scale = 1.0 / asp_scale
|
|
asp_scale = math.sqrt(asp_scale)
|
|
|
|
asp_wx = asp_scale
|
|
asp_hy = 1.0 / asp_scale
|
|
im = cv2.resize(im, dsize=None, fx=asp_wx, fy=asp_hy)
|
|
text_polys[:, :, 0] *= asp_wx
|
|
text_polys[:, :, 1] *= asp_hy
|
|
|
|
h, w, _ = im.shape
|
|
if max(h, w) > 2048:
|
|
rd_scale = 2048.0 / max(h, w)
|
|
im = cv2.resize(im, dsize=None, fx=rd_scale, fy=rd_scale)
|
|
text_polys *= rd_scale
|
|
h, w, _ = im.shape
|
|
if min(h, w) < 16:
|
|
return None
|
|
|
|
# no background
|
|
im, text_polys, text_tags, hv_tags, text_strs = self.crop_area(
|
|
im,
|
|
text_polys,
|
|
text_tags,
|
|
hv_tags,
|
|
text_strs,
|
|
crop_background=False)
|
|
|
|
if text_polys.shape[0] == 0:
|
|
return None
|
|
# # continue for all ignore case
|
|
if np.sum((text_tags * 1.0)) >= text_tags.size:
|
|
return None
|
|
new_h, new_w, _ = im.shape
|
|
if (new_h is None) or (new_w is None):
|
|
return None
|
|
# resize image
|
|
std_ratio = float(input_size) / max(new_w, new_h)
|
|
rand_scales = np.array(
|
|
[0.25, 0.375, 0.5, 0.625, 0.75, 0.875, 1.0, 1.0, 1.0, 1.0, 1.0])
|
|
rz_scale = std_ratio * np.random.choice(rand_scales)
|
|
im = cv2.resize(im, dsize=None, fx=rz_scale, fy=rz_scale)
|
|
text_polys[:, :, 0] *= rz_scale
|
|
text_polys[:, :, 1] *= rz_scale
|
|
|
|
# add gaussian blur
|
|
if np.random.rand() < 0.1 * 0.5:
|
|
ks = np.random.permutation(5)[0] + 1
|
|
ks = int(ks / 2) * 2 + 1
|
|
im = cv2.GaussianBlur(im, ksize=(ks, ks), sigmaX=0, sigmaY=0)
|
|
# add brighter
|
|
if np.random.rand() < 0.1 * 0.5:
|
|
im = im * (1.0 + np.random.rand() * 0.5)
|
|
im = np.clip(im, 0.0, 255.0)
|
|
# add darker
|
|
if np.random.rand() < 0.1 * 0.5:
|
|
im = im * (1.0 - np.random.rand() * 0.5)
|
|
im = np.clip(im, 0.0, 255.0)
|
|
|
|
# Padding the im to [input_size, input_size]
|
|
new_h, new_w, _ = im.shape
|
|
if min(new_w, new_h) < input_size * 0.5:
|
|
return None
|
|
im_padded = np.ones((input_size, input_size, 3), dtype=np.float32)
|
|
im_padded[:, :, 2] = 0.485 * 255
|
|
im_padded[:, :, 1] = 0.456 * 255
|
|
im_padded[:, :, 0] = 0.406 * 255
|
|
|
|
# Random the start position
|
|
del_h = input_size - new_h
|
|
del_w = input_size - new_w
|
|
sh, sw = 0, 0
|
|
if del_h > 1:
|
|
sh = int(np.random.rand() * del_h)
|
|
if del_w > 1:
|
|
sw = int(np.random.rand() * del_w)
|
|
|
|
# Padding
|
|
im_padded[sh:sh + new_h, sw:sw + new_w, :] = im.copy()
|
|
text_polys[:, :, 0] += sw
|
|
text_polys[:, :, 1] += sh
|
|
|
|
score_map, score_label_map, border_map, direction_map, training_mask, \
|
|
pos_list, pos_mask, label_list, score_label_map_text_label = self.generate_tcl_ctc_label(input_size,
|
|
input_size,
|
|
text_polys,
|
|
text_tags,
|
|
text_strs, 0.25)
|
|
if len(label_list) <= 0: # eliminate negative samples
|
|
return None
|
|
pos_list_temp = np.zeros([64, 3])
|
|
pos_mask_temp = np.zeros([64, 1])
|
|
label_list_temp = np.zeros([self.max_text_length, 1]) + self.pad_num
|
|
|
|
for i, label in enumerate(label_list):
|
|
n = len(label)
|
|
if n > self.max_text_length:
|
|
label_list[i] = label[:self.max_text_length]
|
|
continue
|
|
while n < self.max_text_length:
|
|
label.append([self.pad_num])
|
|
n += 1
|
|
|
|
for i in range(len(label_list)):
|
|
label_list[i] = np.array(label_list[i])
|
|
|
|
if len(pos_list) <= 0 or len(pos_list) > self.max_text_nums:
|
|
return None
|
|
for __ in range(self.max_text_nums - len(pos_list), 0, -1):
|
|
pos_list.append(pos_list_temp)
|
|
pos_mask.append(pos_mask_temp)
|
|
label_list.append(label_list_temp)
|
|
|
|
if self.img_id == self.batch_size - 1:
|
|
self.img_id = 0
|
|
else:
|
|
self.img_id += 1
|
|
|
|
im_padded[:, :, 2] -= 0.485 * 255
|
|
im_padded[:, :, 1] -= 0.456 * 255
|
|
im_padded[:, :, 0] -= 0.406 * 255
|
|
im_padded[:, :, 2] /= (255.0 * 0.229)
|
|
im_padded[:, :, 1] /= (255.0 * 0.224)
|
|
im_padded[:, :, 0] /= (255.0 * 0.225)
|
|
im_padded = im_padded.transpose((2, 0, 1))
|
|
images = im_padded[::-1, :, :]
|
|
tcl_maps = score_map[np.newaxis, :, :]
|
|
tcl_label_maps = score_label_map[np.newaxis, :, :]
|
|
border_maps = border_map.transpose((2, 0, 1))
|
|
direction_maps = direction_map.transpose((2, 0, 1))
|
|
training_masks = training_mask[np.newaxis, :, :]
|
|
pos_list = np.array(pos_list)
|
|
pos_mask = np.array(pos_mask)
|
|
label_list = np.array(label_list)
|
|
data['images'] = images
|
|
data['tcl_maps'] = tcl_maps
|
|
data['tcl_label_maps'] = tcl_label_maps
|
|
data['border_maps'] = border_maps
|
|
data['direction_maps'] = direction_maps
|
|
data['training_masks'] = training_masks
|
|
data['label_list'] = label_list
|
|
data['pos_list'] = pos_list
|
|
data['pos_mask'] = pos_mask
|
|
return data
|