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- # copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- """
- This code is refer from:
- https://github.com/WenmuZhou/DBNet.pytorch/blob/master/data_loader/modules/make_shrink_map.py
- """
- from __future__ import absolute_import
- from __future__ import division
- from __future__ import print_function
- from __future__ import unicode_literals
- import numpy as np
- import cv2
- from shapely.geometry import Polygon
- import pyclipper
- __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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