From fe92c51c42dae7f8db2d7332dc4eaa40ef8b5fe4 Mon Sep 17 00:00:00 2001 From: WenmuZhou Date: Thu, 4 Nov 2021 18:23:23 +0800 Subject: [PATCH] add refer for some code --- ppocr/data/imaug/iaa_augment.py | 17 +-- ppocr/data/imaug/make_border_map.py | 4 + ppocr/data/imaug/make_pse_gt.py | 30 ++++-- ppocr/data/imaug/make_shrink_map.py | 4 + ppocr/data/imaug/random_crop_data.py | 4 + ppocr/data/imaug/text_image_aug/augment.py | 17 +-- ppocr/data/imaug/text_image_aug/warp_mls.py | 17 +-- ppocr/losses/det_pse_loss.py | 17 +-- ppocr/modeling/heads/det_pse_head.py | 31 ++---- ppocr/modeling/necks/fpn.py | 101 +++++++++++------- .../postprocess/pse_postprocess/pse/README.md | 3 +- .../pse_postprocess/pse_postprocess.py | 33 +++--- ppocr/utils/iou.py | 25 ++--- ppocr/utils/logging.py | 17 +-- 14 files changed, 151 insertions(+), 169 deletions(-) diff --git a/ppocr/data/imaug/iaa_augment.py b/ppocr/data/imaug/iaa_augment.py index 9ce6bd42..e9a1fa06 100644 --- a/ppocr/data/imaug/iaa_augment.py +++ b/ppocr/data/imaug/iaa_augment.py @@ -1,16 +1,7 @@ -# 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/iaa_augment.py +""" from __future__ import absolute_import from __future__ import division from __future__ import print_function diff --git a/ppocr/data/imaug/make_border_map.py b/ppocr/data/imaug/make_border_map.py index cc2c9034..44110ff3 100644 --- a/ppocr/data/imaug/make_border_map.py +++ b/ppocr/data/imaug/make_border_map.py @@ -1,4 +1,8 @@ # -*- coding:utf-8 -*- +""" +This code is refer from: +https://github.com/WenmuZhou/DBNet.pytorch/blob/master/data_loader/modules/make_border_map.py +""" from __future__ import absolute_import from __future__ import division diff --git a/ppocr/data/imaug/make_pse_gt.py b/ppocr/data/imaug/make_pse_gt.py index 55abc897..d1e2b1c5 100644 --- a/ppocr/data/imaug/make_pse_gt.py +++ b/ppocr/data/imaug/make_pse_gt.py @@ -12,6 +12,7 @@ from shapely.geometry import Polygon __all__ = ['MakePseGt'] + class MakePseGt(object): r''' Making binary mask from detection data with ICDAR format. @@ -38,16 +39,20 @@ class MakePseGt(object): text_polys *= scale gt_kernels = [] - for i in range(1,self.kernel_num+1): + for i in range(1, self.kernel_num + 1): # s1->sn, from big to small - rate = 1.0 - (1.0 - self.min_shrink_ratio) / (self.kernel_num - 1) * i - text_kernel, ignore_tags = self.generate_kernel(image.shape[0:2], rate, text_polys, ignore_tags) + rate = 1.0 - (1.0 - self.min_shrink_ratio) / (self.kernel_num - 1 + ) * i + text_kernel, ignore_tags = self.generate_kernel( + image.shape[0:2], rate, text_polys, ignore_tags) gt_kernels.append(text_kernel) training_mask = np.ones(image.shape[0:2], dtype='uint8') for i in range(text_polys.shape[0]): if ignore_tags[i]: - cv2.fillPoly(training_mask, text_polys[i].astype(np.int32)[np.newaxis, :, :], 0) + cv2.fillPoly(training_mask, + text_polys[i].astype(np.int32)[np.newaxis, :, :], + 0) gt_kernels = np.array(gt_kernels) gt_kernels[gt_kernels > 0] = 1 @@ -59,16 +64,25 @@ class MakePseGt(object): data['mask'] = training_mask.astype('float32') return data - def generate_kernel(self, img_size, shrink_ratio, text_polys, ignore_tags=None): + def generate_kernel(self, + img_size, + shrink_ratio, + text_polys, + ignore_tags=None): + """ + Refer to part of the code: + https://github.com/open-mmlab/mmocr/blob/main/mmocr/datasets/pipelines/textdet_targets/base_textdet_targets.py + """ + h, w = img_size text_kernel = np.zeros((h, w), dtype=np.float32) for i, poly in enumerate(text_polys): polygon = Polygon(poly) - distance = polygon.area * (1 - shrink_ratio * shrink_ratio) / (polygon.length + 1e-6) + distance = polygon.area * (1 - shrink_ratio * shrink_ratio) / ( + polygon.length + 1e-6) subject = [tuple(l) for l in poly] pco = pyclipper.PyclipperOffset() - pco.AddPath(subject, pyclipper.JT_ROUND, - pyclipper.ET_CLOSEDPOLYGON) + pco.AddPath(subject, pyclipper.JT_ROUND, pyclipper.ET_CLOSEDPOLYGON) shrinked = np.array(pco.Execute(-distance)) if len(shrinked) == 0 or shrinked.size == 0: diff --git a/ppocr/data/imaug/make_shrink_map.py b/ppocr/data/imaug/make_shrink_map.py index 15e8afa0..78171268 100644 --- a/ppocr/data/imaug/make_shrink_map.py +++ b/ppocr/data/imaug/make_shrink_map.py @@ -1,4 +1,8 @@ # -*- coding:utf-8 -*- +""" +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 diff --git a/ppocr/data/imaug/random_crop_data.py b/ppocr/data/imaug/random_crop_data.py index 7c1c25ab..507695ff 100644 --- a/ppocr/data/imaug/random_crop_data.py +++ b/ppocr/data/imaug/random_crop_data.py @@ -1,4 +1,8 @@ # -*- coding:utf-8 -*- +""" +This code is refer from: +https://github.com/WenmuZhou/DBNet.pytorch/blob/master/data_loader/modules/random_crop_data.py +""" from __future__ import absolute_import from __future__ import division diff --git a/ppocr/data/imaug/text_image_aug/augment.py b/ppocr/data/imaug/text_image_aug/augment.py index 1aeff373..eb2c7f12 100644 --- a/ppocr/data/imaug/text_image_aug/augment.py +++ b/ppocr/data/imaug/text_image_aug/augment.py @@ -1,16 +1,7 @@ -# 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/RubanSeven/Text-Image-Augmentation-python/blob/master/augment.py +""" import numpy as np from .warp_mls import WarpMLS diff --git a/ppocr/data/imaug/text_image_aug/warp_mls.py b/ppocr/data/imaug/text_image_aug/warp_mls.py index d6cbe749..e6ab7337 100644 --- a/ppocr/data/imaug/text_image_aug/warp_mls.py +++ b/ppocr/data/imaug/text_image_aug/warp_mls.py @@ -1,16 +1,7 @@ -# 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/RubanSeven/Text-Image-Augmentation-python/blob/master/warp_mls.py +""" import numpy as np diff --git a/ppocr/losses/det_pse_loss.py b/ppocr/losses/det_pse_loss.py index 78423091..6beea8d8 100644 --- a/ppocr/losses/det_pse_loss.py +++ b/ppocr/losses/det_pse_loss.py @@ -1,16 +1,7 @@ -# copyright (c) 2021 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/whai362/PSENet/blob/python3/models/head/psenet_head.py +""" import paddle from paddle import nn diff --git a/ppocr/modeling/heads/det_pse_head.py b/ppocr/modeling/heads/det_pse_head.py index db800f57..9ac1e795 100644 --- a/ppocr/modeling/heads/det_pse_head.py +++ b/ppocr/modeling/heads/det_pse_head.py @@ -1,32 +1,21 @@ -# 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/whai362/PSENet/blob/python3/models/head/psenet_head.py +""" + from paddle import nn class PSEHead(nn.Layer): - def __init__(self, - in_channels, - hidden_dim=256, - out_channels=7, - **kwargs): + def __init__(self, in_channels, hidden_dim=256, out_channels=7, **kwargs): super(PSEHead, self).__init__() - self.conv1 = nn.Conv2D(in_channels, hidden_dim, kernel_size=3, stride=1, padding=1) + self.conv1 = nn.Conv2D( + in_channels, hidden_dim, kernel_size=3, stride=1, padding=1) self.bn1 = nn.BatchNorm2D(hidden_dim) self.relu1 = nn.ReLU() - self.conv2 = nn.Conv2D(hidden_dim, out_channels, kernel_size=1, stride=1, padding=0) - + self.conv2 = nn.Conv2D( + hidden_dim, out_channels, kernel_size=1, stride=1, padding=0) def forward(self, x, **kwargs): out = self.conv1(x) diff --git a/ppocr/modeling/necks/fpn.py b/ppocr/modeling/necks/fpn.py index 8728a5c9..9d69a4c1 100644 --- a/ppocr/modeling/necks/fpn.py +++ b/ppocr/modeling/necks/fpn.py @@ -1,74 +1,99 @@ -# copyright (c) 2021 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/whai362/PSENet/blob/python3/models/neck/fpn.py +""" import paddle.nn as nn import paddle import math import paddle.nn.functional as F + class Conv_BN_ReLU(nn.Layer): - def __init__(self, in_planes, out_planes, kernel_size=1, stride=1, padding=0): + def __init__(self, + in_planes, + out_planes, + kernel_size=1, + stride=1, + padding=0): super(Conv_BN_ReLU, self).__init__() - self.conv = nn.Conv2D(in_planes, out_planes, kernel_size=kernel_size, stride=stride, padding=padding, - bias_attr=False) + self.conv = nn.Conv2D( + in_planes, + out_planes, + kernel_size=kernel_size, + stride=stride, + padding=padding, + bias_attr=False) self.bn = nn.BatchNorm2D(out_planes, momentum=0.1) self.relu = nn.ReLU() for m in self.sublayers(): if isinstance(m, nn.Conv2D): n = m._kernel_size[0] * m._kernel_size[1] * m._out_channels - m.weight = paddle.create_parameter(shape=m.weight.shape, dtype='float32', default_initializer=paddle.nn.initializer.Normal(0, math.sqrt(2. / n))) + m.weight = paddle.create_parameter( + shape=m.weight.shape, + dtype='float32', + default_initializer=paddle.nn.initializer.Normal( + 0, math.sqrt(2. / n))) elif isinstance(m, nn.BatchNorm2D): - m.weight = paddle.create_parameter(shape=m.weight.shape, dtype='float32', default_initializer=paddle.nn.initializer.Constant(1.0)) - m.bias = paddle.create_parameter(shape=m.bias.shape, dtype='float32', default_initializer=paddle.nn.initializer.Constant(0.0)) + m.weight = paddle.create_parameter( + shape=m.weight.shape, + dtype='float32', + default_initializer=paddle.nn.initializer.Constant(1.0)) + m.bias = paddle.create_parameter( + shape=m.bias.shape, + dtype='float32', + default_initializer=paddle.nn.initializer.Constant(0.0)) def forward(self, x): return self.relu(self.bn(self.conv(x))) + class FPN(nn.Layer): def __init__(self, in_channels, out_channels): super(FPN, self).__init__() # Top layer - self.toplayer_ = Conv_BN_ReLU(in_channels[3], out_channels, kernel_size=1, stride=1, padding=0) + self.toplayer_ = Conv_BN_ReLU( + in_channels[3], out_channels, kernel_size=1, stride=1, padding=0) # Lateral layers - self.latlayer1_ = Conv_BN_ReLU(in_channels[2], out_channels, kernel_size=1, stride=1, padding=0) + self.latlayer1_ = Conv_BN_ReLU( + in_channels[2], out_channels, kernel_size=1, stride=1, padding=0) - self.latlayer2_ = Conv_BN_ReLU(in_channels[1], out_channels, kernel_size=1, stride=1, padding=0) + self.latlayer2_ = Conv_BN_ReLU( + in_channels[1], out_channels, kernel_size=1, stride=1, padding=0) - self.latlayer3_ = Conv_BN_ReLU(in_channels[0], out_channels, kernel_size=1, stride=1, padding=0) + self.latlayer3_ = Conv_BN_ReLU( + in_channels[0], out_channels, kernel_size=1, stride=1, padding=0) # Smooth layers - self.smooth1_ = Conv_BN_ReLU(out_channels, out_channels, kernel_size=3, stride=1, padding=1) - - self.smooth2_ = Conv_BN_ReLU(out_channels, out_channels, kernel_size=3, stride=1, padding=1) + self.smooth1_ = Conv_BN_ReLU( + out_channels, out_channels, kernel_size=3, stride=1, padding=1) - self.smooth3_ = Conv_BN_ReLU(out_channels, out_channels, kernel_size=3, stride=1, padding=1) + self.smooth2_ = Conv_BN_ReLU( + out_channels, out_channels, kernel_size=3, stride=1, padding=1) + self.smooth3_ = Conv_BN_ReLU( + out_channels, out_channels, kernel_size=3, stride=1, padding=1) self.out_channels = out_channels * 4 for m in self.sublayers(): if isinstance(m, nn.Conv2D): n = m._kernel_size[0] * m._kernel_size[1] * m._out_channels - m.weight = paddle.create_parameter(shape=m.weight.shape, dtype='float32', - default_initializer=paddle.nn.initializer.Normal(0, - math.sqrt(2. / n))) + m.weight = paddle.create_parameter( + shape=m.weight.shape, + dtype='float32', + default_initializer=paddle.nn.initializer.Normal( + 0, math.sqrt(2. / n))) elif isinstance(m, nn.BatchNorm2D): - m.weight = paddle.create_parameter(shape=m.weight.shape, dtype='float32', - default_initializer=paddle.nn.initializer.Constant(1.0)) - m.bias = paddle.create_parameter(shape=m.bias.shape, dtype='float32', - default_initializer=paddle.nn.initializer.Constant(0.0)) + m.weight = paddle.create_parameter( + shape=m.weight.shape, + dtype='float32', + default_initializer=paddle.nn.initializer.Constant(1.0)) + m.bias = paddle.create_parameter( + shape=m.bias.shape, + dtype='float32', + default_initializer=paddle.nn.initializer.Constant(0.0)) def _upsample(self, x, scale=1): return F.upsample(x, scale_factor=scale, mode='bilinear') @@ -81,15 +106,15 @@ class FPN(nn.Layer): p5 = self.toplayer_(f5) f4 = self.latlayer1_(f4) - p4 = self._upsample_add(p5, f4,2) + p4 = self._upsample_add(p5, f4, 2) p4 = self.smooth1_(p4) f3 = self.latlayer2_(f3) - p3 = self._upsample_add(p4, f3,2) + p3 = self._upsample_add(p4, f3, 2) p3 = self.smooth2_(p3) f2 = self.latlayer3_(f2) - p2 = self._upsample_add(p3, f2,2) + p2 = self._upsample_add(p3, f2, 2) p2 = self.smooth3_(p2) p3 = self._upsample(p3, 2) @@ -97,4 +122,4 @@ class FPN(nn.Layer): p5 = self._upsample(p5, 8) fuse = paddle.concat([p2, p3, p4, p5], axis=1) - return fuse \ No newline at end of file + return fuse diff --git a/ppocr/postprocess/pse_postprocess/pse/README.md b/ppocr/postprocess/pse_postprocess/pse/README.md index 9c2d9eae..6a19d5d1 100644 --- a/ppocr/postprocess/pse_postprocess/pse/README.md +++ b/ppocr/postprocess/pse_postprocess/pse/README.md @@ -1,5 +1,6 @@ ## 编译 -code from https://github.com/whai362/pan_pp.pytorch +This code is refer from: +https://github.com/whai362/PSENet/blob/python3/models/post_processing/pse ```python python3 setup.py build_ext --inplace ``` diff --git a/ppocr/postprocess/pse_postprocess/pse_postprocess.py b/ppocr/postprocess/pse_postprocess/pse_postprocess.py index 4b89d221..d86af2e5 100755 --- a/ppocr/postprocess/pse_postprocess/pse_postprocess.py +++ b/ppocr/postprocess/pse_postprocess/pse_postprocess.py @@ -1,16 +1,7 @@ -# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. -# -# 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/whai362/PSENet/blob/python3/models/head/psenet_head.py +""" from __future__ import absolute_import from __future__ import division @@ -47,7 +38,8 @@ class PSEPostProcess(object): pred = outs_dict['maps'] if not isinstance(pred, paddle.Tensor): pred = paddle.to_tensor(pred) - pred = F.interpolate(pred, scale_factor=4 // self.scale, mode='bilinear') + pred = F.interpolate( + pred, scale_factor=4 // self.scale, mode='bilinear') score = F.sigmoid(pred[:, 0, :, :]) @@ -60,7 +52,9 @@ class PSEPostProcess(object): boxes_batch = [] for batch_index in range(pred.shape[0]): - boxes, scores = self.boxes_from_bitmap(score[batch_index], kernels[batch_index], shape_list[batch_index]) + boxes, scores = self.boxes_from_bitmap(score[batch_index], + kernels[batch_index], + shape_list[batch_index]) boxes_batch.append({'points': boxes, 'scores': scores}) return boxes_batch @@ -98,15 +92,14 @@ class PSEPostProcess(object): mask = np.zeros((box_height, box_width), np.uint8) mask[points[:, 1], points[:, 0]] = 255 - contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) + contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, + cv2.CHAIN_APPROX_SIMPLE) bbox = np.squeeze(contours[0], 1) else: raise NotImplementedError - bbox[:, 0] = np.clip( - np.round(bbox[:, 0] / ratio_w), 0, src_w) - bbox[:, 1] = np.clip( - np.round(bbox[:, 1] / ratio_h), 0, src_h) + bbox[:, 0] = np.clip(np.round(bbox[:, 0] / ratio_w), 0, src_w) + bbox[:, 1] = np.clip(np.round(bbox[:, 1] / ratio_h), 0, src_h) boxes.append(bbox) scores.append(score_i) return boxes, scores diff --git a/ppocr/utils/iou.py b/ppocr/utils/iou.py index 20529dee..80d15df0 100644 --- a/ppocr/utils/iou.py +++ b/ppocr/utils/iou.py @@ -1,28 +1,20 @@ -# 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/whai362/PSENet/blob/python3/models/loss/iou.py +""" import paddle EPS = 1e-6 + def iou_single(a, b, mask, n_class): valid = mask == 1 a = a.masked_select(valid) b = b.masked_select(valid) miou = [] for i in range(n_class): - if a.shape == [0] and a.shape==b.shape: + if a.shape == [0] and a.shape == b.shape: inter = paddle.to_tensor(0.0) union = paddle.to_tensor(0.0) else: @@ -32,6 +24,7 @@ def iou_single(a, b, mask, n_class): miou = sum(miou) / len(miou) return miou + def iou(a, b, mask, n_class=2, reduce=True): batch_size = a.shape[0] @@ -39,10 +32,10 @@ def iou(a, b, mask, n_class=2, reduce=True): b = b.reshape([batch_size, -1]) mask = mask.reshape([batch_size, -1]) - iou = paddle.zeros((batch_size,), dtype='float32') + iou = paddle.zeros((batch_size, ), dtype='float32') for i in range(batch_size): iou[i] = iou_single(a[i], b[i], mask[i], n_class) if reduce: iou = paddle.mean(iou) - return iou \ No newline at end of file + return iou diff --git a/ppocr/utils/logging.py b/ppocr/utils/logging.py index 11896c37..e30eee68 100644 --- a/ppocr/utils/logging.py +++ b/ppocr/utils/logging.py @@ -1,16 +1,7 @@ -# 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/PytorchOCR/blob/master/torchocr/utils/logging.py +""" import os import sys -- GitLab