689 lines
27 KiB
Python
689 lines
27 KiB
Python
#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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import math
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import cv2
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import numpy as np
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import json
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import sys
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import os
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__all__ = ['SASTProcessTrain']
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class SASTProcessTrain(object):
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def __init__(self,
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image_shape = [512, 512],
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min_crop_size = 24,
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min_crop_side_ratio = 0.3,
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min_text_size = 10,
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max_text_size = 512,
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**kwargs):
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self.input_size = image_shape[1]
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self.min_crop_size = min_crop_size
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self.min_crop_side_ratio = min_crop_side_ratio
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self.min_text_size = min_text_size
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self.max_text_size = max_text_size
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def quad_area(self, poly):
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"""
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compute area of a polygon
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:param poly:
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:return:
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"""
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edge = [
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(poly[1][0] - poly[0][0]) * (poly[1][1] + poly[0][1]),
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(poly[2][0] - poly[1][0]) * (poly[2][1] + poly[1][1]),
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(poly[3][0] - poly[2][0]) * (poly[3][1] + poly[2][1]),
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(poly[0][0] - poly[3][0]) * (poly[0][1] + poly[3][1])
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]
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return np.sum(edge) / 2.
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def gen_quad_from_poly(self, poly):
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"""
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Generate min area quad from poly.
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"""
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point_num = poly.shape[0]
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min_area_quad = np.zeros((4, 2), dtype=np.float32)
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if True:
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rect = cv2.minAreaRect(poly.astype(np.int32)) # (center (x,y), (width, height), angle of rotation)
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center_point = rect[0]
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box = np.array(cv2.boxPoints(rect))
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first_point_idx = 0
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min_dist = 1e4
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for i in range(4):
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dist = np.linalg.norm(box[(i + 0) % 4] - poly[0]) + \
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np.linalg.norm(box[(i + 1) % 4] - poly[point_num // 2 - 1]) + \
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np.linalg.norm(box[(i + 2) % 4] - poly[point_num // 2]) + \
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np.linalg.norm(box[(i + 3) % 4] - poly[-1])
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if dist < min_dist:
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min_dist = dist
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first_point_idx = i
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for i in range(4):
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min_area_quad[i] = box[(first_point_idx + i) % 4]
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return min_area_quad
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def check_and_validate_polys(self, polys, tags, xxx_todo_changeme):
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"""
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check so that the text poly is in the same direction,
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and also filter some invalid polygons
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:param polys:
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:param tags:
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:return:
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"""
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(h, w) = xxx_todo_changeme
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if polys.shape[0] == 0:
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return polys, np.array([]), np.array([])
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polys[:, :, 0] = np.clip(polys[:, :, 0], 0, w - 1)
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polys[:, :, 1] = np.clip(polys[:, :, 1], 0, h - 1)
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validated_polys = []
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validated_tags = []
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hv_tags = []
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for poly, tag in zip(polys, tags):
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quad = self.gen_quad_from_poly(poly)
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p_area = self.quad_area(quad)
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if abs(p_area) < 1:
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print('invalid poly')
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continue
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if p_area > 0:
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if tag == False:
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print('poly in wrong direction')
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tag = True # reversed cases should be ignore
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poly = poly[(0, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1), :]
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quad = quad[(0, 3, 2, 1), :]
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len_w = np.linalg.norm(quad[0] - quad[1]) + np.linalg.norm(quad[3] - quad[2])
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len_h = np.linalg.norm(quad[0] - quad[3]) + np.linalg.norm(quad[1] - quad[2])
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hv_tag = 1
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if len_w * 2.0 < len_h:
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hv_tag = 0
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validated_polys.append(poly)
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validated_tags.append(tag)
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hv_tags.append(hv_tag)
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return np.array(validated_polys), np.array(validated_tags), np.array(hv_tags)
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def crop_area(self, im, polys, tags, hv_tags, crop_background=False, max_tries=25):
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"""
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make random crop from the input image
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:param im:
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:param polys:
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:param tags:
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:param crop_background:
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:param max_tries: 50 -> 25
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:return:
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"""
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h, w, _ = im.shape
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pad_h = h // 10
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pad_w = w // 10
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h_array = np.zeros((h + pad_h * 2), dtype=np.int32)
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w_array = np.zeros((w + pad_w * 2), dtype=np.int32)
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for poly in polys:
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poly = np.round(poly, decimals=0).astype(np.int32)
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minx = np.min(poly[:, 0])
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maxx = np.max(poly[:, 0])
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w_array[minx + pad_w: maxx + pad_w] = 1
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miny = np.min(poly[:, 1])
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maxy = np.max(poly[:, 1])
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h_array[miny + pad_h: maxy + pad_h] = 1
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# ensure the cropped area not across a text
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h_axis = np.where(h_array == 0)[0]
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w_axis = np.where(w_array == 0)[0]
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if len(h_axis) == 0 or len(w_axis) == 0:
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return im, polys, tags, hv_tags
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for i in range(max_tries):
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xx = np.random.choice(w_axis, size=2)
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xmin = np.min(xx) - pad_w
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xmax = np.max(xx) - pad_w
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xmin = np.clip(xmin, 0, w - 1)
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xmax = np.clip(xmax, 0, w - 1)
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yy = np.random.choice(h_axis, size=2)
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ymin = np.min(yy) - pad_h
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ymax = np.max(yy) - pad_h
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ymin = np.clip(ymin, 0, h - 1)
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ymax = np.clip(ymax, 0, h - 1)
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# if xmax - xmin < ARGS.min_crop_side_ratio * w or \
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# ymax - ymin < ARGS.min_crop_side_ratio * h:
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if xmax - xmin < self.min_crop_size or \
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ymax - ymin < self.min_crop_size:
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# area too small
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continue
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if polys.shape[0] != 0:
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poly_axis_in_area = (polys[:, :, 0] >= xmin) & (polys[:, :, 0] <= xmax) \
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& (polys[:, :, 1] >= ymin) & (polys[:, :, 1] <= ymax)
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selected_polys = np.where(np.sum(poly_axis_in_area, axis=1) == 4)[0]
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else:
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selected_polys = []
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if len(selected_polys) == 0:
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# no text in this area
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if crop_background:
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return im[ymin : ymax + 1, xmin : xmax + 1, :], \
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polys[selected_polys], tags[selected_polys], hv_tags[selected_polys], txts
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else:
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continue
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im = im[ymin: ymax + 1, xmin: xmax + 1, :]
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polys = polys[selected_polys]
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tags = tags[selected_polys]
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hv_tags = hv_tags[selected_polys]
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polys[:, :, 0] -= xmin
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polys[:, :, 1] -= ymin
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return im, polys, tags, hv_tags
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return im, polys, tags, hv_tags
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def generate_direction_map(self, poly_quads, direction_map):
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"""
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"""
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width_list = []
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height_list = []
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for quad in poly_quads:
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quad_w = (np.linalg.norm(quad[0] - quad[1]) + np.linalg.norm(quad[2] - quad[3])) / 2.0
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quad_h = (np.linalg.norm(quad[0] - quad[3]) + np.linalg.norm(quad[2] - quad[1])) / 2.0
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width_list.append(quad_w)
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height_list.append(quad_h)
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norm_width = max(sum(width_list) / (len(width_list) + 1e-6), 1.0)
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average_height = max(sum(height_list) / (len(height_list) + 1e-6), 1.0)
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for quad in poly_quads:
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direct_vector_full = ((quad[1] + quad[2]) - (quad[0] + quad[3])) / 2.0
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direct_vector = direct_vector_full / (np.linalg.norm(direct_vector_full) + 1e-6) * norm_width
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direction_label = tuple(map(float, [direct_vector[0], direct_vector[1], 1.0 / (average_height + 1e-6)]))
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cv2.fillPoly(direction_map, quad.round().astype(np.int32)[np.newaxis, :, :], direction_label)
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return direction_map
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def calculate_average_height(self, poly_quads):
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"""
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"""
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height_list = []
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for quad in poly_quads:
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quad_h = (np.linalg.norm(quad[0] - quad[3]) + np.linalg.norm(quad[2] - quad[1])) / 2.0
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height_list.append(quad_h)
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average_height = max(sum(height_list) / len(height_list), 1.0)
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return average_height
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def generate_tcl_label(self, hw, polys, tags, ds_ratio,
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tcl_ratio=0.3, shrink_ratio_of_width=0.15):
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"""
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Generate polygon.
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"""
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h, w = hw
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h, w = int(h * ds_ratio), int(w * ds_ratio)
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polys = polys * ds_ratio
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score_map = np.zeros((h, w,), dtype=np.float32)
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tbo_map = np.zeros((h, w, 5), dtype=np.float32)
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training_mask = np.ones((h, w,), dtype=np.float32)
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direction_map = np.ones((h, w, 3)) * np.array([0, 0, 1]).reshape([1, 1, 3]).astype(np.float32)
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for poly_idx, poly_tag in enumerate(zip(polys, tags)):
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poly = poly_tag[0]
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tag = poly_tag[1]
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# generate min_area_quad
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min_area_quad, center_point = self.gen_min_area_quad_from_poly(poly)
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min_area_quad_h = 0.5 * (np.linalg.norm(min_area_quad[0] - min_area_quad[3]) +
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np.linalg.norm(min_area_quad[1] - min_area_quad[2]))
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min_area_quad_w = 0.5 * (np.linalg.norm(min_area_quad[0] - min_area_quad[1]) +
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np.linalg.norm(min_area_quad[2] - min_area_quad[3]))
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if min(min_area_quad_h, min_area_quad_w) < self.min_text_size * ds_ratio \
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or min(min_area_quad_h, min_area_quad_w) > self.max_text_size * ds_ratio:
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continue
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if tag:
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# continue
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cv2.fillPoly(training_mask, poly.astype(np.int32)[np.newaxis, :, :], 0.15)
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else:
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tcl_poly = self.poly2tcl(poly, tcl_ratio)
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tcl_quads = self.poly2quads(tcl_poly)
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poly_quads = self.poly2quads(poly)
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# stcl map
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stcl_quads, quad_index = self.shrink_poly_along_width(tcl_quads, shrink_ratio_of_width=shrink_ratio_of_width,
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expand_height_ratio=1.0 / tcl_ratio)
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# generate tcl map
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cv2.fillPoly(score_map, np.round(stcl_quads).astype(np.int32), 1.0)
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# generate tbo map
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for idx, quad in enumerate(stcl_quads):
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quad_mask = np.zeros((h, w), dtype=np.float32)
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quad_mask = cv2.fillPoly(quad_mask, np.round(quad[np.newaxis, :, :]).astype(np.int32), 1.0)
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tbo_map = self.gen_quad_tbo(poly_quads[quad_index[idx]], quad_mask, tbo_map)
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return score_map, tbo_map, training_mask
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def generate_tvo_and_tco(self, hw, polys, tags, tcl_ratio=0.3, ds_ratio=0.25):
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"""
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Generate tcl map, tvo map and tbo map.
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"""
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h, w = hw
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h, w = int(h * ds_ratio), int(w * ds_ratio)
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polys = polys * ds_ratio
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poly_mask = np.zeros((h, w), dtype=np.float32)
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tvo_map = np.ones((9, h, w), dtype=np.float32)
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tvo_map[0:-1:2] = np.tile(np.arange(0, w), (h, 1))
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tvo_map[1:-1:2] = np.tile(np.arange(0, w), (h, 1)).T
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poly_tv_xy_map = np.zeros((8, h, w), dtype=np.float32)
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# tco map
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tco_map = np.ones((3, h, w), dtype=np.float32)
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tco_map[0] = np.tile(np.arange(0, w), (h, 1))
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tco_map[1] = np.tile(np.arange(0, w), (h, 1)).T
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poly_tc_xy_map = np.zeros((2, h, w), dtype=np.float32)
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poly_short_edge_map = np.ones((h, w), dtype=np.float32)
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for poly, poly_tag in zip(polys, tags):
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if poly_tag == True:
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continue
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# adjust point order for vertical poly
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poly = self.adjust_point(poly)
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# generate min_area_quad
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min_area_quad, center_point = self.gen_min_area_quad_from_poly(poly)
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min_area_quad_h = 0.5 * (np.linalg.norm(min_area_quad[0] - min_area_quad[3]) +
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np.linalg.norm(min_area_quad[1] - min_area_quad[2]))
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min_area_quad_w = 0.5 * (np.linalg.norm(min_area_quad[0] - min_area_quad[1]) +
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np.linalg.norm(min_area_quad[2] - min_area_quad[3]))
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# generate tcl map and text, 128 * 128
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tcl_poly = self.poly2tcl(poly, tcl_ratio)
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# generate poly_tv_xy_map
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for idx in range(4):
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cv2.fillPoly(poly_tv_xy_map[2 * idx],
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np.round(tcl_poly[np.newaxis, :, :]).astype(np.int32),
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float(min(max(min_area_quad[idx, 0], 0), w)))
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cv2.fillPoly(poly_tv_xy_map[2 * idx + 1],
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np.round(tcl_poly[np.newaxis, :, :]).astype(np.int32),
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float(min(max(min_area_quad[idx, 1], 0), h)))
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# generate poly_tc_xy_map
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for idx in range(2):
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cv2.fillPoly(poly_tc_xy_map[idx],
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np.round(tcl_poly[np.newaxis, :, :]).astype(np.int32), float(center_point[idx]))
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# generate poly_short_edge_map
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cv2.fillPoly(poly_short_edge_map,
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np.round(tcl_poly[np.newaxis, :, :]).astype(np.int32),
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float(max(min(min_area_quad_h, min_area_quad_w), 1.0)))
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# generate poly_mask and training_mask
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cv2.fillPoly(poly_mask, np.round(tcl_poly[np.newaxis, :, :]).astype(np.int32), 1)
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tvo_map *= poly_mask
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tvo_map[:8] -= poly_tv_xy_map
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tvo_map[-1] /= poly_short_edge_map
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tvo_map = tvo_map.transpose((1, 2, 0))
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tco_map *= poly_mask
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tco_map[:2] -= poly_tc_xy_map
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tco_map[-1] /= poly_short_edge_map
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tco_map = tco_map.transpose((1, 2, 0))
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return tvo_map, tco_map
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def adjust_point(self, poly):
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"""
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adjust point order.
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"""
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point_num = poly.shape[0]
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if point_num == 4:
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len_1 = np.linalg.norm(poly[0] - poly[1])
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len_2 = np.linalg.norm(poly[1] - poly[2])
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len_3 = np.linalg.norm(poly[2] - poly[3])
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len_4 = np.linalg.norm(poly[3] - poly[0])
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if (len_1 + len_3) * 1.5 < (len_2 + len_4):
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poly = poly[[1, 2, 3, 0], :]
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elif point_num > 4:
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vector_1 = poly[0] - poly[1]
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vector_2 = poly[1] - poly[2]
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cos_theta = np.dot(vector_1, vector_2) / (np.linalg.norm(vector_1) * np.linalg.norm(vector_2) + 1e-6)
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theta = np.arccos(np.round(cos_theta, decimals=4))
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if abs(theta) > (70 / 180 * math.pi):
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index = list(range(1, point_num)) + [0]
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poly = poly[np.array(index), :]
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return poly
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def gen_min_area_quad_from_poly(self, poly):
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"""
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Generate min area quad from poly.
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"""
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point_num = poly.shape[0]
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min_area_quad = np.zeros((4, 2), dtype=np.float32)
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if point_num == 4:
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min_area_quad = poly
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center_point = np.sum(poly, axis=0) / 4
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else:
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rect = cv2.minAreaRect(poly.astype(np.int32)) # (center (x,y), (width, height), angle of rotation)
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center_point = rect[0]
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box = np.array(cv2.boxPoints(rect))
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first_point_idx = 0
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min_dist = 1e4
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for i in range(4):
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dist = np.linalg.norm(box[(i + 0) % 4] - poly[0]) + \
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np.linalg.norm(box[(i + 1) % 4] - poly[point_num // 2 - 1]) + \
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np.linalg.norm(box[(i + 2) % 4] - poly[point_num // 2]) + \
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np.linalg.norm(box[(i + 3) % 4] - poly[-1])
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if dist < min_dist:
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min_dist = dist
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first_point_idx = i
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for i in range(4):
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min_area_quad[i] = box[(first_point_idx + i) % 4]
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return min_area_quad, center_point
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def shrink_quad_along_width(self, quad, begin_width_ratio=0., end_width_ratio=1.):
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"""
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Generate shrink_quad_along_width.
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"""
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ratio_pair = np.array([[begin_width_ratio], [end_width_ratio]], dtype=np.float32)
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p0_1 = quad[0] + (quad[1] - quad[0]) * ratio_pair
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p3_2 = quad[3] + (quad[2] - quad[3]) * ratio_pair
|
|
return np.array([p0_1[0], p0_1[1], p3_2[1], p3_2[0]])
|
|
|
|
def shrink_poly_along_width(self, quads, shrink_ratio_of_width, expand_height_ratio=1.0):
|
|
"""
|
|
shrink poly with given length.
|
|
"""
|
|
upper_edge_list = []
|
|
|
|
def get_cut_info(edge_len_list, cut_len):
|
|
for idx, edge_len in enumerate(edge_len_list):
|
|
cut_len -= edge_len
|
|
if cut_len <= 0.000001:
|
|
ratio = (cut_len + edge_len_list[idx]) / edge_len_list[idx]
|
|
return idx, ratio
|
|
|
|
for quad in quads:
|
|
upper_edge_len = np.linalg.norm(quad[0] - quad[1])
|
|
upper_edge_list.append(upper_edge_len)
|
|
|
|
# length of left edge and right edge.
|
|
left_length = np.linalg.norm(quads[0][0] - quads[0][3]) * expand_height_ratio
|
|
right_length = np.linalg.norm(quads[-1][1] - quads[-1][2]) * expand_height_ratio
|
|
|
|
shrink_length = min(left_length, right_length, sum(upper_edge_list)) * shrink_ratio_of_width
|
|
# shrinking length
|
|
upper_len_left = shrink_length
|
|
upper_len_right = sum(upper_edge_list) - shrink_length
|
|
|
|
left_idx, left_ratio = get_cut_info(upper_edge_list, upper_len_left)
|
|
left_quad = self.shrink_quad_along_width(quads[left_idx], begin_width_ratio=left_ratio, end_width_ratio=1)
|
|
right_idx, right_ratio = get_cut_info(upper_edge_list, upper_len_right)
|
|
right_quad = self.shrink_quad_along_width(quads[right_idx], begin_width_ratio=0, end_width_ratio=right_ratio)
|
|
|
|
out_quad_list = []
|
|
if left_idx == right_idx:
|
|
out_quad_list.append([left_quad[0], right_quad[1], right_quad[2], left_quad[3]])
|
|
else:
|
|
out_quad_list.append(left_quad)
|
|
for idx in range(left_idx + 1, right_idx):
|
|
out_quad_list.append(quads[idx])
|
|
out_quad_list.append(right_quad)
|
|
|
|
return np.array(out_quad_list), list(range(left_idx, right_idx + 1))
|
|
|
|
def vector_angle(self, A, B):
|
|
"""
|
|
Calculate the angle between vector AB and x-axis positive direction.
|
|
"""
|
|
AB = np.array([B[1] - A[1], B[0] - A[0]])
|
|
return np.arctan2(*AB)
|
|
|
|
def theta_line_cross_point(self, theta, point):
|
|
"""
|
|
Calculate the line through given point and angle in ax + by + c =0 form.
|
|
"""
|
|
x, y = point
|
|
cos = np.cos(theta)
|
|
sin = np.sin(theta)
|
|
return [sin, -cos, cos * y - sin * x]
|
|
|
|
def line_cross_two_point(self, A, B):
|
|
"""
|
|
Calculate the line through given point A and B in ax + by + c =0 form.
|
|
"""
|
|
angle = self.vector_angle(A, B)
|
|
return self.theta_line_cross_point(angle, A)
|
|
|
|
def average_angle(self, poly):
|
|
"""
|
|
Calculate the average angle between left and right edge in given poly.
|
|
"""
|
|
p0, p1, p2, p3 = poly
|
|
angle30 = self.vector_angle(p3, p0)
|
|
angle21 = self.vector_angle(p2, p1)
|
|
return (angle30 + angle21) / 2
|
|
|
|
def line_cross_point(self, line1, line2):
|
|
"""
|
|
line1 and line2 in 0=ax+by+c form, compute the cross point of line1 and line2
|
|
"""
|
|
a1, b1, c1 = line1
|
|
a2, b2, c2 = line2
|
|
d = a1 * b2 - a2 * b1
|
|
|
|
if d == 0:
|
|
#print("line1", line1)
|
|
#print("line2", line2)
|
|
print('Cross point does not exist')
|
|
return np.array([0, 0], dtype=np.float32)
|
|
else:
|
|
x = (b1 * c2 - b2 * c1) / d
|
|
y = (a2 * c1 - a1 * c2) / d
|
|
|
|
return np.array([x, y], dtype=np.float32)
|
|
|
|
def quad2tcl(self, poly, ratio):
|
|
"""
|
|
Generate center line by poly clock-wise point. (4, 2)
|
|
"""
|
|
ratio_pair = np.array([[0.5 - ratio / 2], [0.5 + ratio / 2]], dtype=np.float32)
|
|
p0_3 = poly[0] + (poly[3] - poly[0]) * ratio_pair
|
|
p1_2 = poly[1] + (poly[2] - poly[1]) * ratio_pair
|
|
return np.array([p0_3[0], p1_2[0], p1_2[1], p0_3[1]])
|
|
|
|
def poly2tcl(self, poly, ratio):
|
|
"""
|
|
Generate center line by poly clock-wise point.
|
|
"""
|
|
ratio_pair = np.array([[0.5 - ratio / 2], [0.5 + ratio / 2]], dtype=np.float32)
|
|
tcl_poly = np.zeros_like(poly)
|
|
point_num = poly.shape[0]
|
|
|
|
for idx in range(point_num // 2):
|
|
point_pair = poly[idx] + (poly[point_num - 1 - idx] - poly[idx]) * ratio_pair
|
|
tcl_poly[idx] = point_pair[0]
|
|
tcl_poly[point_num - 1 - idx] = point_pair[1]
|
|
return tcl_poly
|
|
|
|
def gen_quad_tbo(self, quad, tcl_mask, tbo_map):
|
|
"""
|
|
Generate tbo_map for give quad.
|
|
"""
|
|
# upper and lower line function: ax + by + c = 0;
|
|
up_line = self.line_cross_two_point(quad[0], quad[1])
|
|
lower_line = self.line_cross_two_point(quad[3], quad[2])
|
|
|
|
quad_h = 0.5 * (np.linalg.norm(quad[0] - quad[3]) + np.linalg.norm(quad[1] - quad[2]))
|
|
quad_w = 0.5 * (np.linalg.norm(quad[0] - quad[1]) + np.linalg.norm(quad[2] - quad[3]))
|
|
|
|
# average angle of left and right line.
|
|
angle = self.average_angle(quad)
|
|
|
|
xy_in_poly = np.argwhere(tcl_mask == 1)
|
|
for y, x in xy_in_poly:
|
|
point = (x, y)
|
|
line = self.theta_line_cross_point(angle, point)
|
|
cross_point_upper = self.line_cross_point(up_line, line)
|
|
cross_point_lower = self.line_cross_point(lower_line, line)
|
|
##FIX, offset reverse
|
|
upper_offset_x, upper_offset_y = cross_point_upper - point
|
|
lower_offset_x, lower_offset_y = cross_point_lower - point
|
|
tbo_map[y, x, 0] = upper_offset_y
|
|
tbo_map[y, x, 1] = upper_offset_x
|
|
tbo_map[y, x, 2] = lower_offset_y
|
|
tbo_map[y, x, 3] = lower_offset_x
|
|
tbo_map[y, x, 4] = 1.0 / max(min(quad_h, quad_w), 1.0) * 2
|
|
return tbo_map
|
|
|
|
def poly2quads(self, poly):
|
|
"""
|
|
Split poly into quads.
|
|
"""
|
|
quad_list = []
|
|
point_num = poly.shape[0]
|
|
|
|
# point pair
|
|
point_pair_list = []
|
|
for idx in range(point_num // 2):
|
|
point_pair = [poly[idx], poly[point_num - 1 - idx]]
|
|
point_pair_list.append(point_pair)
|
|
|
|
quad_num = point_num // 2 - 1
|
|
for idx in range(quad_num):
|
|
# reshape and adjust to clock-wise
|
|
quad_list.append((np.array(point_pair_list)[[idx, idx + 1]]).reshape(4, 2)[[0, 2, 3, 1]])
|
|
|
|
return np.array(quad_list)
|
|
|
|
def __call__(self, data):
|
|
im = data['image']
|
|
text_polys = data['polys']
|
|
text_tags = data['ignore_tags']
|
|
if im is None:
|
|
return None
|
|
if text_polys.shape[0] == 0:
|
|
return None
|
|
|
|
h, w, _ = im.shape
|
|
text_polys, text_tags, hv_tags = self.check_and_validate_polys(text_polys, text_tags, (h, w))
|
|
|
|
if text_polys.shape[0] == 0:
|
|
return None
|
|
|
|
#set aspect ratio and keep area fix
|
|
asp_scales = np.arange(1.0, 1.55, 0.1)
|
|
asp_scale = np.random.choice(asp_scales)
|
|
|
|
if np.random.rand() < 0.5:
|
|
asp_scale = 1.0 / asp_scale
|
|
asp_scale = math.sqrt(asp_scale)
|
|
|
|
asp_wx = asp_scale
|
|
asp_hy = 1.0 / asp_scale
|
|
im = cv2.resize(im, dsize=None, fx=asp_wx, fy=asp_hy)
|
|
text_polys[:, :, 0] *= asp_wx
|
|
text_polys[:, :, 1] *= asp_hy
|
|
|
|
h, w, _ = im.shape
|
|
if max(h, w) > 2048:
|
|
rd_scale = 2048.0 / max(h, w)
|
|
im = cv2.resize(im, dsize=None, fx=rd_scale, fy=rd_scale)
|
|
text_polys *= rd_scale
|
|
h, w, _ = im.shape
|
|
if min(h, w) < 16:
|
|
return None
|
|
|
|
#no background
|
|
im, text_polys, text_tags, hv_tags = self.crop_area(im, \
|
|
text_polys, text_tags, hv_tags, crop_background=False)
|
|
|
|
if text_polys.shape[0] == 0:
|
|
return None
|
|
#continue for all ignore case
|
|
if np.sum((text_tags * 1.0)) >= text_tags.size:
|
|
return None
|
|
new_h, new_w, _ = im.shape
|
|
if (new_h is None) or (new_w is None):
|
|
return None
|
|
#resize image
|
|
std_ratio = float(self.input_size) / max(new_w, new_h)
|
|
rand_scales = np.array([0.25, 0.375, 0.5, 0.625, 0.75, 0.875, 1.0, 1.0, 1.0, 1.0, 1.0])
|
|
rz_scale = std_ratio * np.random.choice(rand_scales)
|
|
im = cv2.resize(im, dsize=None, fx=rz_scale, fy=rz_scale)
|
|
text_polys[:, :, 0] *= rz_scale
|
|
text_polys[:, :, 1] *= rz_scale
|
|
|
|
#add gaussian blur
|
|
if np.random.rand() < 0.1 * 0.5:
|
|
ks = np.random.permutation(5)[0] + 1
|
|
ks = int(ks/2)*2 + 1
|
|
im = cv2.GaussianBlur(im, ksize=(ks, ks), sigmaX=0, sigmaY=0)
|
|
#add brighter
|
|
if np.random.rand() < 0.1 * 0.5:
|
|
im = im * (1.0 + np.random.rand() * 0.5)
|
|
im = np.clip(im, 0.0, 255.0)
|
|
#add darker
|
|
if np.random.rand() < 0.1 * 0.5:
|
|
im = im * (1.0 - np.random.rand() * 0.5)
|
|
im = np.clip(im, 0.0, 255.0)
|
|
|
|
# Padding the im to [input_size, input_size]
|
|
new_h, new_w, _ = im.shape
|
|
if min(new_w, new_h) < self.input_size * 0.5:
|
|
return None
|
|
|
|
im_padded = np.ones((self.input_size, self.input_size, 3), dtype=np.float32)
|
|
im_padded[:, :, 2] = 0.485 * 255
|
|
im_padded[:, :, 1] = 0.456 * 255
|
|
im_padded[:, :, 0] = 0.406 * 255
|
|
|
|
# Random the start position
|
|
del_h = self.input_size - new_h
|
|
del_w = self.input_size - new_w
|
|
sh, sw = 0, 0
|
|
if del_h > 1:
|
|
sh = int(np.random.rand() * del_h)
|
|
if del_w > 1:
|
|
sw = int(np.random.rand() * del_w)
|
|
|
|
# Padding
|
|
im_padded[sh: sh + new_h, sw: sw + new_w, :] = im.copy()
|
|
text_polys[:, :, 0] += sw
|
|
text_polys[:, :, 1] += sh
|
|
|
|
score_map, border_map, training_mask = self.generate_tcl_label((self.input_size, self.input_size),
|
|
text_polys, text_tags, 0.25)
|
|
|
|
# SAST head
|
|
tvo_map, tco_map = self.generate_tvo_and_tco((self.input_size, self.input_size), text_polys, text_tags, tcl_ratio=0.3, ds_ratio=0.25)
|
|
# print("test--------tvo_map shape:", tvo_map.shape)
|
|
|
|
im_padded[:, :, 2] -= 0.485 * 255
|
|
im_padded[:, :, 1] -= 0.456 * 255
|
|
im_padded[:, :, 0] -= 0.406 * 255
|
|
im_padded[:, :, 2] /= (255.0 * 0.229)
|
|
im_padded[:, :, 1] /= (255.0 * 0.224)
|
|
im_padded[:, :, 0] /= (255.0 * 0.225)
|
|
im_padded = im_padded.transpose((2, 0, 1))
|
|
|
|
data['image'] = im_padded[::-1, :, :]
|
|
data['score_map'] = score_map[np.newaxis, :, :]
|
|
data['border_map'] = border_map.transpose((2, 0, 1))
|
|
data['training_mask'] = training_mask[np.newaxis, :, :]
|
|
data['tvo_map'] = tvo_map.transpose((2, 0, 1))
|
|
data['tco_map'] = tco_map.transpose((2, 0, 1))
|
|
return data |