rm rec_char_type

configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec.yml

@@ -14,7 +14,6 @@ Global:
   use_visualdl: false
   infer_img: doc/imgs_words/ch/word_1.jpg
   character_dict_path: ppocr/utils/ppocr_keys_v1.txt
-  character_type: ch
   max_text_length: 25
   infer_mode: false
   use_space_char: true

configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec_distillation.yml

@@ -14,7 +14,6 @@ Global:
   use_visualdl: false
   infer_img: doc/imgs_words/ch/word_1.jpg
   character_dict_path: ppocr/utils/ppocr_keys_v1.txt
-  character_type: ch
   max_text_length: 25
   infer_mode: false
   use_space_char: true

configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec_enhanced_ctc_loss.yml

@@ -14,7 +14,6 @@ Global:
   use_visualdl: false
   infer_img: doc/imgs_words/ch/word_1.jpg
   character_dict_path: ppocr/utils/ppocr_keys_v1.txt
-  character_type: ch
   max_text_length: 25
   infer_mode: false
   use_space_char: true

configs/rec/ch_ppocr_v2.0/rec_chinese_common_train_v2.0.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words/ch/word_1.jpg
   # for data or label process
   character_dict_path: ppocr/utils/ppocr_keys_v1.txt
-  character_type: ch
   max_text_length: 25
   infer_mode: False
   use_space_char: True

configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words/ch/word_1.jpg
   # for data or label process
   character_dict_path: ppocr/utils/ppocr_keys_v1.txt
-  character_type: ch
   max_text_length: 25
   infer_mode: False
   use_space_char: True

configs/rec/multi_language/rec_arabic_lite_train.yml

@@ -15,7 +15,6 @@ Global:
   use_visualdl: false
   infer_img: null
   character_dict_path: ppocr/utils/dict/arabic_dict.txt
-  character_type: arabic
   max_text_length: 25
   infer_mode: false
   use_space_char: true

configs/rec/multi_language/rec_cyrillic_lite_train.yml

@@ -15,7 +15,6 @@ Global:
   use_visualdl: false
   infer_img: null
   character_dict_path: ppocr/utils/dict/cyrillic_dict.txt
-  character_type: cyrillic
   max_text_length: 25
   infer_mode: false
   use_space_char: true

configs/rec/multi_language/rec_devanagari_lite_train.yml

@@ -15,7 +15,6 @@ Global:
   use_visualdl: false
   infer_img: null
   character_dict_path: ppocr/utils/dict/devanagari_dict.txt
-  character_type: devanagari
   max_text_length: 25
   infer_mode: false
   use_space_char: true

configs/rec/multi_language/rec_en_number_lite_train.yml

@@ -16,7 +16,6 @@ Global:
   infer_img:
   # for data or label process
   character_dict_path: ppocr/utils/en_dict.txt
-  character_type: EN
   max_text_length: 25
   infer_mode: False
   use_space_char: True

configs/rec/multi_language/rec_french_lite_train.yml

@@ -16,7 +16,6 @@ Global:
   infer_img:
   # for data or label process
   character_dict_path: ppocr/utils/dict/french_dict.txt
-  character_type: french
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/multi_language/rec_german_lite_train.yml

@@ -16,7 +16,6 @@ Global:
   infer_img:
   # for data or label process
   character_dict_path: ppocr/utils/dict/german_dict.txt
-  character_type: german
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/multi_language/rec_japan_lite_train.yml

@@ -16,7 +16,6 @@ Global:
   infer_img:
   # for data or label process
   character_dict_path: ppocr/utils/dict/japan_dict.txt
-  character_type: japan
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/multi_language/rec_korean_lite_train.yml

@@ -16,7 +16,6 @@ Global:
   infer_img:
   # for data or label process
   character_dict_path: ppocr/utils/dict/korean_dict.txt
-  character_type: korean
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/multi_language/rec_latin_lite_train.yml

@@ -15,7 +15,6 @@ Global:
   use_visualdl: false
   infer_img: null
   character_dict_path: ppocr/utils/dict/latin_dict.txt
-  character_type: latin
   max_text_length: 25
   infer_mode: false
   use_space_char: true

configs/rec/rec_icdar15_train.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words_en/word_10.png
   # for data or label process
   character_dict_path: ppocr/utils/en_dict.txt
-  character_type: EN
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/rec_mtb_nrtr.yml

@@ -14,8 +14,7 @@ Global:
   use_visualdl: False
   infer_img: doc/imgs_words_en/word_10.png
   # for data or label process
-  character_dict_path: 
+  character_dict_path: ppocr/utils/EN_symbol_dict.txt
-  character_type: EN_symbol
   max_text_length: 25
   infer_mode: False
   use_space_char: True

configs/rec/rec_mv3_none_bilstm_ctc.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words_en/word_10.png
   # for data or label process
   character_dict_path:
-  character_type: en
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/rec_mv3_none_none_ctc.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words_en/word_10.png
   # for data or label process
   character_dict_path:
-  character_type: en
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/rec_mv3_tps_bilstm_att.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words/ch/word_1.jpg
   # for data or label process
   character_dict_path:
-  character_type: en
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/rec_mv3_tps_bilstm_ctc.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words_en/word_10.png
   # for data or label process
   character_dict_path:
-  character_type: en
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/rec_r31_sar.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: 
   # for data or label process
   character_dict_path: ppocr/utils/dict90.txt
-  character_type: EN_symbol
   max_text_length: 30
   infer_mode: False
   use_space_char: False

configs/rec/rec_r34_vd_none_bilstm_ctc.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words_en/word_10.png
   # for data or label process
   character_dict_path:
-  character_type: en
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/rec_r34_vd_none_none_ctc.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words_en/word_10.png
   # for data or label process
   character_dict_path:
-  character_type: en
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/rec_r34_vd_tps_bilstm_att.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words/ch/word_1.jpg
   # for data or label process
   character_dict_path:
-  character_type: en
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/rec_r34_vd_tps_bilstm_ctc.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words_en/word_10.png
   # for data or label process
   character_dict_path:
-  character_type: en
   max_text_length: 25
   infer_mode: False
   use_space_char: False

configs/rec/rec_r50_fpn_srn.yml

@@ -15,7 +15,6 @@ Global:
   infer_img: doc/imgs_words/ch/word_1.jpg
   # for data or label process
   character_dict_path:
-  character_type: en
   max_text_length: 25
   num_heads: 8
   infer_mode: False

configs/rec/rec_resnet_stn_bilstm_att.yml

@@ -14,8 +14,7 @@ Global:
   use_visualdl: False
   infer_img: doc/imgs_words_en/word_10.png
   # for data or label process
-  character_dict_path: 
+  character_dict_path: ppocr/utils/EN_symbol_dict.txt
-  character_type: EN_symbol
   max_text_length: 100
   infer_mode: False
   use_space_char: False

doc/doc_ch/inference.md

@@ -273,7 +273,7 @@ python3 tools/export_model.py -c configs/rec/rec_r34_vd_none_bilstm_ctc.yml -o G
 CRNN 文本识别模型推理，可以执行如下命令：
 
 ```
-python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./inference/rec_crnn/" --rec_image_shape="3, 32, 100" --rec_char_type="en"
+python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./inference/rec_crnn/" --rec_image_shape="3, 32, 100" --rec_char_dict_path="./ppocr/utils/ic15_dict.txt"
 ```
 
 ![](../imgs_words_en/word_336.png)
@@ -288,7 +288,7 @@ Predicts of ./doc/imgs_words_en/word_336.png:('super', 0.9999073)
 
 - 训练时采用的图像分辨率不同，训练上述模型采用的图像分辨率是[3，32，100]，而中文模型训练时，为了保证长文本的识别效果，训练时采用的图像分辨率是[3, 32, 320]。预测推理程序默认的的形状参数是训练中文采用的图像分辨率，即[3, 32, 320]。因此，这里推理上述英文模型时，需要通过参数rec_image_shape设置识别图像的形状。
 
-- 字符列表，DTRB论文中实验只是针对26个小写英文本母和10个数字进行实验，总共36个字符。所有大小字符都转成了小写字符，不在上面列表的字符都忽略，认为是空格。因此这里没有输入字符字典，而是通过如下命令生成字典.因此在推理时需要设置参数rec_char_type，指定为英文"en"。
+- 字符列表，DTRB论文中实验只是针对26个小写英文本母和10个数字进行实验，总共36个字符。所有大小字符都转成了小写字符，不在上面列表的字符都忽略，认为是空格。因此这里没有输入字符字典，而是通过如下命令生成字典.因此在推理时需要设置参数rec_char_dict_path，指定为英文字典"./ppocr/utils/ic15_dict.txt"。
 
 ```
 self.character_str = "0123456789abcdefghijklmnopqrstuvwxyz"
@@ -303,15 +303,15 @@ dict_character = list(self.character_str)
 python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" \
                                    --rec_model_dir="./inference/srn/" \
                                    --rec_image_shape="1, 64, 256" \
-                                   --rec_char_type="en" \
+                                   --rec_char_dict_path="./ppocr/utils/ic15_dict.txt" \
                                    --rec_algorithm="SRN"
 ```
 
 ### 4. 自定义文本识别字典的推理
-如果训练时修改了文本的字典，在使用inference模型预测时，需要通过`--rec_char_dict_path`指定使用的字典路径，并且设置 `rec_char_type=ch`
+如果训练时修改了文本的字典，在使用inference模型预测时，需要通过`--rec_char_dict_path`指定使用的字典路径
 
 ```
-python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./your inference model" --rec_image_shape="3, 32, 100" --rec_char_type="ch" --rec_char_dict_path="your text dict path"
+python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./your inference model" --rec_image_shape="3, 32, 100"  --rec_char_dict_path="your text dict path"
 ```
 
 <a name="多语言模型的推理"></a>
@@ -320,7 +320,7 @@ python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png
 需要通过 `--vis_font_path` 指定可视化的字体路径，`doc/fonts/` 路径下有默认提供的小语种字体，例如韩文识别：
 
 ```
-python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/korean/1.jpg" --rec_model_dir="./your inference model" --rec_char_type="korean" --rec_char_dict_path="ppocr/utils/dict/korean_dict.txt" --vis_font_path="doc/fonts/korean.ttf"
+python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/korean/1.jpg" --rec_model_dir="./your inference model"  --rec_char_dict_path="ppocr/utils/dict/korean_dict.txt" --vis_font_path="doc/fonts/korean.ttf"
 ```
 ![](../imgs_words/korean/1.jpg)
 
@@ -388,7 +388,7 @@ python3 tools/infer/predict_system.py --image_dir="./doc/imgs/00018069.jpg" --de
 下面给出基于EAST文本检测和STAR-Net文本识别执行命令：
 
 ```
-python3 tools/infer/predict_system.py --image_dir="./doc/imgs_en/img_10.jpg" --det_model_dir="./inference/det_east/" --det_algorithm="EAST" --rec_model_dir="./inference/starnet/" --rec_image_shape="3, 32, 100" --rec_char_type="en"
+python3 tools/infer/predict_system.py --image_dir="./doc/imgs_en/img_10.jpg" --det_model_dir="./inference/det_east/" --det_algorithm="EAST" --rec_model_dir="./inference/starnet/" --rec_image_shape="3, 32, 100" --rec_char_dict_path="./ppocr/utils/ic15_dict.txt"
 ```
 
 执行命令后，识别结果图像如下：

doc/doc_en/inference_en.md

@@ -281,7 +281,7 @@ python3 tools/export_model.py -c configs/det/rec_r34_vd_none_bilstm_ctc.yml -o G
 For CRNN text recognition model inference, execute the following commands:
 
 ```
-python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./inference/starnet/" --rec_image_shape="3, 32, 100" --rec_char_type="en"
+python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./inference/starnet/" --rec_image_shape="3, 32, 100" --rec_char_dict_path="./ppocr/utils/ic15_dict.txt"
 ```
 
 ![](../imgs_words_en/word_336.png)
@@ -314,7 +314,7 @@ with the training, such as: --rec_image_shape="1, 64, 256"
 python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" \
                                     --rec_model_dir="./inference/srn/" \
                                     --rec_image_shape="1, 64, 256" \
-                                    --rec_char_type="en" \
+                                    --rec_char_dict_path="./ppocr/utils/ic15_dict.txt" \
                                     --rec_algorithm="SRN"
 ```
 
@@ -323,7 +323,7 @@ python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png
 If the text dictionary is modified during training, when using the inference model to predict, you need to specify the dictionary path used by `--rec_char_dict_path`, and set `rec_char_type=ch`
 
 ```
-python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./your inference model" --rec_image_shape="3, 32, 100" --rec_char_type="ch" --rec_char_dict_path="your text dict path"
+python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words_en/word_336.png" --rec_model_dir="./your inference model" --rec_image_shape="3, 32, 100"  --rec_char_dict_path="your text dict path"
 ```
 
 <a name="MULTILINGUAL_MODEL_INFERENCE"></a>
@@ -333,7 +333,7 @@ If you need to predict other language models, when using inference model predict
 You need to specify the visual font path through `--vis_font_path`. There are small language fonts provided by default under the `doc/fonts` path, such as Korean recognition:
 
 ```
-python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/korean/1.jpg" --rec_model_dir="./your inference model" --rec_char_type="korean" --rec_char_dict_path="ppocr/utils/dict/korean_dict.txt" --vis_font_path="doc/fonts/korean.ttf"
+python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/korean/1.jpg" --rec_model_dir="./your inference model"  --rec_char_dict_path="ppocr/utils/dict/korean_dict.txt" --vis_font_path="doc/fonts/korean.ttf"
 ```
 ![](../imgs_words/korean/1.jpg)
 
@@ -399,7 +399,7 @@ If you want to try other detection algorithms or recognition algorithms, please
 The following command uses the combination of the EAST text detection and STAR-Net text recognition:
 
 ```
-python3 tools/infer/predict_system.py --image_dir="./doc/imgs_en/img_10.jpg" --det_model_dir="./inference/det_east/" --det_algorithm="EAST" --rec_model_dir="./inference/starnet/" --rec_image_shape="3, 32, 100" --rec_char_type="en"
+python3 tools/infer/predict_system.py --image_dir="./doc/imgs_en/img_10.jpg" --det_model_dir="./inference/det_east/" --det_algorithm="EAST" --rec_model_dir="./inference/starnet/" --rec_image_shape="3, 32, 100" --rec_char_dict_path="./ppocr/utils/ic15_dict.txt"
 ```
 
 After executing the command, the recognition result image is as follows:

ppocr/data/imaug/label_ops.py

@@ -21,6 +21,8 @@ import numpy as np
 import string
 import json
 
+from ppocr.utils.logging import get_logger
+
 
 class ClsLabelEncode(object):
     def __init__(self, label_list, **kwargs):
@@ -92,31 +94,22 @@ class BaseRecLabelEncode(object):
     def __init__(self,
                  max_text_length,
                  character_dict_path=None,
-                 character_type='ch',
                  use_space_char=False):
-        support_character_type = [
-            'ch', 'en', 'EN_symbol', 'french', 'german', 'japan', 'korean',
-            'EN', 'it', 'xi', 'pu', 'ru', 'ar', 'ta', 'ug', 'fa', 'ur', 'rs',
-            'oc', 'rsc', 'bg', 'uk', 'be', 'te', 'ka', 'chinese_cht', 'hi',
-            'mr', 'ne', 'latin', 'arabic', 'cyrillic', 'devanagari'
-        ]
-        assert character_type in support_character_type, "Only {} are supported now but get {}".format(
-            support_character_type, character_type)
 
         self.max_text_len = max_text_length
         self.beg_str = "sos"
         self.end_str = "eos"
-        if character_type == "en":
+
+        if character_dict_path is None:
+            logger = get_logger()
+            logger.warning(
+                "The character_dict_path is None, model can only recognize number and lower letters"
+            )
             self.character_str = "0123456789abcdefghijklmnopqrstuvwxyz"
             dict_character = list(self.character_str)
-        elif character_type == "EN_symbol":
+            self.lower = True
-            # same with ASTER setting (use 94 char).
+        else:
-            self.character_str = string.printable[:-6]
-            dict_character = list(self.character_str)
-        elif character_type in support_character_type:
             self.character_str = ""
-            assert character_dict_path is not None, "character_dict_path should not be None when character_type is {}".format(
-                character_type)
             with open(character_dict_path, "rb") as fin:
                 lines = fin.readlines()
                 for line in lines:
@@ -125,7 +118,6 @@ class BaseRecLabelEncode(object):
             if use_space_char:
                 self.character_str += " "
             dict_character = list(self.character_str)
-        self.character_type = character_type
         dict_character = self.add_special_char(dict_character)
         self.dict = {}
         for i, char in enumerate(dict_character):
@@ -147,7 +139,7 @@ class BaseRecLabelEncode(object):
         """
         if len(text) == 0 or len(text) > self.max_text_len:
             return None
-        if self.character_type == "en":
+        if self.lower:
             text = text.lower()
         text_list = []
         for char in text:
@@ -167,13 +159,11 @@ class NRTRLabelEncode(BaseRecLabelEncode):
     def __init__(self,
                  max_text_length,
                  character_dict_path=None,
-                 character_type='EN_symbol',
                  use_space_char=False,
                  **kwargs):
 
-        super(NRTRLabelEncode,
+        super(NRTRLabelEncode, self).__init__(
-              self).__init__(max_text_length, character_dict_path,
+            max_text_length, character_dict_path, use_space_char)
-                             character_type, use_space_char)
 
     def __call__(self, data):
         text = data['label']
@@ -200,12 +190,10 @@ class CTCLabelEncode(BaseRecLabelEncode):
     def __init__(self,
                  max_text_length,
                  character_dict_path=None,
-                 character_type='ch',
                  use_space_char=False,
                  **kwargs):
-        super(CTCLabelEncode,
+        super(CTCLabelEncode, self).__init__(
-              self).__init__(max_text_length, character_dict_path,
+            max_text_length, character_dict_path, use_space_char)
-                             character_type, use_space_char)
 
     def __call__(self, data):
         text = data['label']
@@ -231,12 +219,10 @@ class E2ELabelEncodeTest(BaseRecLabelEncode):
     def __init__(self,
                  max_text_length,
                  character_dict_path=None,
-                 character_type='EN',
                  use_space_char=False,
                  **kwargs):
-        super(E2ELabelEncodeTest,
+        super(E2ELabelEncodeTest, self).__init__(
-              self).__init__(max_text_length, character_dict_path,
+            max_text_length, character_dict_path, use_space_char)
-                             character_type, use_space_char)
 
     def __call__(self, data):
         import json
@@ -305,12 +291,10 @@ class AttnLabelEncode(BaseRecLabelEncode):
     def __init__(self,
                  max_text_length,
                  character_dict_path=None,
-                 character_type='ch',
                  use_space_char=False,
                  **kwargs):
-        super(AttnLabelEncode,
+        super(AttnLabelEncode, self).__init__(
-              self).__init__(max_text_length, character_dict_path,
+            max_text_length, character_dict_path, use_space_char)
-                             character_type, use_space_char)
 
     def add_special_char(self, dict_character):
         self.beg_str = "sos"
@@ -353,12 +337,10 @@ class SEEDLabelEncode(BaseRecLabelEncode):
     def __init__(self,
                  max_text_length,
                  character_dict_path=None,
-                 character_type='ch',
                  use_space_char=False,
                  **kwargs):
-        super(SEEDLabelEncode,
+        super(SEEDLabelEncode, self).__init__(
-              self).__init__(max_text_length, character_dict_path,
+            max_text_length, character_dict_path, use_space_char)
-                             character_type, use_space_char)
 
     def add_special_char(self, dict_character):
         self.end_str = "eos"
@@ -385,12 +367,10 @@ class SRNLabelEncode(BaseRecLabelEncode):
     def __init__(self,
                  max_text_length=25,
                  character_dict_path=None,
-                 character_type='en',
                  use_space_char=False,
                  **kwargs):
-        super(SRNLabelEncode,
+        super(SRNLabelEncode, self).__init__(
-              self).__init__(max_text_length, character_dict_path,
+            max_text_length, character_dict_path, use_space_char)
-                             character_type, use_space_char)
 
     def add_special_char(self, dict_character):
         dict_character = dict_character + [self.beg_str, self.end_str]
@@ -598,12 +578,10 @@ class SARLabelEncode(BaseRecLabelEncode):
     def __init__(self,
                  max_text_length,
                  character_dict_path=None,
-                 character_type='ch',
                  use_space_char=False,
                  **kwargs):
-        super(SARLabelEncode,
+        super(SARLabelEncode, self).__init__(
-              self).__init__(max_text_length, character_dict_path,
+            max_text_length, character_dict_path, use_space_char)
-                             character_type, use_space_char)
 
     def add_special_char(self, dict_character):
         beg_end_str = "<BOS/EOS>"

ppocr/postprocess/rec_postprocess.py

@@ -21,33 +21,16 @@ import re
 class BaseRecLabelDecode(object):
     """ Convert between text-label and text-index """
 
-    def __init__(self,
+    def __init__(self, character_dict_path=None, use_space_char=False):
-                 character_dict_path=None,
-                 character_type='ch',
-                 use_space_char=False):
-        support_character_type = [
-            'ch', 'en', 'EN_symbol', 'french', 'german', 'japan', 'korean',
-            'it', 'xi', 'pu', 'ru', 'ar', 'ta', 'ug', 'fa', 'ur', 'rs', 'oc',
-            'rsc', 'bg', 'uk', 'be', 'te', 'ka', 'chinese_cht', 'hi', 'mr',
-            'ne', 'EN', 'latin', 'arabic', 'cyrillic', 'devanagari'
-        ]
-        assert character_type in support_character_type, "Only {} are supported now but get {}".format(
-            support_character_type, character_type)
-
         self.beg_str = "sos"
         self.end_str = "eos"
 
-        if character_type == "en":
+        self.character_str = []
+        if character_dict_path is None:
             self.character_str = "0123456789abcdefghijklmnopqrstuvwxyz"
             dict_character = list(self.character_str)
-        elif character_type == "EN_symbol":
+            self.lower = True
-            # same with ASTER setting (use 94 char).
+        else:
-            self.character_str = string.printable[:-6]
-            dict_character = list(self.character_str)
-        elif character_type in support_character_type:
-            self.character_str = []
-            assert character_dict_path is not None, "character_dict_path should not be None when character_type is {}".format(
-                character_type)
             with open(character_dict_path, "rb") as fin:
                 lines = fin.readlines()
                 for line in lines:
@@ -57,9 +40,6 @@ class BaseRecLabelDecode(object):
                 self.character_str.append(" ")
             dict_character = list(self.character_str)
 
-        else:
-            raise NotImplementedError
-        self.character_type = character_type
         dict_character = self.add_special_char(dict_character)
         self.dict = {}
         for i, char in enumerate(dict_character):
@@ -102,13 +82,10 @@ class BaseRecLabelDecode(object):
 class CTCLabelDecode(BaseRecLabelDecode):
     """ Convert between text-label and text-index """
 
-    def __init__(self,
+    def __init__(self, character_dict_path=None, use_space_char=False,
-                 character_dict_path=None,
-                 character_type='ch',
-                 use_space_char=False,
                  **kwargs):
         super(CTCLabelDecode, self).__init__(character_dict_path,
-                                             character_type, use_space_char)
+                                             use_space_char)
 
     def __call__(self, preds, label=None, *args, **kwargs):
         if isinstance(preds, tuple):
@@ -136,13 +113,12 @@ class DistillationCTCLabelDecode(CTCLabelDecode):
 
     def __init__(self,
                  character_dict_path=None,
-                 character_type='ch',
                  use_space_char=False,
                  model_name=["student"],
                  key=None,
                  **kwargs):
-        super(DistillationCTCLabelDecode, self).__init__(
+        super(DistillationCTCLabelDecode, self).__init__(character_dict_path,
-            character_dict_path, character_type, use_space_char)
+                                                         use_space_char)
         if not isinstance(model_name, list):
             model_name = [model_name]
         self.model_name = model_name
@@ -162,13 +138,9 @@ class DistillationCTCLabelDecode(CTCLabelDecode):
 class NRTRLabelDecode(BaseRecLabelDecode):
     """ Convert between text-label and text-index """
 
-    def __init__(self,
+    def __init__(self, character_dict_path=None, use_space_char=True, **kwargs):
-                 character_dict_path=None,
-                 character_type='EN_symbol',
-                 use_space_char=True,
-                 **kwargs):
         super(NRTRLabelDecode, self).__init__(character_dict_path,
-                                              character_type, use_space_char)
+                                              use_space_char)
 
     def __call__(self, preds, label=None, *args, **kwargs):
 
@@ -230,13 +202,10 @@ class NRTRLabelDecode(BaseRecLabelDecode):
 class AttnLabelDecode(BaseRecLabelDecode):
     """ Convert between text-label and text-index """
 
-    def __init__(self,
+    def __init__(self, character_dict_path=None, use_space_char=False,
-                 character_dict_path=None,
-                 character_type='ch',
-                 use_space_char=False,
                  **kwargs):
         super(AttnLabelDecode, self).__init__(character_dict_path,
-                                              character_type, use_space_char)
+                                              use_space_char)
 
     def add_special_char(self, dict_character):
         self.beg_str = "sos"
@@ -313,13 +282,10 @@ class AttnLabelDecode(BaseRecLabelDecode):
 class SEEDLabelDecode(BaseRecLabelDecode):
     """ Convert between text-label and text-index """
 
-    def __init__(self,
+    def __init__(self, character_dict_path=None, use_space_char=False,
-                 character_dict_path=None,
-                 character_type='ch',
-                 use_space_char=False,
                  **kwargs):
         super(SEEDLabelDecode, self).__init__(character_dict_path,
-                                              character_type, use_space_char)
+                                              use_space_char)
 
     def add_special_char(self, dict_character):
         self.beg_str = "sos"
@@ -394,13 +360,10 @@ class SEEDLabelDecode(BaseRecLabelDecode):
 class SRNLabelDecode(BaseRecLabelDecode):
     """ Convert between text-label and text-index """
 
-    def __init__(self,
+    def __init__(self, character_dict_path=None, use_space_char=False,
-                 character_dict_path=None,
-                 character_type='en',
-                 use_space_char=False,
                  **kwargs):
         super(SRNLabelDecode, self).__init__(character_dict_path,
-                                             character_type, use_space_char)
+                                             use_space_char)
         self.max_text_length = kwargs.get('max_text_length', 25)
 
     def __call__(self, preds, label=None, *args, **kwargs):
@@ -616,13 +579,10 @@ class TableLabelDecode(object):
 class SARLabelDecode(BaseRecLabelDecode):
     """ Convert between text-label and text-index """
 
-    def __init__(self,
+    def __init__(self, character_dict_path=None, use_space_char=False,
-                 character_dict_path=None,
-                 character_type='ch',
-                 use_space_char=False,
                  **kwargs):
         super(SARLabelDecode, self).__init__(character_dict_path,
-                                             character_type, use_space_char)
+                                             use_space_char)
 
         self.rm_symbol = kwargs.get('rm_symbol', False)
 

ppocr/utils/EN_symbol_dict.txt

@@ -0,0 +1,94 @@
+0
+1
+2
+3
+4
+5
+6
+7
+8
+9
+a
+b
+c
+d
+e
+f
+g
+h
+i
+j
+k
+l
+m
+n
+o
+p
+q
+r
+s
+t
+u
+v
+w
+x
+y
+z
+A
+B
+C
+D
+E
+F
+G
+H
+I
+J
+K
+L
+M
+N
+O
+P
+Q
+R
+S
+T
+U
+V
+W
+X
+Y
+Z
+!
+"
+#
+$
+%
+&
+'
+(
+)
+*
++
+,
+-
+.
+/
+:
+;
+<
+=
+>
+?
+@
+[
+\
+]
+^
+_
+`
+{
+|
+}
+~

tools/infer/predict_cls.py

@@ -131,14 +131,9 @@ def main(args):
         img_list.append(img)
     try:
         img_list, cls_res, predict_time = text_classifier(img_list)
-    except:
+    except Exception as E:
         logger.info(traceback.format_exc())
-        logger.info(
+        logger.info(E)
-            "ERROR!!!! \n"
-            "Please read the FAQ：https://github.com/PaddlePaddle/PaddleOCR#faq \n"
-            "If your model has tps module:  "
-            "TPS does not support variable shape.\n"
-            "Please set --rec_image_shape='3,32,100' and --rec_char_type='en' ")
         exit()
     for ino in range(len(img_list)):
         logger.info("Predicts of {}:{}".format(valid_image_file_list[ino],

tools/infer/predict_rec.py

@@ -38,40 +38,34 @@ logger = get_logger()
 class TextRecognizer(object):
     def __init__(self, args):
         self.rec_image_shape = [int(v) for v in args.rec_image_shape.split(",")]
-        self.character_type = args.rec_char_type
         self.rec_batch_num = args.rec_batch_num
         self.rec_algorithm = args.rec_algorithm
         postprocess_params = {
             'name': 'CTCLabelDecode',
-            "character_type": args.rec_char_type,
             "character_dict_path": args.rec_char_dict_path,
             "use_space_char": args.use_space_char
         }
         if self.rec_algorithm == "SRN":
             postprocess_params = {
                 'name': 'SRNLabelDecode',
-                "character_type": args.rec_char_type,
                 "character_dict_path": args.rec_char_dict_path,
                 "use_space_char": args.use_space_char
             }
         elif self.rec_algorithm == "RARE":
             postprocess_params = {
                 'name': 'AttnLabelDecode',
-                "character_type": args.rec_char_type,
                 "character_dict_path": args.rec_char_dict_path,
                 "use_space_char": args.use_space_char
             }
         elif self.rec_algorithm == 'NRTR':
             postprocess_params = {
                 'name': 'NRTRLabelDecode',
-                "character_type": args.rec_char_type,
                 "character_dict_path": args.rec_char_dict_path,
                 "use_space_char": args.use_space_char
             }
         elif self.rec_algorithm == "SAR":
             postprocess_params = {
                 'name': 'SARLabelDecode',
-                "character_type": args.rec_char_type,
                 "character_dict_path": args.rec_char_dict_path,
                 "use_space_char": args.use_space_char
             }

tools/infer/utility.py

@@ -74,7 +74,6 @@ def init_args():
     parser.add_argument("--rec_algorithm", type=str, default='CRNN')
     parser.add_argument("--rec_model_dir", type=str)
     parser.add_argument("--rec_image_shape", type=str, default="3, 32, 320")
-    parser.add_argument("--rec_char_type", type=str, default='ch')
     parser.add_argument("--rec_batch_num", type=int, default=6)
     parser.add_argument("--max_text_length", type=int, default=25)
     parser.add_argument(