utils.py 6.8 KB
Newer Older
chenxj's avatar
chenxj committed
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
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
import numpy as np
import cv2
from PIL import Image
import os


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

def _check_image_file(path):
    img_end = {'jpg', 'bmp', 'png', 'jpeg', 'rgb', 'tif', 'tiff', 'gif'}
    return any([path.lower().endswith(e) for e in img_end])

def get_image_file_list(img_file):
    imgs_lists = []
    if img_file is None or not os.path.exists(img_file):
        raise Exception("not found any img file in {}".format(img_file))

    if os.path.isfile(img_file) and _check_image_file(img_file):
        imgs_lists.append(img_file)
    elif os.path.isdir(img_file):
        for single_file in os.listdir(img_file):
            file_path = os.path.join(img_file, single_file)
            if os.path.isfile(file_path) and _check_image_file(file_path):
                imgs_lists.append(file_path)
    if len(imgs_lists) == 0:
        raise Exception("not found any img file in {}".format(img_file))
    imgs_lists = sorted(imgs_lists)
    return imgs_lists