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
@@ -66,8 +65,8 @@ Loss:
   name: CANLoss
 
 PostProcess:
-  name: SeqLabelDecode
-  character: 111
+  name: CANLabelDecode
+  character_dict_path: ppocr/utils/dict/latex_symbol_dict.txt
 
 Metric:
   name: CANMetric
@@ -75,15 +74,18 @@ Metric:
 
 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 .make_pse_gt import MakePseGt
 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 @@ class CTLabelEncode(object):
         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 @@ class ResizeNormalize(object):
         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 @@ class RobustScannerRecResizeImg(object):
         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://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

@@ -1,3 +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.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
 import math
 import paddle
 import paddle.nn as nn
@@ -5,14 +23,6 @@ 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://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 .table_postprocess import TableMasterLabelDecode, TableLabelDecode
 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 @@ class VLLabelDecode(BaseRecLabelDecode):
         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
@@ -66,8 +65,8 @@ Loss:
   name: CANLoss
 
 PostProcess:
-  name: SeqLabelDecode
-  character: 111
+  name: CANLabelDecode
+  character_dict_path: ppocr/utils/dict/latex_symbol_dict.txt
 
 Metric:
   name: CANMetric
@@ -75,20 +74,23 @@ Metric:
 
 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 @@ class TextRecognizer(object):
         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
             }