mirror of
https://github.com/PaddlePaddle/PaddleOCR.git
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203 lines
7.6 KiB
Python
203 lines
7.6 KiB
Python
# copyright (c) 2021 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 copy
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import cv2
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import random
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import numpy as np
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from PIL import Image
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from shapely.geometry import Polygon
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from ppocr.data.imaug.iaa_augment import IaaAugment
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from ppocr.data.imaug.random_crop_data import is_poly_outside_rect
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def get_rotate_crop_image(img, points):
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'''
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img_height, img_width = img.shape[0:2]
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left = int(np.min(points[:, 0]))
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right = int(np.max(points[:, 0]))
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top = int(np.min(points[:, 1]))
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bottom = int(np.max(points[:, 1]))
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img_crop = img[top:bottom, left:right, :].copy()
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points[:, 0] = points[:, 0] - left
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points[:, 1] = points[:, 1] - top
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'''
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img_crop_width = int(
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max(
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np.linalg.norm(points[0] - points[1]),
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np.linalg.norm(points[2] - points[3])))
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img_crop_height = int(
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max(
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np.linalg.norm(points[0] - points[3]),
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np.linalg.norm(points[1] - points[2])))
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pts_std = np.float32([[0, 0], [img_crop_width, 0],
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[img_crop_width, img_crop_height],
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[0, img_crop_height]])
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M = cv2.getPerspectiveTransform(points, pts_std)
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dst_img = cv2.warpPerspective(
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img,
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M, (img_crop_width, img_crop_height),
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borderMode=cv2.BORDER_REPLICATE,
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flags=cv2.INTER_CUBIC)
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dst_img_height, dst_img_width = dst_img.shape[0:2]
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if dst_img_height * 1.0 / dst_img_width >= 1.5:
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dst_img = np.rot90(dst_img)
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return dst_img
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class CopyPaste(object):
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def __init__(self, objects_paste_ratio=0.2, limit_paste=True, **kwargs):
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self.ext_data_num = 1
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self.objects_paste_ratio = objects_paste_ratio
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self.limit_paste = limit_paste
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augmenter_args = [{'type': 'Resize', 'args': {'size': [0.5, 3]}}]
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self.aug = IaaAugment(augmenter_args)
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def __call__(self, data):
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src_img = data['image']
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src_polys = data['polys'].tolist()
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src_ignores = data['ignore_tags'].tolist()
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ext_data = data['ext_data'][0]
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ext_image = ext_data['image']
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ext_polys = ext_data['polys']
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ext_ignores = ext_data['ignore_tags']
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indexs = [i for i in range(len(ext_ignores)) if not ext_ignores[i]]
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select_num = max(
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1, min(int(self.objects_paste_ratio * len(ext_polys)), 30))
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random.shuffle(indexs)
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select_idxs = indexs[:select_num]
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select_polys = ext_polys[select_idxs]
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select_ignores = ext_ignores[select_idxs]
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src_img = cv2.cvtColor(src_img, cv2.COLOR_BGR2RGB)
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ext_image = cv2.cvtColor(ext_image, cv2.COLOR_BGR2RGB)
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src_img = Image.fromarray(src_img).convert('RGBA')
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for poly, tag in zip(select_polys, select_ignores):
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box_img = get_rotate_crop_image(ext_image, poly)
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src_img, box = self.paste_img(src_img, box_img, src_polys)
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if box is not None:
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src_polys.append(box)
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src_ignores.append(tag)
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src_img = cv2.cvtColor(np.array(src_img), cv2.COLOR_RGB2BGR)
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h, w = src_img.shape[:2]
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src_polys = np.array(src_polys)
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src_polys[:, :, 0] = np.clip(src_polys[:, :, 0], 0, w)
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src_polys[:, :, 1] = np.clip(src_polys[:, :, 1], 0, h)
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data['image'] = src_img
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data['polys'] = src_polys
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data['ignore_tags'] = np.array(src_ignores)
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return data
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def paste_img(self, src_img, box_img, src_polys):
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box_img_pil = Image.fromarray(box_img).convert('RGBA')
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src_w, src_h = src_img.size
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box_w, box_h = box_img_pil.size
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if box_w > src_w or box_h > src_h:
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return src_img, None
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angle = np.random.randint(0, 360)
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box = np.array([[[0, 0], [box_w, 0], [box_w, box_h], [0, box_h]]])
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box = rotate_bbox(box_img, box, angle)[0]
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paste_x, paste_y = self.select_coord(src_polys, box, src_w - box_w,
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src_h - box_h)
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if paste_x is None:
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return src_img, None
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box[:, 0] += paste_x
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box[:, 1] += paste_y
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box_img_pil = box_img_pil.rotate(angle, expand=1)
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r, g, b, A = box_img_pil.split()
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src_img.paste(box_img_pil, (paste_x, paste_y), mask=A)
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return src_img, box
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def select_coord(self, src_polys, box, endx, endy):
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if self.limit_paste:
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xmin, ymin, xmax, ymax = box[:, 0].min(), box[:, 1].min(
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), box[:, 0].max(), box[:, 1].max()
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for _ in range(50):
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paste_x = random.randint(0, endx)
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paste_y = random.randint(0, endy)
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xmin1 = xmin + paste_x
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xmax1 = xmax + paste_x
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ymin1 = ymin + paste_y
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ymax1 = ymax + paste_y
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num_poly_in_rect = 0
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for poly in src_polys:
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if not is_poly_outside_rect(poly, xmax1, ymin1,
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xmax1 - xmin1, ymax1 - ymin1):
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num_poly_in_rect += 1
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break
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if num_poly_in_rect == 0:
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return paste_x, paste_y
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return None, None
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else:
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paste_x = random.randint(0, endx)
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paste_y = random.randint(0, endy)
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return paste_x, paste_y
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def get_union(pD, pG):
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return Polygon(pD).union(Polygon(pG)).area
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def get_intersection_over_union(pD, pG):
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return get_intersection(pD, pG) / get_union(pD, pG)
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def get_intersection(pD, pG):
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return Polygon(pD).intersection(Polygon(pG)).area
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def rotate_bbox(img, text_polys, angle, scale=1):
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"""
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从给定的角度中选择一个角度，对图片和文本框进行旋转
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:param img: 图片
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:param text_polys: 文本框
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:param degrees: 角度，可以是一个数值或者list
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:param same_size: 是否保持和原图一样大
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:return: 旋转后的图片和角度
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"""
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# ---------------------- 旋转图像 ----------------------
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w = img.shape[1]
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h = img.shape[0]
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# 角度变弧度
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rangle = np.deg2rad(angle)
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# 计算旋转之后图像的w, h
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nw = (abs(np.sin(rangle) * h) + abs(np.cos(rangle) * w))
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nh = (abs(np.cos(rangle) * h) + abs(np.sin(rangle) * w))
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# 构造仿射矩阵
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rot_mat = cv2.getRotationMatrix2D((nw * 0.5, nh * 0.5), angle, scale)
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# 计算原图中心点到新图中心点的偏移量
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rot_move = np.dot(rot_mat, np.array([(nw - w) * 0.5, (nh - h) * 0.5, 0]))
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# 更新仿射矩阵
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rot_mat[0, 2] += rot_move[0]
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rot_mat[1, 2] += rot_move[1]
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# ---------------------- 矫正bbox坐标 ----------------------
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# rot_mat是最终的旋转矩阵
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# 获取原始bbox的四个中点，然后将这四个点转换到旋转后的坐标系下
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rot_text_polys = list()
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for bbox in text_polys:
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point1 = np.dot(rot_mat, np.array([bbox[0, 0], bbox[0, 1], 1]))
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point2 = np.dot(rot_mat, np.array([bbox[1, 0], bbox[1, 1], 1]))
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point3 = np.dot(rot_mat, np.array([bbox[2, 0], bbox[2, 1], 1]))
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point4 = np.dot(rot_mat, np.array([bbox[3, 0], bbox[3, 1], 1]))
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rot_text_polys.append([point1, point2, point3, point4])
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return np.array(rot_text_polys, dtype=np.float32)
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