update can transform method and add copyright info for new file

configs/rec/rec_d28_can.yml

@@ -42,7 +42,6 @@ Architecture:
  bottleneck: True
  use_dropout: True
  input_channel: 1 
-
  Head:
  name: CANHead
  in_channel: 684
@@ -66,24 +65,27 @@ Loss:
  name: CANLoss
 
 PostProcess:
- name: SeqLabelDecode
- character: 111
+ name: CANLabelDecode
+ character_dict_path: ppocr/utils/dict/latex_symbol_dict.txt
 
 Metric:
  name: CANMetric
  main_indicator: exp_rate
 
 Train:
  dataset:
- name: PGDataSet
+ name: SimpleDataSet
  data_dir: ./train_data/CROHME/training/images/
  transforms:
  - DecodeImage:
  channel_first: False
+ - NormalizeImage:
+ mean: [0,0,0]
+ std: [1,1,1]
+ order: 'hwc'
  - GrayImageChannelFormat: 
- normalize: True
  inverse: True
- - SeqLabelEncode:
+ - CANLabelEncode:
  character_dict_path: ppocr/utils/dict/latex_symbol_dict.txt
  lower: False
  - KeepKeys:
@@ -98,15 +100,18 @@ Train:
 
 Eval:
  dataset:
- name: PGDataSet
+ name: SimpleDataSet
  data_dir: ./train_data/CROHME/evaluation/images/
  transforms: 
  - DecodeImage:
  channel_first: False
+ - NormalizeImage:
+ mean: [0,0,0]
+ std: [1,1,1]
+ order: 'hwc'
  - GrayImageChannelFormat:
- normalize: True
  inverse: True
- - SeqLabelEncode:
+ - CANLabelEncode:
  character_dict_path: ppocr/utils/dict/latex_symbol_dict.txt
  lower: False
  - KeepKeys:

ppocr/data/imaug/__init__.py

@@ -27,7 +27,7 @@
 from .rec_img_aug import BaseDataAugmentation, RecAug, RecConAug, RecResizeImg, ClsResizeImg, \
  SRNRecResizeImg, GrayRecResizeImg, SARRecResizeImg, PRENResizeImg, \
  ABINetRecResizeImg, SVTRRecResizeImg, ABINetRecAug, VLRecResizeImg, SPINRecResizeImg, RobustScannerRecResizeImg, \
- RFLRecResizeImg, GrayImageChannelFormat
+ RFLRecResizeImg
 from .ssl_img_aug import SSLRotateResize
 from .randaugment import RandAugment
 from .copy_paste import CopyPaste

ppocr/data/imaug/label_ops.py

@@ -1479,14 +1479,14 @@ def __call__(self, data):
  return data
 
 
-class SeqLabelEncode(BaseRecLabelEncode):
+class CANLabelEncode(BaseRecLabelEncode):
  def __init__(self,
  character_dict_path,
  max_text_length=100,
  use_space_char=False,
  lower=True,
  **kwargs):
- super(SeqLabelEncode, self).__init__(
+ super(CANLabelEncode, self).__init__(
  max_text_length, character_dict_path, use_space_char, lower)
 
  def encode(self, text_seq):

ppocr/data/imaug/operators.py

@@ -498,3 +498,27 @@ def __call__(self, img):
  img_numpy = np.array(img).astype("float32")
  img_numpy = img_numpy.transpose((2, 0, 1)) / 255
  return img_numpy
+
+
+class GrayImageChannelFormat(object):
+ """
+ format gray scale image's channel: (3,h,w) -> (1,h,w)
+ Args:
+ inverse: inverse gray image 
+ """
+
+ def __init__(self, inverse=False, **kwargs):
+ self.inverse = inverse
+
+ def __call__(self, data):
+ img = data['image']
+ img_single_channel = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+ img_expanded = np.expand_dims(img_single_channel, 0)
+
+ if self.inverse:
+ data['image'] = np.abs(img_expanded - 1)
+ else:
+ data['image'] = img_expanded
+
+ data['src_image'] = img
+ return data

ppocr/data/imaug/rec_img_aug.py

@@ -465,36 +465,6 @@ def __call__(self, data):
  return data
 
 
-class GrayImageChannelFormat(object):
- """
- format gray scale image's channel: (3,h,w) -> (1,h,w)
- Args:
- normalize: True/False 
- when True convert image dynamic range [0,255]->[0,1]
- inverse: inverse gray image 
- """
-
- def __init__(self, normalize=True, inverse=False, **kwargs):
- self.normalize = normalize
- self.inverse = inverse
-
- def __call__(self, data):
- img = data['image']
- img_single_channel = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
- img_single_channel = np.expand_dims(img_single_channel, 0)
-
- if self.normalize:
- img_single_channel = img_single_channel / 255.0
-
- if self.inverse:
- data['image'] = np.abs(img_single_channel - 1).astype('float32')
- else:
- data['image'] = img_single_channel.astype('float32')
-
- data['src_image'] = img
- return data
-
-
 def resize_norm_img_sar(img, image_shape, width_downsample_ratio=0.25):
  imgC, imgH, imgW_min, imgW_max = image_shape
  h = img.shape[0]

ppocr/losses/rec_can_loss.py

@@ -1,3 +1,21 @@
+# 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:https://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/LBH1024/CAN/models/can.py
+"""
+
 import paddle
 import paddle.nn as nn
 import numpy as np

ppocr/modeling/backbones/rec_densenet.py

@@ -1,18 +1,28 @@
+# 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:https://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.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import math
 import paddle
 import paddle.nn as nn
 import paddle.nn.functional as F
 
 
 class Bottleneck(nn.Layer):
- '''
- ratio: 16
- growthRate: 24
- reduction: 0.5
- bottleneck: True
- use_dropout: True
- '''
-
  def __init__(self, nChannels, growthRate, use_dropout):
  super(Bottleneck, self).__init__()
  interChannels = 4 * growthRate
@@ -78,11 +88,7 @@ class DenseNet(nn.Layer):
  def __init__(self, growthRate, reduction, bottleneck, use_dropout,
  input_channel, **kwargs):
  super(DenseNet, self).__init__()
- '''
- ratio: 16
- growthRate: 24
- reduction: 0.5
- '''
+
  nDenseBlocks = 16
  nChannels = 2 * growthRate
 

ppocr/modeling/heads/rec_can_head.py

@@ -1,4 +1,29 @@
-from turtle import forward
+# copyright (c) 2019 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:https://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/LBH1024/CAN/models/can.py
+https://github.com/LBH1024/CAN/models/counting.py
+https://github.com/LBH1024/CAN/models/decoder.py
+https://github.com/LBH1024/CAN/models/attention.py
+
+"""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import paddle.nn as nn
 import paddle
 import math

ppocr/postprocess/__init__.py

@@ -37,7 +37,7 @@
 from .picodet_postprocess import PicoDetPostProcess
 from .ct_postprocess import CTPostProcess
 from .drrg_postprocess import DRRGPostprocess
-from .rec_postprocess import SeqLabelDecode
+from .rec_postprocess import CANLabelDecode
 
 
 def build_post_process(config, global_config=None):
@@ -52,7 +52,7 @@ def build_post_process(config, global_config=None):
  'TableMasterLabelDecode', 'SPINLabelDecode',
  'DistillationSerPostProcess', 'DistillationRePostProcess',
  'VLLabelDecode', 'PicoDetPostProcess', 'CTPostProcess',
- 'RFLLabelDecode', 'DRRGPostprocess', 'SeqLabelDecode'
+ 'RFLLabelDecode', 'DRRGPostprocess', 'CANLabelDecode'
  ]
 
  if config['name'] == 'PSEPostProcess':

ppocr/postprocess/rec_postprocess.py

@@ -899,12 +899,12 @@ def __call__(self, preds, label=None, length=None, *args, **kwargs):
  return text, label
 
 
-class SeqLabelDecode(BaseRecLabelDecode):
+class CANLabelDecode(BaseRecLabelDecode):
  """ Convert between latex-symbol and symbol-index """
 
  def __init__(self, character_dict_path=None, use_space_char=False,
  **kwargs):
- super(SeqLabelDecode, self).__init__(character_dict_path,
+ super(CANLabelDecode, self).__init__(character_dict_path,
  use_space_char)
 
  def decode(self, text_index, preds_prob=None):

test_tipc/configs/rec_d28_can/rec_d28_can.yml

@@ -42,7 +42,6 @@ Architecture:
  bottleneck: True
  use_dropout: True
  input_channel: 1 
-
  Head:
  name: CANHead
  in_channel: 684
@@ -66,29 +65,32 @@ Loss:
  name: CANLoss
 
 PostProcess:
- name: SeqLabelDecode
- character: 111
+ name: CANLabelDecode
+ character_dict_path: ppocr/utils/dict/latex_symbol_dict.txt
 
 Metric:
  name: CANMetric
  main_indicator: exp_rate
 
 Train:
  dataset:
- name: PGDataSet
- data_dir: ./train_data/CROHME_lite/training/images/
+ name: SimpleDataSet
+ data_dir: ./train_data/CROHME/training/images/
  transforms:
  - DecodeImage:
  channel_first: False
+ - NormalizeImage:
+ mean: [0,0,0]
+ std: [1,1,1]
+ order: 'hwc'
  - GrayImageChannelFormat: 
- normalize: True
  inverse: True
- - SeqLabelEncode:
+ - CANLabelEncode:
  character_dict_path: ppocr/utils/dict/latex_symbol_dict.txt
  lower: False
  - KeepKeys:
  keep_keys: ['image', 'label']
- label_file_list: ["./train_data/CROHME_lite/training/labels.txt"]
+ label_file_list: ["./train_data/CROHME/training/labels.txt"]
  loader:
  shuffle: True
  batch_size_per_card: 8
@@ -98,20 +100,23 @@ Train:
 
 Eval:
  dataset:
- name: PGDataSet
- data_dir: ./train_data/CROHME_lite/evaluation/images/
+ name: SimpleDataSet
+ data_dir: ./train_data/CROHME/evaluation/images/
  transforms: 
  - DecodeImage:
  channel_first: False
+ - NormalizeImage:
+ mean: [0,0,0]
+ std: [1,1,1]
+ order: 'hwc'
  - GrayImageChannelFormat:
- normalize: True
  inverse: True
- - SeqLabelEncode:
+ - CANLabelEncode:
  character_dict_path: ppocr/utils/dict/latex_symbol_dict.txt
  lower: False
  - KeepKeys:
  keep_keys: ['image', 'label']
- label_file_list: ["./train_data/CROHME_lite/evaluation/labels.txt"]
+ label_file_list: ["./train_data/CROHME/evaluation/labels.txt"]
  loader:
  shuffle: False
  drop_last: False

test_tipc/configs/rec_d28_can/train_infer_python.txt

@@ -1,7 +1,7 @@
 ===========================train_params===========================
 model_name:rec_d28_can
-python:python3.7
-gpu_list:0|0,1
+python:python
+gpu_list:0|0
 Global.use_gpu:True|True
 Global.auto_cast:null
 Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=240

test_tipc/prepare.sh

@@ -262,7 +262,6 @@ if [ ${MODE} = "lite_train_lite_infer" ];then
  cd ./pretrain_models/ && tar xf can_train.tar && cd ../
  wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/CROHME_lite.tar --no-check-certificate
  cd ./train_data/ && tar xf CROHME_lite.tar && cd ../
-
  fi
  if [ ${model_name} == "layoutxlm_ser" ]; then
  ${python_name} -m pip install -r ppstructure/kie/requirements.txt

tools/infer/predict_rec.py

@@ -111,7 +111,7 @@ def __init__(self, args):
  elif self.rec_algorithm == "CAN":
  self.inverse = args.rec_image_inverse
  postprocess_params = {
- 'name': 'SeqLabelDecode',
+ 'name': 'CANLabelDecode',
  "character_dict_path": args.rec_char_dict_path,
  "use_space_char": args.use_space_char
  }