/
utils.py
173 lines (146 loc) · 5.94 KB
/
utils.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
import numpy as np
import cv2
from PIL import Image
def rotate_cut_img(im, degree, x_center, y_center, w, h, leftAdjust=False, rightAdjust=False, alph=0.2):
# degree_ = degree * 180.0 / np.pi
# print(degree_)
right = 0
left = 0
if rightAdjust:
right = 1
if leftAdjust:
left = 1
box = (max(1, x_center - w / 2 - left * alph * (w / 2))
, y_center - h / 2, # ymin
min(x_center + w / 2 + right * alph * (w / 2), im.size[0] - 1)
, y_center + h / 2) # ymax
newW = box[2] - box[0]
newH = box[3] - box[1]
tmpImg = im.rotate(degree, center=(x_center, y_center)).crop(box)
return tmpImg, newW, newH
def crop_rect(img, rect, alph=0.15):
img = np.asarray(img)
# get the parameter of the small rectangle
# print("rect!")
# print(rect)
center, size, angle = rect[0], rect[1], rect[2]
min_size = min(size)
if angle > -45:
center, size = tuple(map(int, center)), tuple(map(int, size))
# angle-=270
size = (int(size[0] + min_size * alph), int(size[1] + min_size * alph))
height, width = img.shape[0], img.shape[1]
M = cv2.getRotationMatrix2D(center, angle, 1)
# size = tuple([int(rect[1][1]), int(rect[1][0])])
img_rot = cv2.warpAffine(img, M, (width, height))
# cv2.imwrite("debug_im/img_rot.jpg", img_rot)
img_crop = cv2.getRectSubPix(img_rot, size, center)
else:
center = tuple(map(int, center))
size = tuple([int(rect[1][1]), int(rect[1][0])])
size = (int(size[0] + min_size * alph), int(size[1] + min_size * alph))
angle -= 270
height, width = img.shape[0], img.shape[1]
M = cv2.getRotationMatrix2D(center, angle, 1)
img_rot = cv2.warpAffine(img, M, (width, height))
# cv2.imwrite("debug_im/img_rot.jpg", img_rot)
img_crop = cv2.getRectSubPix(img_rot, size, center)
img_crop = Image.fromarray(img_crop)
return img_crop
def draw_bbox(img_path, result, color=(255, 0, 0), thickness=2):
if isinstance(img_path, str):
img_path = cv2.imread(img_path)
# img_path = cv2.cvtColor(img_path, cv2.COLOR_BGR2RGB)
img_path = img_path.copy()
for point in result:
point = point.astype(int)
cv2.line(img_path, tuple(point[0]), tuple(point[1]), color, thickness)
cv2.line(img_path, tuple(point[1]), tuple(point[2]), color, thickness)
cv2.line(img_path, tuple(point[2]), tuple(point[3]), color, thickness)
cv2.line(img_path, tuple(point[3]), tuple(point[0]), color, thickness)
return img_path
def sort_box(boxs):
res = []
for box in boxs:
# box = [x if x>0 else 0 for x in box ]
x1, y1, x2, y2, x3, y3, x4, y4 = box[:8]
newBox = [[x1, y1], [x2, y2], [x3, y3], [x4, y4]]
# sort x
newBox = sorted(newBox, key=lambda x: x[0])
x1, y1 = sorted(newBox[:2], key=lambda x: x[1])[0]
index = newBox.index([x1, y1])
newBox.pop(index)
newBox = sorted(newBox, key=lambda x: -x[1])
x4, y4 = sorted(newBox[:2], key=lambda x: x[0])[0]
index = newBox.index([x4, y4])
newBox.pop(index)
newBox = sorted(newBox, key=lambda x: -x[0])
x2, y2 = sorted(newBox[:2], key=lambda x: x[1])[0]
index = newBox.index([x2, y2])
newBox.pop(index)
newBox = sorted(newBox, key=lambda x: -x[1])
x3, y3 = sorted(newBox[:2], key=lambda x: x[0])[0]
res.append([x1, y1, x2, y2, x3, y3, x4, y4])
return res
def solve(box):
"""
绕 cx,cy点 w,h 旋转 angle 的坐标
x = cx-w/2
y = cy-h/2
x1-cx = -w/2*cos(angle) +h/2*sin(angle)
y1 -cy= -w/2*sin(angle) -h/2*cos(angle)
h(x1-cx) = -wh/2*cos(angle) +hh/2*sin(angle)
w(y1 -cy)= -ww/2*sin(angle) -hw/2*cos(angle)
(hh+ww)/2sin(angle) = h(x1-cx)-w(y1 -cy)
"""
x1, y1, x2, y2, x3, y3, x4, y4 = box[:8]
cx = (x1 + x3 + x2 + x4) / 4.0
cy = (y1 + y3 + y4 + y2) / 4.0
w = (np.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2) + np.sqrt((x3 - x4) ** 2 + (y3 - y4) ** 2)) / 2
h = (np.sqrt((x2 - x3) ** 2 + (y2 - y3) ** 2) + np.sqrt((x1 - x4) ** 2 + (y1 - y4) ** 2)) / 2
sinA = (h * (x1 - cx) - w * (y1 - cy)) * 1.0 / (h * h + w * w) * 2
angle = np.arcsin(sinA)
return angle, w, h, cx, cy
def sorted_boxes(dt_boxes):
"""
Sort text boxes in order from top to bottom, left to right
args:
dt_boxes(array):detected text boxes with shape [4, 2]
return:
sorted boxes(array) with shape [4, 2]
"""
num_boxes = dt_boxes.shape[0]
sorted_boxes = sorted(dt_boxes, key=lambda x: (x[0][1], x[0][0]))
_boxes = list(sorted_boxes)
for i in range(num_boxes - 1):
if abs(_boxes[i+1][0][1] - _boxes[i][0][1]) < 10 and \
(_boxes[i + 1][0][0] < _boxes[i][0][0]):
tmp = _boxes[i]
_boxes[i] = _boxes[i + 1]
_boxes[i + 1] = tmp
return _boxes
def get_rotate_crop_image(img, points):
img_height, img_width = img.shape[0:2]
left = int(np.min(points[:, 0]))
right = int(np.max(points[:, 0]))
top = int(np.min(points[:, 1]))
bottom = int(np.max(points[:, 1]))
img_crop = img[top:bottom, left:right, :].copy()
points[:, 0] = points[:, 0] - left
points[:, 1] = points[:, 1] - top
img_crop_width = int(np.linalg.norm(points[0] - points[1]))
img_crop_height = int(np.linalg.norm(points[0] - points[3]))
pts_std = np.float32([[0, 0], [img_crop_width, 0],\
[img_crop_width, img_crop_height], [0, img_crop_height]])
M = cv2.getPerspectiveTransform(points, pts_std)
dst_img = cv2.warpPerspective(
img_crop,
M, (img_crop_width, img_crop_height),
borderMode=cv2.BORDER_REPLICATE)
dst_img_height, dst_img_width = dst_img.shape[0:2]
if dst_img_height * 1.0 / dst_img_width >= 1.5:
dst_img = np.rot90(dst_img)
return dst_img
def app_url(version, name):
url = '/{}/{}'.format(version, name)
return url