def get_ann(img, gt_path):
# h, w = img.shape[0:2]
h, w = img.height, img.width
lines = mmcv.list_from_file(gt_path)
bboxes = []
words = []
for line in lines:
line = line.encode('utf-8').decode('utf-8-sig')
line = line.replace('\xef\xbb\xbf', '')
gt = line.split(' ')
w_ = np.float(gt[4])
h_ = np.float(gt[5])
x1 = np.float(gt[2]) + w_ / 2.0
y1 = np.float(gt[3]) + h_ / 2.0
theta = np.float(gt[6]) / math.pi * 180
bbox = cv2.boxPoints(((x1, y1), (w_, h_), theta))
# print(np.asarray(bbox.reshape(-1)))
bbox = np.array(adjust_box_sort(np.asarray(
bbox.reshape(-1)))) / ([w * 1.0, h * 1.0] * 4)
# bbox = bbox.reshape(-1)
bboxes.append(bbox)
words.append('???')
return np.array(bboxes), words
def parse_mat(self, mat, image_id):
"""
.mat file parser
:param mat_path: (str), mat file path
:return: (list), TextInstance
"""
labels = []
vertices = []
if len(mat.shape) < 3:
number = 1
else:
number = mat.shape[2]
for cell in range(number):
if number == 1:
x1 = mat[0][0]
x2 = mat[0][1]
x3 = mat[0][2]
x4 = mat[0][3]
y1 = mat[1][0]
y2 = mat[1][1]
y3 = mat[1][2]
y4 = mat[1][3]
else:
x1 = mat[0][0][cell]
x2 = mat[0][1][cell]
x3 = mat[0][2][cell]
x4 = mat[0][3][cell]
y1 = mat[1][0][cell]
y2 = mat[1][1][cell]
y3 = mat[1][2][cell]
y4 = mat[1][3][cell]
oriented_box = [
int(x1),
int(y1),
int(x2),
int(y2),
int(x3),
int(y3),
int(x4),
int(y4)
]
oriented_box = adjust_box_sort(oriented_box)
oriented_box = np.asarray(oriented_box)
vertices.append(oriented_box)
labels.append(1)
return np.array(vertices), np.array(labels)
def extract_vertices(lines):
'''extract vertices info from txt lines
Input:
lines : list of string info
Output:
vertices: vertices of text regions <numpy.ndarray, (n,8)>
labels : 1->valid, 0->ignore, <numpy.ndarray, (n,)>
'''
labels = []
vertices = []
for line in lines:
box = list(map(int, line.rstrip('\n').lstrip('\ufeff').split(',')[:8]))
box = adjust_box_sort(box)
vertices.append(box)
label = 0 if '###' in line else 1
labels.append(label)
return np.array(vertices), np.array(labels)