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from collections import OrderedDict
import numpy as np
import cv2
from shapely.geometry import Polygon
import pyclipper
from concern.config import Configurable, State
class MakeSegDetectorData(Configurable):
min_text_size = State(default=8)
shrink_ratio = State(default=0.4)
def __init__(self, **kwargs):
self.load_all(**kwargs)
def __call__(self, data, *args, **kwargs):
'''
data: a dict typically returned from `MakeICDARData`,
where the following keys are contrains:
image*, polygons*, ignore_tags*, shape, filename
* means required.
'''
image = data['image']
polygons = data['polygons']
ignore_tags = data['ignore_tags']
image = data['image']
filename = data['filename']
h, w = image.shape[:2]
polygons, ignore_tags = self.validate_polygons(
polygons, ignore_tags, h, w)
gt = np.zeros((1, h, w), dtype=np.float32)
mask = np.ones((h, w), dtype=np.float32)
for i in range(polygons.shape[0]):
polygon = polygons[i]
height = min(np.linalg.norm(polygon[0] - polygon[3]),
np.linalg.norm(polygon[1] - polygon[2]))
width = min(np.linalg.norm(polygon[0] - polygon[1]),
np.linalg.norm(polygon[2] - polygon[3]))
if ignore_tags[i] or min(height, width) < self.min_text_size:
cv2.fillPoly(mask, polygon.astype(
np.int32)[np.newaxis, :, :], 0)
ignore_tags[i] = True
else:
polygon_shape = Polygon(polygon)
distance = polygon_shape.area * \
(1 - np.power(self.shrink_ratio, 2)) / polygon_shape.length
subject = [tuple(l) for l in polygons[i]]
padding = pyclipper.PyclipperOffset()
padding.AddPath(subject, pyclipper.JT_ROUND,
pyclipper.ET_CLOSEDPOLYGON)
shrinked = padding.Execute(-distance)
if shrinked == []:
cv2.fillPoly(mask, polygon.astype(
np.int32)[np.newaxis, :, :], 0)
ignore_tags[i] = True
continue
shrinked = np.array(shrinked[0]).reshape(-1, 2)
cv2.fillPoly(gt[0], [shrinked.astype(np.int32)], 1)
if filename is None:
filename = ''
data.update(image=image,
polygons=polygons,
gt=gt, mask=mask, filename=filename)
return data
def validate_polygons(self, polygons, ignore_tags, h, w):
'''
polygons (numpy.array, required): of shape (num_instances, num_points, 2)
'''
if polygons.shape[0] == 0:
return polygons, ignore_tags
assert polygons.shape[0] == len(ignore_tags)
polygons[:, :, 0] = np.clip(polygons[:, :, 0], 0, w - 1)
polygons[:, :, 1] = np.clip(polygons[:, :, 1], 0, h - 1)
for i in range(polygons.shape[0]):
area = self.polygon_area(polygons[i])
if abs(area) < 1:
ignore_tags[i] = True
if area > 0:
polygons[i] = polygons[i][(0, 3, 2, 1), :]
return polygons, ignore_tags
def polygon_area(self, polygon):
edge = [
(polygon[1][0] - polygon[0][0]) * (polygon[1][1] + polygon[0][1]),
(polygon[2][0] - polygon[1][0]) * (polygon[2][1] + polygon[1][1]),
(polygon[3][0] - polygon[2][0]) * (polygon[3][1] + polygon[2][1]),
(polygon[0][0] - polygon[3][0]) * (polygon[0][1] + polygon[3][1])
]
return np.sum(edge) / 2.
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