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from __future__ import absolute_import, division, print_function, unicode_literals
import cv2
import numpy as np
import pyclipper
from shapely.geometry import Polygon
__all__ = ["MakeShrinkMap"]
class MakeShrinkMap(object):
r"""
Making binary mask from detection data with ICDAR format.
Typically following the process of class `MakeICDARData`.
"""
def __init__(self, min_text_size=8, shrink_ratio=0.4, **kwargs):
self.min_text_size = min_text_size
self.shrink_ratio = shrink_ratio
def __call__(self, data):
image = data["image"]
text_polys = data["polys"]
ignore_tags = data["ignore_tags"]
h, w = image.shape[:2]
text_polys, ignore_tags = self.validate_polygons(text_polys, ignore_tags, h, w)
gt = np.zeros((h, w), dtype=np.float32)
mask = np.ones((h, w), dtype=np.float32)
for i in range(len(text_polys)):
polygon = text_polys[i]
height = max(polygon[:, 1]) - min(polygon[:, 1])
width = max(polygon[:, 0]) - min(polygon[:, 0])
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)
subject = [tuple(l) for l in polygon]
padding = pyclipper.PyclipperOffset()
padding.AddPath(subject, pyclipper.JT_ROUND, pyclipper.ET_CLOSEDPOLYGON)
shrinked = []
# Increase the shrink ratio every time we get multiple polygon returned back
possible_ratios = np.arange(self.shrink_ratio, 1, self.shrink_ratio)
np.append(possible_ratios, 1)
# print(possible_ratios)
for ratio in possible_ratios:
# print(f"Change shrink ratio to {ratio}")
distance = (
polygon_shape.area
* (1 - np.power(ratio, 2))
/ polygon_shape.length
)
shrinked = padding.Execute(-distance)
if len(shrinked) == 1:
break
if shrinked == []:
cv2.fillPoly(mask, polygon.astype(np.int32)[np.newaxis, :, :], 0)
ignore_tags[i] = True
continue
for each_shirnk in shrinked:
shirnk = np.array(each_shirnk).reshape(-1, 2)
cv2.fillPoly(gt, [shirnk.astype(np.int32)], 1)
data["shrink_map"] = gt
data["shrink_mask"] = mask
return data
def validate_polygons(self, polygons, ignore_tags, h, w):
"""
polygons (numpy.array, required): of shape (num_instances, num_points, 2)
"""
if len(polygons) == 0:
return polygons, ignore_tags
assert len(polygons) == len(ignore_tags)
for polygon in polygons:
polygon[:, 0] = np.clip(polygon[:, 0], 0, w - 1)
polygon[:, 1] = np.clip(polygon[:, 1], 0, h - 1)
for i in range(len(polygons)):
area = self.polygon_area(polygons[i])
if abs(area) < 1:
ignore_tags[i] = True
if area > 0:
polygons[i] = polygons[i][::-1, :]
return polygons, ignore_tags
def polygon_area(self, polygon):
"""
compute polygon area
"""
area = 0
q = polygon[-1]
for p in polygon:
area += p[0] * q[1] - p[1] * q[0]
q = p
return area / 2.0
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