95 lines
3.5 KiB
Python
95 lines
3.5 KiB
Python
# -*- coding:utf-8 -*-
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import numpy as np
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import cv2
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from shapely.geometry import Polygon
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import pyclipper
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__all__ = ['MakeShrinkMap']
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class MakeShrinkMap(object):
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r'''
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Making binary mask from detection data with ICDAR format.
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Typically following the process of class `MakeICDARData`.
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'''
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def __init__(self, min_text_size=8, shrink_ratio=0.4, **kwargs):
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self.min_text_size = min_text_size
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self.shrink_ratio = shrink_ratio
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def __call__(self, data):
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image = data['image']
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text_polys = data['polys']
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ignore_tags = data['ignore_tags']
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h, w = image.shape[:2]
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text_polys, ignore_tags = self.validate_polygons(text_polys,
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ignore_tags, h, w)
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gt = np.zeros((h, w), dtype=np.float32)
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# gt = np.zeros((1, h, w), dtype=np.float32)
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mask = np.ones((h, w), dtype=np.float32)
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for i in range(len(text_polys)):
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polygon = text_polys[i]
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height = max(polygon[:, 1]) - min(polygon[:, 1])
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width = max(polygon[:, 0]) - min(polygon[:, 0])
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if ignore_tags[i] or min(height, width) < self.min_text_size:
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cv2.fillPoly(mask,
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polygon.astype(np.int32)[np.newaxis, :, :], 0)
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ignore_tags[i] = True
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else:
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polygon_shape = Polygon(polygon)
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distance = polygon_shape.area * (
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1 - np.power(self.shrink_ratio, 2)) / polygon_shape.length
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subject = [tuple(l) for l in text_polys[i]]
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padding = pyclipper.PyclipperOffset()
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padding.AddPath(subject, pyclipper.JT_ROUND,
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pyclipper.ET_CLOSEDPOLYGON)
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shrinked = padding.Execute(-distance)
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if shrinked == []:
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cv2.fillPoly(mask,
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polygon.astype(np.int32)[np.newaxis, :, :], 0)
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ignore_tags[i] = True
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continue
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shrinked = np.array(shrinked[0]).reshape(-1, 2)
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cv2.fillPoly(gt, [shrinked.astype(np.int32)], 1)
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# cv2.fillPoly(gt[0], [shrinked.astype(np.int32)], 1)
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data['shrink_map'] = gt
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data['shrink_mask'] = mask
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return data
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def validate_polygons(self, polygons, ignore_tags, h, w):
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'''
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polygons (numpy.array, required): of shape (num_instances, num_points, 2)
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'''
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if len(polygons) == 0:
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return polygons, ignore_tags
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assert len(polygons) == len(ignore_tags)
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for polygon in polygons:
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polygon[:, 0] = np.clip(polygon[:, 0], 0, w - 1)
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polygon[:, 1] = np.clip(polygon[:, 1], 0, h - 1)
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for i in range(len(polygons)):
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area = self.polygon_area(polygons[i])
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if abs(area) < 1:
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ignore_tags[i] = True
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if area > 0:
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polygons[i] = polygons[i][::-1, :]
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return polygons, ignore_tags
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def polygon_area(self, polygon):
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# return cv2.contourArea(polygon.astype(np.float32))
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edge = 0
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for i in range(polygon.shape[0]):
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next_index = (i + 1) % polygon.shape[0]
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edge += (polygon[next_index, 0] - polygon[i, 0]) * (
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polygon[next_index, 1] - polygon[i, 1])
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return edge / 2.
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