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123
backend/ppocr/data/imaug/make_shrink_map.py
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123
backend/ppocr/data/imaug/make_shrink_map.py
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# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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This code is refer from:
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https://github.com/WenmuZhou/DBNet.pytorch/blob/master/data_loader/modules/make_shrink_map.py
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"""
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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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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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subject = [tuple(l) for l in polygon]
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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 = []
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# Increase the shrink ratio every time we get multiple polygon returned back
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possible_ratios = np.arange(self.shrink_ratio, 1,
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self.shrink_ratio)
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np.append(possible_ratios, 1)
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# print(possible_ratios)
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for ratio in possible_ratios:
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# print(f"Change shrink ratio to {ratio}")
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distance = polygon_shape.area * (
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1 - np.power(ratio, 2)) / polygon_shape.length
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shrinked = padding.Execute(-distance)
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if len(shrinked) == 1:
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break
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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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for each_shirnk in shrinked:
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shirnk = np.array(each_shirnk).reshape(-1, 2)
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cv2.fillPoly(gt, [shirnk.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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"""
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compute polygon area
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"""
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area = 0
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q = polygon[-1]
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for p in polygon:
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area += p[0] * q[1] - p[1] * q[0]
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q = p
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return area / 2.0
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