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data.py
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data.py
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# coding:utf-8
import glob
import csv
import cv2
import time
import os
import numpy as np
import scipy.optimize
import matplotlib.pyplot as plt
import matplotlib.patches as Patches
from shapely.geometry import Polygon
import tensorflow as tf
from data_util import GeneratorEnqueuer
tf.app.flags.DEFINE_string('training_data_path', '/home/huluwa/Etranform/ver_data/train/',
'training dataset to use')
tf.app.flags.DEFINE_integer('max_image_large_side', 1280,
'max image size of training')
tf.app.flags.DEFINE_integer('max_text_size', 800,
'if the text in the input image is bigger than this, then we resize'
'the image according to this')
tf.app.flags.DEFINE_integer('min_text_size', 0,
'if the text size is smaller than this, we ignore it during training')
tf.app.flags.DEFINE_float('min_crop_side_ratio', 0.1,
'when doing random crop from input image, the'
'min length of min(H, W')
tf.app.flags.DEFINE_string('geometry', 'RBOX',
'which geometry to generate, RBOX or QUAD')
FLAGS = tf.app.flags.FLAGS
def get_images():
files = []
for ext in ['jpg', 'png', 'jpeg', 'JPG']:
files.extend(glob.glob(
os.path.join(FLAGS.training_data_path, '*.{}'.format(ext))))
return files
def load_annoataion(p):
'''
load annotation from the text file
:param p:
:return:
'''
text_polys = []
vertex_text_polys = []
text_tags = []
vertex_text_tags = []
vertex_1_text_polys = []
vertex_1_text_tags = []
vertex_2_text_polys = []
vertex_2_text_tags = []
vertex_3_text_polys = []
vertex_3_text_tags = []
vertex_4_text_polys = []
vertex_4_text_tags = []
if not os.path.exists(p):
return np.array(text_polys, dtype=np.float32)
with open(p, 'r') as f:
reader = csv.reader(f)
for line in reader:
label = line[-1]
# strip BOM. \ufeff for python3, \xef\xbb\bf for python2
line = [i.strip('\ufeff').strip('\xef\xbb\xbf') for i in line]
if ',' in line:
line = [i.strip('\ufeff').strip('\xef\xbb\xbf') for i in line]
else:
line = [i.strip(' ').strip('\xef\xbb\xbf') for i in line]
x1, y1, x2, y2, x3, y3, x4, y4 = list(map(float, line[:8]))
text_polys.append([[x1, y1], [x2, y2], [x3, y3], [x4, y4]])
if label == '*' or label == '###':
text_tags.append(True)
else:
text_tags.append(False)
vertex_h = 100
#leftup
vertex_1_x1 = max(x1 - vertex_h/2,0)
vertex_1_y1 = max(y1 - vertex_h/2,0)
vertex_1_x2 = max(x1 + vertex_h/2,0)
vertex_1_y2 = max(y1 - vertex_h/2,0)
vertex_1_x3 = max(x1 + vertex_h/2,0)
vertex_1_y3 = max(y1 + vertex_h/2,0)
vertex_1_x4 = max(x1 - vertex_h/2,0)
vertex_1_y4 = max(y1 + vertex_h/2,0)
vertex_text_polys.append([[vertex_1_x1,vertex_1_y1], [vertex_1_x2,vertex_1_y2],[vertex_1_x3,vertex_1_y3],[vertex_1_x4,vertex_1_y4]])
vertex_1_text_polys.append([[vertex_1_x1,vertex_1_y1], [vertex_1_x2,vertex_1_y2],[vertex_1_x3,vertex_1_y3],[vertex_1_x4,vertex_1_y4]])
if label == '*' or label == '###':
vertex_text_tags.append(True)
vertex_1_text_tags.append(True)
else:
vertex_text_tags.append(False)
vertex_1_text_tags.append(False)
#rightup
vertex_2_x1 = max(x2 - vertex_h/2,0)
vertex_2_y1 = max(y2 - vertex_h/2,0)
vertex_2_x2 = x2 + vertex_h/2
vertex_2_y2 = max(y2 - vertex_h/2,0)
vertex_2_x3 = x2 + vertex_h/2
vertex_2_y3 = y2 + vertex_h/2
vertex_2_x4 = x2 - vertex_h/2
vertex_2_y4 = y2 + vertex_h/2
vertex_text_polys.append([[vertex_2_x1,vertex_2_y1], [vertex_2_x2,vertex_2_y2],[vertex_2_x3,vertex_2_y3],[vertex_2_x4,vertex_2_y4]])
vertex_2_text_polys.append([[vertex_2_x1,vertex_2_y1], [vertex_2_x2,vertex_2_y2],[vertex_2_x3,vertex_2_y3],[vertex_2_x4,vertex_2_y4]])
if label == '*' or label == '###':
vertex_text_tags.append(True)
vertex_2_text_tags.append(True)
else:
vertex_text_tags.append(False)
vertex_2_text_tags.append(False)
#rightdown
vertex_3_x1 = x3 - vertex_h/2
vertex_3_y1 = y3 - vertex_h/2
vertex_3_x2 = x3 + vertex_h/2
vertex_3_y2 = y3 - vertex_h/2
vertex_3_x3 = x3 + vertex_h/2
vertex_3_y3 = y3 + vertex_h/2
vertex_3_x4 = x3 - vertex_h/2
vertex_3_y4 = y3 + vertex_h/2
vertex_text_polys.append([[vertex_3_x1,vertex_3_y1], [vertex_3_x2,vertex_3_y2],[vertex_3_x3,vertex_3_y3],[vertex_3_x4,vertex_3_y4]])
vertex_3_text_polys.append([[vertex_3_x1,vertex_3_y1], [vertex_3_x2,vertex_3_y2],[vertex_3_x3,vertex_3_y3],[vertex_3_x4,vertex_3_y4]])
if label == '*' or label == '###':
vertex_text_tags.append(True)
vertex_3_text_tags.append(True)
else:
vertex_text_tags.append(False)
vertex_3_text_tags.append(False)
#leftdown
vertex_4_x1 = max(x4 - vertex_h/2,0)
vertex_4_y1 = y4 - vertex_h/2
vertex_4_x2 = x4 + vertex_h/2
vertex_4_y2 = y4 - vertex_h/2
vertex_4_x3 = x4 + vertex_h/2
vertex_4_y3 = y4 + vertex_h/2
vertex_4_x4 = max(x4 - vertex_h/2,0)
vertex_4_y4 = y4 + vertex_h/2
vertex_text_polys.append([[vertex_4_x1,vertex_4_y1], [vertex_4_x2,vertex_4_y2],[vertex_4_x3,vertex_4_y3],[vertex_4_x4,vertex_4_y4]])
vertex_4_text_polys.append([[vertex_4_x1,vertex_4_y1], [vertex_4_x2,vertex_4_y2],[vertex_4_x3,vertex_4_y3],[vertex_4_x4,vertex_4_y4]])
if label == '*' or label == '###':
vertex_text_tags.append(True)
vertex_4_text_tags.append(True)
else:
vertex_text_tags.append(False)
vertex_4_text_tags.append(False)
return np.array(text_polys, dtype=np.float32), np.array(text_tags, dtype=np.bool), np.array(vertex_text_polys, dtype=np.float32), np.array(vertex_text_tags, dtype=np.bool),np.array(vertex_1_text_polys, dtype=np.float32), np.array(vertex_1_text_tags, dtype=np.bool), np.array(vertex_2_text_polys, dtype=np.float32), np.array(vertex_2_text_tags, dtype=np.bool), np.array(vertex_3_text_polys, dtype=np.float32), np.array(vertex_3_text_tags, dtype=np.bool), np.array(vertex_4_text_polys, dtype=np.float32), np.array(vertex_4_text_tags, dtype=np.bool)
def polygon_area(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 check_and_validate_polys(polys, tags, xxx_todo_changeme):
'''
check so that the text poly is in the same direction,
and also filter some invalid polygons
:param polys:
:param tags:
:return:
'''
(h, w) = xxx_todo_changeme
if polys.shape[0] == 0:
return polys
polys[:, :, 0] = np.clip(polys[:, :, 0], 0, w-1)
polys[:, :, 1] = np.clip(polys[:, :, 1], 0, h-1)
validated_polys = []
validated_tags = []
for poly, tag in zip(polys, tags):
p_area = polygon_area(poly)
if abs(p_area) < 1:
# print poly
print('invalid poly')
continue
if p_area > 0:
print('poly in wrong direction')
poly = poly[(0, 3, 2, 1), :]
validated_polys.append(poly)
validated_tags.append(tag)
return np.array(validated_polys), np.array(validated_tags)
def crop_area(im, polys, tags, vertex_polys, vertex_tags, vertex_1_polys, vertex_1_tags, vertex_2_polys, vertex_2_tags, vertex_3_polys, vertex_3_tags, vertex_4_polys, vertex_4_tags, crop_background=False, max_tries=50):
'''
make random crop from the input image
:param im:
:param polys:
:param tags:
:param crop_background:
:param max_tries:
: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)
vertex_1_h_array = np.zeros((h + pad_h*2), dtype=np.int32)
vertex_1_w_array = np.zeros((w + pad_w*2), dtype=np.int32)
vertex_2_h_array = np.zeros((h + pad_h*2), dtype=np.int32)
vertex_2_w_array = np.zeros((w + pad_w*2), dtype=np.int32)
vertex_3_h_array = np.zeros((h + pad_h*2), dtype=np.int32)
vertex_3_w_array = np.zeros((w + pad_w*2), dtype=np.int32)
vertex_4_h_array = np.zeros((h + pad_h*2), dtype=np.int32)
vertex_4_w_array = np.zeros((w + pad_w*2), dtype=np.int32)
vertex_h_array = np.zeros((h + pad_h*2), dtype=np.int32)
vertex_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
for vertex_poly in vertex_polys:
vertex_poly = np.round(vertex_poly, decimals=0).astype(np.int32)
minx = np.min(vertex_poly[:, 0])
maxx = np.max(vertex_poly[:, 0])
vertex_w_array[minx+pad_w:maxx+pad_w] = 1
miny = np.min(vertex_poly[:, 1])
maxy = np.max(vertex_poly[:, 1])
vertex_h_array[miny+pad_h:maxy+pad_h] = 1
for vertex_1_poly in vertex_1_polys:
vertex_1_poly = np.round(vertex_1_poly, decimals=0).astype(np.int32)
minx = np.min(vertex_1_poly[:, 0])
maxx = np.max(vertex_1_poly[:, 0])
vertex_1_w_array[minx+pad_w:maxx+pad_w] = 1
miny = np.min(vertex_1_poly[:, 1])
maxy = np.max(vertex_1_poly[:, 1])
vertex_1_h_array[miny+pad_h:maxy+pad_h] = 1
for vertex_2_poly in vertex_2_polys:
vertex_2_poly = np.round(vertex_2_poly, decimals=0).astype(np.int32)
minx = np.min(vertex_2_poly[:, 0])
maxx = np.max(vertex_2_poly[:, 0])
vertex_2_w_array[minx+pad_w:maxx+pad_w] = 1
miny = np.min(vertex_2_poly[:, 1])
maxy = np.max(vertex_poly[:, 1])
vertex_2_h_array[miny+pad_h:maxy+pad_h] = 1
for vertex_3_poly in vertex_3_polys:
vertex_3_poly = np.round(vertex_3_poly, decimals=0).astype(np.int32)
minx = np.min(vertex_3_poly[:, 0])
maxx = np.max(vertex_3_poly[:, 0])
vertex_3_w_array[minx+pad_w:maxx+pad_w] = 1
miny = np.min(vertex_3_poly[:, 1])
maxy = np.max(vertex_3_poly[:, 1])
vertex_3_h_array[miny+pad_h:maxy+pad_h] = 1
for vertex_4_poly in vertex_4_polys:
vertex_4_poly = np.round(vertex_4_poly, decimals=0).astype(np.int32)
minx = np.min(vertex_4_poly[:, 0])
maxx = np.max(vertex_4_poly[:, 0])
vertex_4_w_array[minx+pad_w:maxx+pad_w] = 1
miny = np.min(vertex_4_poly[:, 1])
maxy = np.max(vertex_4_poly[:, 1])
vertex_4_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]
vertex_h_axis = np.where(vertex_h_array == 0)[0]
vertex_w_axis = np.where(vertex_w_array == 0)[0]
if len(h_axis) == 0 or len(w_axis) == 0 or len(vertex_h_axis) == 0 or len(vertex_w_axis) == 0:
return im, polys, tags, vertex_polys, vertex_tags, vertex_1_polys, vertex_1_tags, vertex_2_polys, vertex_2_tags, vertex_3_polys, vertex_3_tags, vertex_4_polys, vertex_4_tags
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 < FLAGS.min_crop_side_ratio*w or ymax - ymin < FLAGS.min_crop_side_ratio*h:
# area too small
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 vertex_polys.shape[0] != 0:
vertex_poly_axis_in_area = (vertex_polys[:, :, 0] >= xmin) & (vertex_polys[:, :, 0] <= xmax) \
& (vertex_polys[:, :, 1] >= ymin) & (vertex_polys[:, :, 1] <= ymax)
vertex_selected_polys = np.where(np.sum(vertex_poly_axis_in_area, axis=1) == 4)[0]
else:
vertex_selected_polys = []
if vertex_1_polys.shape[0] != 0:
vertex_1_poly_axis_in_area = (vertex_1_polys[:, :, 0] >= xmin) & (vertex_1_polys[:, :, 0] <= xmax) \
& (vertex_1_polys[:, :, 1] >= ymin) & (vertex_1_polys[:, :, 1] <= ymax)
vertex_1_selected_polys = np.where(np.sum(vertex_1_poly_axis_in_area, axis=1) == 4)[0]
else:
vertex_1_selected_polys = []
if vertex_2_polys.shape[0] != 0:
vertex_2_poly_axis_in_area = (vertex_2_polys[:, :, 0] >= xmin) & (vertex_2_polys[:, :, 0] <= xmax) \
& (vertex_2_polys[:, :, 1] >= ymin) & (vertex_2_polys[:, :, 1] <= ymax)
vertex_2_selected_polys = np.where(np.sum(vertex_2_poly_axis_in_area, axis=1) == 4)[0]
else:
vertex_2_selected_polys = []
if vertex_3_polys.shape[0] != 0:
vertex_3_poly_axis_in_area = (vertex_3_polys[:, :, 0] >= xmin) & (vertex_3_polys[:, :, 0] <= xmax) \
& (vertex_3_polys[:, :, 1] >= ymin) & (vertex_3_polys[:, :, 1] <= ymax)
vertex_3_selected_polys = np.where(np.sum(vertex_3_poly_axis_in_area, axis=1) == 4)[0]
else:
vertex_3_selected_polys = []
if vertex_4_polys.shape[0] != 0:
vertex_4_poly_axis_in_area = (vertex_4_polys[:, :, 0] >= xmin) & (vertex_4_polys[:, :, 0] <= xmax) \
& (vertex_4_polys[:, :, 1] >= ymin) & (vertex_4_polys[:, :, 1] <= ymax)
vertex_4_selected_polys = np.where(np.sum(vertex_4_poly_axis_in_area, axis=1) == 4)[0]
else:
vertex_4_selected_polys = []
if len(selected_polys) == 0 or len(vertex_selected_polys) == 0 or len(vertex_1_selected_polys) == 0 or len(vertex_2_selected_polys) == 0 or len(vertex_3_selected_polys) == 0 or len(vertex_4_selected_polys) == 0:
# no text in this area
if crop_background:
return im[ymin:ymax+1, xmin:xmax+1, :], polys[selected_polys], tags[selected_polys], vertex_polys[vertex_selected_polys], vertex_tags[vertex_selected_polys], vertex_1_polys[vertex_1_selected_polys], vertex_1_tags[vertex_1_selected_polys], vertex_2_polys[vertex_2_selected_polys], vertex_2_tags[vertex_2_selected_polys], vertex_3_polys[vertex_3_selected_polys], vertex_3_tags[vertex_3_selected_polys], vertex_4_polys[vertex_4_selected_polys], vertex_4_tags[vertex_4_selected_polys]
else:
continue
im = im[ymin:ymax+1, xmin:xmax+1, :]
polys = polys[selected_polys]
vertex_polys = vertex_polys[vertex_selected_polys]
tags = tags[selected_polys]
vertex_tags = vertex_tags[vertex_selected_polys]
vertex_1_polys = vertex_1_polys[vertex_1_selected_polys]
vertex_1_tags = vertex_1_tags[vertex_1_selected_polys]
vertex_2_polys = vertex_2_polys[vertex_2_selected_polys]
vertex_2_tags = vertex_2_tags[vertex_2_selected_polys]
vertex_3_polys = vertex_3_polys[vertex_3_selected_polys]
vertex_3_tags = vertex_3_tags[vertex_3_selected_polys]
vertex_4_polys = vertex_4_polys[vertex_4_selected_polys]
vertex_4_tags = vertex_4_tags[vertex_4_selected_polys]
polys[:, :, 0] -= xmin
polys[:, :, 1] -= ymin
vertex_polys[:, :, 0] -= xmin
vertex_polys[:, :, 1] -= ymin
vertex_1_polys[:, :, 0] -= xmin
vertex_1_polys[:, :, 1] -= ymin
vertex_2_polys[:, :, 0] -= xmin
vertex_2_polys[:, :, 1] -= ymin
vertex_3_polys[:, :, 0] -= xmin
vertex_3_polys[:, :, 1] -= ymin
vertex_4_polys[:, :, 0] -= xmin
vertex_4_polys[:, :, 1] -= ymin
return im, polys, tags, vertex_polys, vertex_tags, vertex_1_polys, vertex_1_tags, vertex_2_polys, vertex_2_tags, vertex_3_polys, vertex_3_tags, vertex_4_polys, vertex_4_tags
return im, polys, tags, vertex_polys, vertex_tags, vertex_1_polys, vertex_1_tags, vertex_2_polys, vertex_2_tags, vertex_3_polys, vertex_3_tags, vertex_4_polys, vertex_4_tags
def shrink_poly(poly, r):
'''
fit a poly inside the origin poly, maybe bugs here...
used for generate the score map
:param poly: the text poly
:param r: r in the paper
:return: the shrinked poly
'''
# shrink ratio
R = 0.3
# find the longer pair
if np.linalg.norm(poly[0] - poly[1]) + np.linalg.norm(poly[2] - poly[3]) > \
np.linalg.norm(poly[0] - poly[3]) + np.linalg.norm(poly[1] - poly[2]):
# first move (p0, p1), (p2, p3), then (p0, p3), (p1, p2)
## p0, p1
theta = np.arctan2((poly[1][1] - poly[0][1]), (poly[1][0] - poly[0][0]))
poly[0][0] += R * r[0] * np.cos(theta)
poly[0][1] += R * r[0] * np.sin(theta)
poly[1][0] -= R * r[1] * np.cos(theta)
poly[1][1] -= R * r[1] * np.sin(theta)
## p2, p3
theta = np.arctan2((poly[2][1] - poly[3][1]), (poly[2][0] - poly[3][0]))
poly[3][0] += R * r[3] * np.cos(theta)
poly[3][1] += R * r[3] * np.sin(theta)
poly[2][0] -= R * r[2] * np.cos(theta)
poly[2][1] -= R * r[2] * np.sin(theta)
## p0, p3
theta = np.arctan2((poly[3][0] - poly[0][0]), (poly[3][1] - poly[0][1]))
poly[0][0] += R * r[0] * np.sin(theta)
poly[0][1] += R * r[0] * np.cos(theta)
poly[3][0] -= R * r[3] * np.sin(theta)
poly[3][1] -= R * r[3] * np.cos(theta)
## p1, p2
theta = np.arctan2((poly[2][0] - poly[1][0]), (poly[2][1] - poly[1][1]))
poly[1][0] += R * r[1] * np.sin(theta)
poly[1][1] += R * r[1] * np.cos(theta)
poly[2][0] -= R * r[2] * np.sin(theta)
poly[2][1] -= R * r[2] * np.cos(theta)
else:
## p0, p3
# print poly
theta = np.arctan2((poly[3][0] - poly[0][0]), (poly[3][1] - poly[0][1]))
poly[0][0] += R * r[0] * np.sin(theta)
poly[0][1] += R * r[0] * np.cos(theta)
poly[3][0] -= R * r[3] * np.sin(theta)
poly[3][1] -= R * r[3] * np.cos(theta)
## p1, p2
theta = np.arctan2((poly[2][0] - poly[1][0]), (poly[2][1] - poly[1][1]))
poly[1][0] += R * r[1] * np.sin(theta)
poly[1][1] += R * r[1] * np.cos(theta)
poly[2][0] -= R * r[2] * np.sin(theta)
poly[2][1] -= R * r[2] * np.cos(theta)
## p0, p1
theta = np.arctan2((poly[1][1] - poly[0][1]), (poly[1][0] - poly[0][0]))
poly[0][0] += R * r[0] * np.cos(theta)
poly[0][1] += R * r[0] * np.sin(theta)
poly[1][0] -= R * r[1] * np.cos(theta)
poly[1][1] -= R * r[1] * np.sin(theta)
## p2, p3
theta = np.arctan2((poly[2][1] - poly[3][1]), (poly[2][0] - poly[3][0]))
poly[3][0] += R * r[3] * np.cos(theta)
poly[3][1] += R * r[3] * np.sin(theta)
poly[2][0] -= R * r[2] * np.cos(theta)
poly[2][1] -= R * r[2] * np.sin(theta)
return poly
def point_dist_to_line(p1, p2, p3):
# compute the distance from p3 to p1-p2
return np.linalg.norm(np.cross(p2 - p1, p1 - p3)) / np.linalg.norm(p2 - p1)
def fit_line(p1, p2):
# fit a line ax+by+c = 0
if p1[0] == p1[1]:
return [1., 0., -p1[0]]
else:
[k, b] = np.polyfit(p1, p2, deg=1)
return [k, -1., b]
def line_cross_point(line1, line2):
# line1 0= ax+by+c, compute the cross point of line1 and line2
if line1[0] != 0 and line1[0] == line2[0]:
print('Cross point does not exist')
return None
if line1[0] == 0 and line2[0] == 0:
print('Cross point does not exist')
return None
if line1[1] == 0:
x = -line1[2]
y = line2[0] * x + line2[2]
elif line2[1] == 0:
x = -line2[2]
y = line1[0] * x + line1[2]
else:
k1, _, b1 = line1
k2, _, b2 = line2
x = -(b1-b2)/(k1-k2)
y = k1*x + b1
return np.array([x, y], dtype=np.float32)
def line_verticle(line, point):
# get the verticle line from line across point
if line[1] == 0:
verticle = [0, -1, point[1]]
else:
if line[0] == 0:
verticle = [1, 0, -point[0]]
else:
verticle = [-1./line[0], -1, point[1] - (-1/line[0] * point[0])]
return verticle
def rectangle_from_parallelogram(poly):
'''
fit a rectangle from a parallelogram
:param poly:
:return:
'''
p0, p1, p2, p3 = poly
angle_p0 = np.arccos(np.dot(p1-p0, p3-p0)/(np.linalg.norm(p0-p1) * np.linalg.norm(p3-p0)))
if angle_p0 < 0.5 * np.pi:
if np.linalg.norm(p0 - p1) > np.linalg.norm(p0-p3):
# p0 and p2
## p0
p2p3 = fit_line([p2[0], p3[0]], [p2[1], p3[1]])
p2p3_verticle = line_verticle(p2p3, p0)
new_p3 = line_cross_point(p2p3, p2p3_verticle)
## p2
p0p1 = fit_line([p0[0], p1[0]], [p0[1], p1[1]])
p0p1_verticle = line_verticle(p0p1, p2)
new_p1 = line_cross_point(p0p1, p0p1_verticle)
return np.array([p0, new_p1, p2, new_p3], dtype=np.float32)
else:
p1p2 = fit_line([p1[0], p2[0]], [p1[1], p2[1]])
p1p2_verticle = line_verticle(p1p2, p0)
new_p1 = line_cross_point(p1p2, p1p2_verticle)
p0p3 = fit_line([p0[0], p3[0]], [p0[1], p3[1]])
p0p3_verticle = line_verticle(p0p3, p2)
new_p3 = line_cross_point(p0p3, p0p3_verticle)
return np.array([p0, new_p1, p2, new_p3], dtype=np.float32)
else:
if np.linalg.norm(p0-p1) > np.linalg.norm(p0-p3):
# p1 and p3
## p1
p2p3 = fit_line([p2[0], p3[0]], [p2[1], p3[1]])
p2p3_verticle = line_verticle(p2p3, p1)
new_p2 = line_cross_point(p2p3, p2p3_verticle)
## p3
p0p1 = fit_line([p0[0], p1[0]], [p0[1], p1[1]])
p0p1_verticle = line_verticle(p0p1, p3)
new_p0 = line_cross_point(p0p1, p0p1_verticle)
return np.array([new_p0, p1, new_p2, p3], dtype=np.float32)
else:
p0p3 = fit_line([p0[0], p3[0]], [p0[1], p3[1]])
p0p3_verticle = line_verticle(p0p3, p1)
new_p0 = line_cross_point(p0p3, p0p3_verticle)
p1p2 = fit_line([p1[0], p2[0]], [p1[1], p2[1]])
p1p2_verticle = line_verticle(p1p2, p3)
new_p2 = line_cross_point(p1p2, p1p2_verticle)
return np.array([new_p0, p1, new_p2, p3], dtype=np.float32)
def sort_rectangle(poly):
# sort the four coordinates of the polygon, points in poly should be sorted clockwise
# First find the lowest point
p_lowest = np.argmax(poly[:, 1])
if np.count_nonzero(poly[:, 1] == poly[p_lowest, 1]) == 2:
# 底边平行于X轴, 那么p0为左上角 - if the bottom line is parallel to x-axis, then p0 must be the upper-left corner
p0_index = np.argmin(np.sum(poly, axis=1))
p1_index = (p0_index + 1) % 4
p2_index = (p0_index + 2) % 4
p3_index = (p0_index + 3) % 4
return poly[[p0_index, p1_index, p2_index, p3_index]], 0.
else:
# 找到最低点右边的点 - find the point that sits right to the lowest point
p_lowest_right = (p_lowest - 1) % 4
p_lowest_left = (p_lowest + 1) % 4
angle = np.arctan(-(poly[p_lowest][1] - poly[p_lowest_right][1])/(poly[p_lowest][0] - poly[p_lowest_right][0]))
# assert angle > 0
if angle <= 0:
print(angle, poly[p_lowest], poly[p_lowest_right])
if angle/np.pi * 180 > 45:
# 这个点为p2 - this point is p2
p2_index = p_lowest
p1_index = (p2_index - 1) % 4
p0_index = (p2_index - 2) % 4
p3_index = (p2_index + 1) % 4
return poly[[p0_index, p1_index, p2_index, p3_index]], -(np.pi/2 - angle)
else:
# 这个点为p3 - this point is p3
p3_index = p_lowest
p0_index = (p3_index + 1) % 4
p1_index = (p3_index + 2) % 4
p2_index = (p3_index + 3) % 4
return poly[[p0_index, p1_index, p2_index, p3_index]], angle
def restore_rectangle_rbox(origin, geometry):
d = geometry[:, :4]
angle = geometry[:, 4]
# for angle > 0
true_origin = []
origin_0 = origin[angle >= 0]
d_0 = d[angle >= 0]
angle_0 = angle[angle >= 0]
true_origin.extend(origin_0)
if origin_0.shape[0] > 0:
p = np.array([np.zeros(d_0.shape[0]), -d_0[:, 0] - d_0[:, 2],
d_0[:, 1] + d_0[:, 3], -d_0[:, 0] - d_0[:, 2],
d_0[:, 1] + d_0[:, 3], np.zeros(d_0.shape[0]),
np.zeros(d_0.shape[0]), np.zeros(d_0.shape[0]),
d_0[:, 3], -d_0[:, 2]])
p = p.transpose((1, 0)).reshape((-1, 5, 2)) # N*5*2
rotate_matrix_x = np.array([np.cos(angle_0), np.sin(angle_0)]).transpose((1, 0))
rotate_matrix_x = np.repeat(rotate_matrix_x, 5, axis=1).reshape(-1, 2, 5).transpose((0, 2, 1)) # N*5*2
rotate_matrix_y = np.array([-np.sin(angle_0), np.cos(angle_0)]).transpose((1, 0))
rotate_matrix_y = np.repeat(rotate_matrix_y, 5, axis=1).reshape(-1, 2, 5).transpose((0, 2, 1))
p_rotate_x = np.sum(rotate_matrix_x * p, axis=2)[:, :, np.newaxis] # N*5*1
p_rotate_y = np.sum(rotate_matrix_y * p, axis=2)[:, :, np.newaxis] # N*5*1
p_rotate = np.concatenate([p_rotate_x, p_rotate_y], axis=2) # N*5*2
p3_in_origin = origin_0 - p_rotate[:, 4, :]
new_p0 = p_rotate[:, 0, :] + p3_in_origin # N*2
new_p1 = p_rotate[:, 1, :] + p3_in_origin
new_p2 = p_rotate[:, 2, :] + p3_in_origin
new_p3 = p_rotate[:, 3, :] + p3_in_origin
new_p_0 = np.concatenate([new_p0[:, np.newaxis, :], new_p1[:, np.newaxis, :],
new_p2[:, np.newaxis, :], new_p3[:, np.newaxis, :]], axis=1)
# new_p_0 = np.concatenate([new_p0[:, np.newaxis, :], new_p1[:, np.newaxis, :],
# new_p2[:, np.newaxis, :], new_p3[:, np.newaxis, :], origin_0[:,np.newaxis,:]], axis=1) # N*4*2
else:
new_p_0 = np.zeros((0, 5, 2))
# for angle < 0
origin_1 = origin[angle < 0]
true_origin.extend(origin_1)
d_1 = d[angle < 0]
angle_1 = angle[angle < 0]
if origin_1.shape[0] > 0:
p = np.array([-d_1[:, 1] - d_1[:, 3], -d_1[:, 0] - d_1[:, 2],
np.zeros(d_1.shape[0]), -d_1[:, 0] - d_1[:, 2],
np.zeros(d_1.shape[0]), np.zeros(d_1.shape[0]),
-d_1[:, 1] - d_1[:, 3], np.zeros(d_1.shape[0]),
-d_1[:, 1], -d_1[:, 2]])
p = p.transpose((1, 0)).reshape((-1, 5, 2)) # N*5*2
rotate_matrix_x = np.array([np.cos(-angle_1), -np.sin(-angle_1)]).transpose((1, 0))
rotate_matrix_x = np.repeat(rotate_matrix_x, 5, axis=1).reshape(-1, 2, 5).transpose((0, 2, 1)) # N*5*2
rotate_matrix_y = np.array([np.sin(-angle_1), np.cos(-angle_1)]).transpose((1, 0))
rotate_matrix_y = np.repeat(rotate_matrix_y, 5, axis=1).reshape(-1, 2, 5).transpose((0, 2, 1))
p_rotate_x = np.sum(rotate_matrix_x * p, axis=2)[:, :, np.newaxis] # N*5*1
p_rotate_y = np.sum(rotate_matrix_y * p, axis=2)[:, :, np.newaxis] # N*5*1
p_rotate = np.concatenate([p_rotate_x, p_rotate_y], axis=2) # N*5*2
p3_in_origin = origin_1 - p_rotate[:, 4, :]
new_p0 = p_rotate[:, 0, :] + p3_in_origin # N*2
new_p1 = p_rotate[:, 1, :] + p3_in_origin
new_p2 = p_rotate[:, 2, :] + p3_in_origin
new_p3 = p_rotate[:, 3, :] + p3_in_origin
new_p_1 = np.concatenate([new_p0[:, np.newaxis, :], new_p1[:, np.newaxis, :],
new_p2[:, np.newaxis, :], new_p3[:, np.newaxis, :]], axis=1) # N*4*2
# new_p_1 = np.concatenate([new_p0[:, np.newaxis, :], new_p1[:, np.newaxis, :],
# new_p2[:, np.newaxis, :], new_p3[:, np.newaxis, :], origin_1[:,np.newaxis,:]], axis=1) # N*4*2
else:
new_p_1 = np.zeros((0, 5, 2))
return np.concatenate([new_p_0, new_p_1])
def restore_rectangle(origin, geometry):
return restore_rectangle_rbox(origin, geometry)
def generate_rbox(im_size, polys, tags):
h, w = im_size
poly_mask = np.zeros((h, w), dtype=np.uint8)
score_map = np.zeros((h, w), dtype=np.uint8)
geo_map = np.zeros((h, w, 5), dtype=np.float32)
# mask used during traning, to ignore some hard areas
training_mask = np.ones((h, w), dtype=np.uint8)
for poly_idx, poly_tag in enumerate(zip(polys, tags)):
poly = poly_tag[0]
tag = poly_tag[1]
r = [None, None, None, None]
for i in range(4):
r[i] = min(np.linalg.norm(poly[i] - poly[(i + 1) % 4]),
np.linalg.norm(poly[i] - poly[(i - 1) % 4]))
# score map
shrinked_poly = shrink_poly(poly.copy(), r).astype(np.int32)[np.newaxis, :, :]
cv2.fillPoly(score_map, shrinked_poly, 1)
cv2.fillPoly(poly_mask, shrinked_poly, poly_idx + 1)
# if the poly is too small, then ignore it during training
poly_h = min(np.linalg.norm(poly[0] - poly[3]), np.linalg.norm(poly[1] - poly[2]))
poly_w = min(np.linalg.norm(poly[0] - poly[1]), np.linalg.norm(poly[2] - poly[3]))
if min(poly_h, poly_w) < FLAGS.min_text_size:
cv2.fillPoly(training_mask, poly.astype(np.int32)[np.newaxis, :, :], 0)
if tag:
cv2.fillPoly(training_mask, poly.astype(np.int32)[np.newaxis, :, :], 0)
xy_in_poly = np.argwhere(poly_mask == (poly_idx + 1))
# if geometry == 'RBOX':
# 对任意两个顶点的组合生成一个平行四边形 - generate a parallelogram for any combination of two vertices
fitted_parallelograms = []
for i in range(4):
p0 = poly[i]
p1 = poly[(i + 1) % 4]
p2 = poly[(i + 2) % 4]
p3 = poly[(i + 3) % 4]
edge = fit_line([p0[0], p1[0]], [p0[1], p1[1]])
backward_edge = fit_line([p0[0], p3[0]], [p0[1], p3[1]])
forward_edge = fit_line([p1[0], p2[0]], [p1[1], p2[1]])
if point_dist_to_line(p0, p1, p2) > point_dist_to_line(p0, p1, p3):
# 平行线经过p2 - parallel lines through p2
if edge[1] == 0:
edge_opposite = [1, 0, -p2[0]]
else:
edge_opposite = [edge[0], -1, p2[1] - edge[0] * p2[0]]
else:
# 经过p3 - after p3
if edge[1] == 0:
edge_opposite = [1, 0, -p3[0]]
else:
edge_opposite = [edge[0], -1, p3[1] - edge[0] * p3[0]]
# move forward edge
new_p0 = p0
new_p1 = p1
new_p2 = p2
new_p3 = p3
new_p2 = line_cross_point(forward_edge, edge_opposite)
if point_dist_to_line(p1, new_p2, p0) > point_dist_to_line(p1, new_p2, p3):
# across p0
if forward_edge[1] == 0:
forward_opposite = [1, 0, -p0[0]]
else:
forward_opposite = [forward_edge[0], -1, p0[1] - forward_edge[0] * p0[0]]
else:
# across p3
if forward_edge[1] == 0:
forward_opposite = [1, 0, -p3[0]]
else:
forward_opposite = [forward_edge[0], -1, p3[1] - forward_edge[0] * p3[0]]
new_p0 = line_cross_point(forward_opposite, edge)
new_p3 = line_cross_point(forward_opposite, edge_opposite)
fitted_parallelograms.append([new_p0, new_p1, new_p2, new_p3, new_p0])
# or move backward edge
new_p0 = p0
new_p1 = p1
new_p2 = p2
new_p3 = p3
new_p3 = line_cross_point(backward_edge, edge_opposite)
if point_dist_to_line(p0, p3, p1) > point_dist_to_line(p0, p3, p2):
# across p1
if backward_edge[1] == 0:
backward_opposite = [1, 0, -p1[0]]
else:
backward_opposite = [backward_edge[0], -1, p1[1] - backward_edge[0] * p1[0]]
else:
# across p2
if backward_edge[1] == 0:
backward_opposite = [1, 0, -p2[0]]
else:
backward_opposite = [backward_edge[0], -1, p2[1] - backward_edge[0] * p2[0]]
new_p1 = line_cross_point(backward_opposite, edge)
new_p2 = line_cross_point(backward_opposite, edge_opposite)
fitted_parallelograms.append([new_p0, new_p1, new_p2, new_p3, new_p0])
areas = [Polygon(t).area for t in fitted_parallelograms]
parallelogram = np.array(fitted_parallelograms[np.argmin(areas)][:-1], dtype=np.float32)
# sort thie polygon
parallelogram_coord_sum = np.sum(parallelogram, axis=1)
min_coord_idx = np.argmin(parallelogram_coord_sum)
parallelogram = parallelogram[
[min_coord_idx, (min_coord_idx + 1) % 4, (min_coord_idx + 2) % 4, (min_coord_idx + 3) % 4]]
rectange = rectangle_from_parallelogram(parallelogram)
rectange, rotate_angle = sort_rectangle(rectange)
p0_rect, p1_rect, p2_rect, p3_rect = rectange
for y, x in xy_in_poly:
point = np.array([x, y], dtype=np.float32)
# top
geo_map[y, x, 0] = point_dist_to_line(p0_rect, p1_rect, point)
# right
geo_map[y, x, 1] = point_dist_to_line(p1_rect, p2_rect, point)
# down
geo_map[y, x, 2] = point_dist_to_line(p2_rect, p3_rect, point)
# left
geo_map[y, x, 3] = point_dist_to_line(p3_rect, p0_rect, point)
# angle
geo_map[y, x, 4] = rotate_angle
return score_map, geo_map, training_mask
def generator(input_size=512, batch_size=32,
background_ratio=3./8,
random_scale=np.array([0.5, 1, 2.0, 3.0]),
vis=False):
image_list = np.array(get_images())
print('{} training images in {}'.format(
image_list.shape[0], FLAGS.training_data_path))
index = np.arange(0, image_list.shape[0])
while True:
np.random.shuffle(index)
images = []
image_fns = []
score_maps = []
geo_maps = []
training_masks = []
vertex_score_maps = []
vertex_geo_maps = []
vertex_training_masks = []
vertex_1_score_maps = []
vertex_1_geo_maps = []
vertex_1_training_masks = []
vertex_2_score_maps = []
vertex_2_geo_maps = []
vertex_2_training_masks = []
vertex_3_score_maps = []
vertex_3_geo_maps = []
vertex_3_training_masks = []
vertex_4_score_maps = []
vertex_4_geo_maps = []
vertex_4_training_masks = []
for i in index:
try:
im_fn = image_list[i]
im = cv2.imread(im_fn)
# print im_fn
h, w, _ = im.shape
txt_fn = im_fn.replace(os.path.basename(im_fn).split('.')[-1], 'txt')
if not os.path.exists(txt_fn):
print('text file {} does not exists'.format(txt_fn))
continue
text_polys, text_tags, vertex_text_polys, vertex_text_tags, vertex_1_text_polys, vertex_1_text_tags, vertex_2_text_polys, vertex_2_text_tags, vertex_3_text_polys, vertex_3_text_tags, vertex_4_text_polys, vertex_4_text_tags = load_annoataion(txt_fn)
text_polys, text_tags = check_and_validate_polys(text_polys, text_tags, (h, w))
vertex_text_polys, vertex_text_tags = check_and_validate_polys(vertex_text_polys, vertex_text_tags, (h, w))
vertex_1_text_polys, vertex_1_text_tags = check_and_validate_polys(vertex_1_text_polys, vertex_1_text_tags,
(h, w))
vertex_2_text_polys, vertex_2_text_tags = check_and_validate_polys(vertex_2_text_polys, vertex_2_text_tags,
(h, w))
vertex_3_text_polys, vertex_3_text_tags = check_and_validate_polys(vertex_3_text_polys, vertex_3_text_tags,
(h, w))
vertex_4_text_polys, vertex_4_text_tags = check_and_validate_polys(vertex_4_text_polys, vertex_4_text_tags,
(h, w))
# if text_polys.shape[0] == 0:
# continue
# random scale this image
rd_scale = np.random.choice(random_scale)
im = cv2.resize(im, dsize=None, fx=rd_scale, fy=rd_scale)
text_polys *= rd_scale
vertex_1_text_polys *= rd_scale
vertex_2_text_polys *= rd_scale
vertex_3_text_polys *= rd_scale
vertex_4_text_polys *= rd_scale
vertex_text_polys *= rd_scale
# print rd_scale
# random crop a area from image
if np.random.rand() < background_ratio:
# crop background
im, text_polys, text_tags, vertex_text_polys, vertex_text_tags, vertex_1_text_polys, vertex_1_text_tags, vertex_2_text_polys, vertex_2_text_tags, vertex_3_text_polys, vertex_3_text_tags, vertex_4_text_polys, vertex_4_text_tags= crop_area(im, text_polys, text_tags, vertex_text_polys, vertex_text_tags, vertex_1_text_polys, vertex_1_text_tags, vertex_2_text_polys, vertex_2_text_tags, vertex_3_text_polys, vertex_3_text_tags, vertex_4_text_polys, vertex_4_text_tags, crop_background=True)
# im, text_polys, text_tags, vertex_text_polys, vertex_text_tags = crop_area(im, text_polys, text_tags, vertex_text_polys, vertex_text_tags, vertex_1_text_polys, vertex_1_text_tags, vertex_2_text_polys, vertex_2_text_tags, vertex_3_text_polys, vertex_3_text_tags, vertex_4_text_polys, vertex_4_text_tags, crop_background=True)
# vertex_im, vertex_text_polys, vertex_text_tags = crop_area(im, vertex_text_polys, vertex_text_tags, crop_background=True)
vertex_im = im
if text_polys.shape[0] > 0:
# cannot find background
continue
if vertex_1_text_polys.shape[0] > 0:
# cannot find background
continue
if vertex_2_text_polys.shape[0] > 0:
# cannot find background
continue
if vertex_3_text_polys.shape[0] > 0:
# cannot find background
continue
if vertex_4_text_polys.shape[0] > 0:
# cannot find background
continue
if vertex_text_polys.shape[0] > 0:
# cannot find background
continue
# pad and resize image
new_h, new_w, _ = im.shape
vertex_new_h, vertex_new_w, _= vertex_im.shape
max_h_w_i = np.max([new_h, new_w, input_size])
vertex_max_h_w_i = np.max([vertex_new_h, vertex_new_w, input_size])
im_padded = np.zeros((max_h_w_i, max_h_w_i, 3), dtype=np.uint8)
vertex_im_padded = np.zeros((vertex_max_h_w_i,vertex_max_h_w_i,3),dtype=np.uint8)
im_padded[:new_h, :new_w, :] = im.copy()
vertex_im_padded[:vertex_new_h,:vertex_new_w,:] = vertex_im.copy()
im = cv2.resize(im_padded, dsize=(input_size, input_size))
vertex_im = cv2.resize(vertex_im_padded, dsize=(input_size, input_size))
score_map = np.zeros((input_size, input_size), dtype=np.uint8)
vertex_score_map = np.zeros((input_size, input_size), dtype=np.uint8)
geo_map_channels = 5 if FLAGS.geometry == 'RBOX' else 8
vertex_geo_map_channels = 5 if FLAGS.geometry == 'RBOX' else 8
geo_map = np.zeros((input_size, input_size, geo_map_channels), dtype=np.float32)
vertex_geo_map = np.zeros((input_size, input_size, vertex_geo_map_channels), dtype=np.float32)
training_mask = np.ones((input_size, input_size), dtype=np.uint8)
vertex_training_mask = np.ones((input_size, input_size), dtype=np.uint8)
vertex_1_score_map = np.zeros((input_size, input_size), dtype=np.uint8)
vertex_1_geo_map_channels = 5 if FLAGS.geometry == 'RBOX' else 8
vertex_1_geo_map = np.zeros((input_size, input_size, vertex_1_geo_map_channels), dtype=np.float32)
vertex_1_training_mask = np.ones((input_size, input_size), dtype=np.uint8)
vertex_2_score_map = np.zeros((input_size, input_size), dtype=np.uint8)
vertex_2_geo_map_channels = 5 if FLAGS.geometry == 'RBOX' else 8
vertex_2_geo_map = np.zeros((input_size, input_size, vertex_2_geo_map_channels), dtype=np.float32)
vertex_2_training_mask = np.ones((input_size, input_size), dtype=np.uint8)
vertex_3_score_map = np.zeros((input_size, input_size), dtype=np.uint8)
vertex_3_geo_map_channels = 5 if FLAGS.geometry == 'RBOX' else 8
vertex_3_geo_map = np.zeros((input_size, input_size, vertex_3_geo_map_channels), dtype=np.float32)
vertex_3_training_mask = np.ones((input_size, input_size), dtype=np.uint8)
vertex_4_score_map = np.zeros((input_size, input_size), dtype=np.uint8)
vertex_4_geo_map_channels = 5 if FLAGS.geometry == 'RBOX' else 8
vertex_4_geo_map = np.zeros((input_size, input_size, vertex_4_geo_map_channels), dtype=np.float32)
vertex_4_training_mask = np.ones((input_size, input_size), dtype=np.uint8)
else:
im, text_polys, text_tags, vertex_text_polys, vertex_text_tags, vertex_1_text_polys, vertex_1_text_tags, vertex_2_text_polys, vertex_2_text_tags, vertex_3_text_polys, vertex_3_text_tags, vertex_4_text_polys, vertex_4_text_tags= crop_area(im, text_polys, text_tags, vertex_text_polys, vertex_text_tags, vertex_1_text_polys, vertex_1_text_tags, vertex_2_text_polys, vertex_2_text_tags, vertex_3_text_polys, vertex_3_text_tags, vertex_4_text_polys, vertex_4_text_tags, crop_background=False)
# im, text_polys, text_tags, vertex_text_polys, vertex_text_tags = crop_area(im, text_polys, text_tags, vertex_text_polys, vertex_text_tags, crop_background=False)
# vertex_im, vertex_text_polys, vertex_text_tags = crop_area(im, vertex_text_polys, vertex_text_tags, crop_background=False)
vertex_im = im
if text_polys.shape[0] == 0:
continue
if vertex_1_text_polys.shape[0] == 0:
continue
if vertex_2_text_polys.shape[0] == 0:
continue
if vertex_3_text_polys.shape[0] == 0:
continue
if vertex_4_text_polys.shape[0] == 0:
continue
if vertex_text_polys.shape[0] == 0:
continue
h, w, _ = im.shape
# pad the image to the training input size or the longer side of image
new_h, new_w, _ = im.shape
vertex_new_h, vertex_new_w, _ = vertex_im.shape
max_h_w_i = np.max([new_h, new_w, input_size])
vertex_max_h_w_i = np.max([vertex_new_h, vertex_new_w, input_size])
im_padded = np.zeros((max_h_w_i, max_h_w_i, 3), dtype=np.uint8)
vertex_im_padded = np.zeros((vertex_max_h_w_i, vertex_max_h_w_i, 3), dtype=np.uint8)
im_padded[:new_h, :new_w, :] = im.copy()
vertex_im_padded[:vertex_new_h, :vertex_new_w, :] = vertex_im.copy()
im = im_padded
vertex_im = vertex_im_padded
# resize the image to input size
new_h, new_w, _ = im.shape
vertex_new_h, vertex_new_w, _ = vertex_im.shape
resize_h = input_size
resize_w = input_size
im = cv2.resize(im, dsize=(resize_w, resize_h))
vertex_im = cv2.resize(vertex_im,dsize=(resize_w,resize_h))
resize_ratio_3_x = resize_w/float(new_w)