Merge remote-tracking branch 'origin/android_demo' into android_demo

e296a968 · WenmuZhou · 8601b8e9 · 2f2d152c · e296a968 · e296a968
Commit e296a968 authored May 10, 2021 by WenmuZhou
20 changed files
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -4,4 +4,5 @@ include README.md
 recursive-include ppocr/utils *.txt utility.py logging.py
 recursive-include ppocr/data/ *.py
 recursive-include ppocr/postprocess *.py
 recursive-include tools/infer *.py
\ No newline at end of file
+recursive-include ppocr/utils/e2e_utils/ *.py
\ No newline at end of file
--- a/PPOCRLabel/PPOCRLabel.py
+++ b/PPOCRLabel/PPOCRLabel.py
@@ -147,6 +147,7 @@ class MainWindow(QMainWindow, WindowMixin):
        self.itemsToShapesbox = {}
        self.shapesToItemsbox = {}
        self.prevLabelText = getStr('tempLabel')
+        self.noLabelText = getStr('nullLabel')
        self.model = 'paddle'
        self.PPreader = None
        self.autoSaveNum = 5
@@ -1020,7 +1021,7 @@ class MainWindow(QMainWindow, WindowMixin):
        item.setText(str([(int(p.x()), int(p.y())) for p in shape.points]))
        self.updateComboBox()
-    def updateComboBox(self): # TODO：貌似没用
+    def updateComboBox(self):
        # Get the unique labels and add them to the Combobox.
        itemsTextList = [str(self.labelList.item(i).text()) for i in range(self.labelList.count())]
@@ -1040,7 +1041,7 @@ class MainWindow(QMainWindow, WindowMixin):
            return dict(label=s.label,  # str
                        line_color=s.line_color.getRgb(),
                        fill_color=s.fill_color.getRgb(),
-                        points=[(p.x(), p.y()) for p in s.points],  # QPonitF
+                        points=[(int(p.x()), int(p.y())) for p in s.points],  # QPonitF
                       # add chris
                        difficult=s.difficult)  # bool
@@ -1069,7 +1070,7 @@ class MainWindow(QMainWindow, WindowMixin):
            # print('Image:{0} -> Annotation:{1}'.format(self.filePath, annotationFilePath))
            return True
        except:
-            self.errorMessage(u'Error saving label data')
+            self.errorMessage(u'Error saving label data', u'Error saving label data')
            return False
    def copySelectedShape(self):
@@ -1802,10 +1803,14 @@ class MainWindow(QMainWindow, WindowMixin):
                    result.insert(0, box)
                    print('result in reRec is ', result)
                    self.result_dic.append(result)
-                    if result[1][0] == shape.label:
+                else:
-                        print('label no change')
+                    print('Can not recognise the box')
-                    else:
+                    self.result_dic.append([box,(self.noLabelText,0)])
-                        rec_flag += 1
+                if self.noLabelText == shape.label or result[1][0] == shape.label:
+                    print('label no change')
+                else:
+                    rec_flag += 1
            if len(self.result_dic) > 0 and rec_flag > 0:
                self.saveFile(mode='Auto')
@@ -1836,9 +1841,14 @@ class MainWindow(QMainWindow, WindowMixin):
                    print('label no change')
                else:
                    shape.label = result[1][0]
-                self.singleLabel(shape)
+            else:
-                self.setDirty()
+                print('Can not recognise the box')
-            print(box)
+                if self.noLabelText == shape.label:
+                    print('label no change')
+                else:
+                    shape.label = self.noLabelText
+            self.singleLabel(shape)
+            self.setDirty()
    def autolcm(self):
        vbox = QVBoxLayout()

--- a/PPOCRLabel/libs/canvas.py
+++ b/PPOCRLabel/libs/canvas.py
@@ -45,7 +45,7 @@ class Canvas(QWidget):
    CREATE, EDIT = list(range(2))
    _fill_drawing = False # draw shadows
-    epsilon = 11.0
+    epsilon = 5.0
    def __init__(self, *args, **kwargs):
        super(Canvas, self).__init__(*args, **kwargs)

--- a/PPOCRLabel/libs/resources.py
+++ b/PPOCRLabel/libs/resources.py
--- a/PPOCRLabel/resources/strings/strings-zh-CN.properties
+++ b/PPOCRLabel/resources/strings/strings-zh-CN.properties
@@ -87,6 +87,7 @@ creatPolygon=四点标注
 drawSquares=正方形标注
 saveRec=保存识别结果
 tempLabel=待识别
+nullLabel=无法识别
 steps=操作步骤
 choseModelLg=选择模型语言
 cancel=取消

--- a/PPOCRLabel/resources/strings/strings.properties
+++ b/PPOCRLabel/resources/strings/strings.properties
@@ -77,7 +77,7 @@ IR=Image Resize
 autoRecognition=Auto Recognition
 reRecognition=Re-recognition
 mfile=File
-medit=Eidt
+medit=Edit
 mview=View
 mhelp=Help
 iconList=Icon List
@@ -87,6 +87,7 @@ creatPolygon=Create Quadrilateral
 drawSquares=Draw Squares
 saveRec=Save Recognition Result
 tempLabel=TEMPORARY
+nullLabel=NULL
 steps=Steps
 choseModelLg=Choose Model Language
 cancel=Cancel

--- a/README.md
+++ b/README.md
@@ -32,7 +32,8 @@ PaddleOCR supports both dynamic graph and static graph programming paradigm
 <div align="center">
    <img src="doc/imgs_results/ch_ppocr_mobile_v2.0/test_add_91.jpg" width="800">
-    <img src="doc/imgs_results/ch_ppocr_mobile_v2.0/00018069.jpg" width="800">
+    <img src="doc/imgs_results/multi_lang/img_01.jpg" width="800">
+    <img src="doc/imgs_results/multi_lang/img_02.jpg" width="800">
 </div>
 The above pictures are the visualizations of the general ppocr_server model. For more effect pictures, please see [More visualizations](./doc/doc_en/visualization_en.md).

--- a/configs/e2e/e2e_r50_vd_pg.yml
+++ b/configs/e2e/e2e_r50_vd_pg.yml
@@ -59,8 +59,10 @@ Optimizer:
 PostProcess:
  name: PGPostProcess
  score_thresh: 0.5
+  mode: fast   # fast or slow two ways
 Metric:
  name: E2EMetric
+  gt_mat_dir:    # the dir of gt_mat
  character_dict_path: ppocr/utils/ic15_dict.txt
  main_indicator: f_score_e2e
@@ -106,7 +108,7 @@ Eval:
          order: 'hwc'
      - ToCHWImage:
      - KeepKeys:
-          keep_keys: [ 'image', 'shape', 'polys', 'strs', 'tags' ]
+          keep_keys: [ 'image', 'shape', 'polys', 'strs', 'tags', 'img_id']
  loader:
    shuffle: False
    drop_last: False

--- a/configs/rec/multi_language/generate_multi_language_configs.py
+++ b/configs/rec/multi_language/generate_multi_language_configs.py
@@ -19,21 +19,56 @@ import logging
 logging.basicConfig(level=logging.INFO)
 support_list = {
-    'it':'italian', 'xi':'spanish', 'pu':'portuguese', 'ru':'russian', 'ar':'arabic',
+    'it': 'italian',
-    'ta':'tamil', 'ug':'uyghur', 'fa':'persian', 'ur':'urdu', 'rs':'serbian latin',
+    'xi': 'spanish',
-    'oc':'occitan', 'rsc':'serbian cyrillic', 'bg':'bulgarian', 'uk':'ukranian', 'be':'belarusian',
+    'pu': 'portuguese',
-    'te':'telugu', 'ka':'kannada', 'chinese_cht':'chinese tradition','hi':'hindi','mr':'marathi',
+    'ru': 'russian',
-    'ne':'nepali',
+    'ar': 'arabic',
+    'ta': 'tamil',
+    'ug': 'uyghur',
+    'fa': 'persian',
+    'ur': 'urdu',
+    'rs': 'serbian latin',
+    'oc': 'occitan',
+    'rsc': 'serbian cyrillic',
+    'bg': 'bulgarian',
+    'uk': 'ukranian',
+    'be': 'belarusian',
+    'te': 'telugu',
+    'ka': 'kannada',
+    'chinese_cht': 'chinese tradition',
+    'hi': 'hindi',
+    'mr': 'marathi',
+    'ne': 'nepali',
 }
-assert(
-    os.path.isfile("./rec_multi_language_lite_train.yml")
+latin_lang = [
-    ),"Loss basic configuration file rec_multi_language_lite_train.yml.\
+    'af', 'az', 'bs', 'cs', 'cy', 'da', 'de', 'es', 'et', 'fr', 'ga', 'hr',
+    'hu', 'id', 'is', 'it', 'ku', 'la', 'lt', 'lv', 'mi', 'ms', 'mt', 'nl',
+    'no', 'oc', 'pi', 'pl', 'pt', 'ro', 'rs_latin', 'sk', 'sl', 'sq', 'sv',
+    'sw', 'tl', 'tr', 'uz', 'vi', 'latin'
+]
+arabic_lang = ['ar', 'fa', 'ug', 'ur']
+cyrillic_lang = [
+    'ru', 'rs_cyrillic', 'be', 'bg', 'uk', 'mn', 'abq', 'ady', 'kbd', 'ava',
+    'dar', 'inh', 'che', 'lbe', 'lez', 'tab', 'cyrillic'
+]
+devanagari_lang = [
+    'hi', 'mr', 'ne', 'bh', 'mai', 'ang', 'bho', 'mah', 'sck', 'new', 'gom',
+    'sa', 'bgc', 'devanagari'
+]
+multi_lang = latin_lang + arabic_lang + cyrillic_lang + devanagari_lang
+assert (os.path.isfile("./rec_multi_language_lite_train.yml")
+        ), "Loss basic configuration file rec_multi_language_lite_train.yml.\
 You can download it from \
 https://github.com/PaddlePaddle/PaddleOCR/tree/dygraph/configs/rec/multi_language/"
-global_config = yaml.load(open("./rec_multi_language_lite_train.yml", 'rb'), Loader=yaml.Loader)
+global_config = yaml.load(
+    open("./rec_multi_language_lite_train.yml", 'rb'), Loader=yaml.Loader)
 project_path = os.path.abspath(os.path.join(os.getcwd(), "../../../"))
 class ArgsParser(ArgumentParser):
    def __init__(self):
        super(ArgsParser, self).__init__(
@@ -41,15 +76,30 @@ class ArgsParser(ArgumentParser):
        self.add_argument(
            "-o", "--opt", nargs='+', help="set configuration options")
        self.add_argument(
-            "-l", "--language", nargs='+', help="set language type, support {}".format(support_list))
+            "-l",
+            "--language",
+            nargs='+',
+            help="set language type, support {}".format(support_list))
        self.add_argument(
-            "--train",type=str,help="you can use this command to change the train dataset default path")
+            "--train",
+            type=str,
+            help="you can use this command to change the train dataset default path"
+        )
        self.add_argument(
-            "--val",type=str,help="you can use this command to change the eval dataset default path")
+            "--val",
+            type=str,
+            help="you can use this command to change the eval dataset default path"
+        )
        self.add_argument(
-            "--dict",type=str,help="you can use this command to change the dictionary default path")
+            "--dict",
+            type=str,
+            help="you can use this command to change the dictionary default path"
+        )
        self.add_argument(
-            "--data_dir",type=str,help="you can use this command to change the dataset default root path")
+            "--data_dir",
+            type=str,
+            help="you can use this command to change the dataset default root path"
+        )
    def parse_args(self, argv=None):
        args = super(ArgsParser, self).parse_args(argv)
@@ -68,21 +118,37 @@ class ArgsParser(ArgumentParser):
        return config
    def _set_language(self, type):
-        assert(type),"please use -l or --language to choose language type"
+        lang = type[0]
+        assert (type), "please use -l or --language to choose language type"
        assert(
-                type[0] in support_list.keys()
+                lang in support_list.keys() or lang in multi_lang
               ),"the sub_keys(-l or --language) can only be one of support list: \n{},\nbut get: {}, " \
-                 "please check your running command".format(support_list, type)
+                 "please check your running command".format(multi_lang, type)
-        global_config['Global']['character_dict_path'] = 'ppocr/utils/dict/{}_dict.txt'.format(type[0])
+        if lang in latin_lang:
-        global_config['Global']['save_model_dir'] = './output/rec_{}_lite'.format(type[0])
+            lang = "latin"
-        global_config['Train']['dataset']['label_file_list'] = ["train_data/{}_train.txt".format(type[0])]
+        elif lang in arabic_lang:
-        global_config['Eval']['dataset']['label_file_list'] = ["train_data/{}_val.txt".format(type[0])]
+            lang = "arabic"
-        global_config['Global']['character_type'] = type[0]
+        elif lang in cyrillic_lang:
-        assert(
+            lang = "cyrillic"
-                os.path.isfile(os.path.join(project_path,global_config['Global']['character_dict_path']))
+        elif lang in devanagari_lang:
-              ),"Loss default dictionary file {}_dict.txt.You can download it from \
+            lang = "devanagari"
-https://github.com/PaddlePaddle/PaddleOCR/tree/dygraph/ppocr/utils/dict/".format(type[0])
+        global_config['Global'][
-        return type[0]
+            'character_dict_path'] = 'ppocr/utils/dict/{}_dict.txt'.format(lang)
+        global_config['Global'][
+            'save_model_dir'] = './output/rec_{}_lite'.format(lang)
+        global_config['Train']['dataset'][
+            'label_file_list'] = ["train_data/{}_train.txt".format(lang)]
+        global_config['Eval']['dataset'][
+            'label_file_list'] = ["train_data/{}_val.txt".format(lang)]
+        global_config['Global']['character_type'] = lang
+        assert (
+            os.path.isfile(
+                os.path.join(project_path, global_config['Global'][
+                    'character_dict_path']))
+        ), "Loss default dictionary file {}_dict.txt.You can download it from \
+https://github.com/PaddlePaddle/PaddleOCR/tree/dygraph/ppocr/utils/dict/".format(
+            lang)
+        return lang
 def merge_config(config):
@@ -110,43 +176,51 @@ def merge_config(config):
                    cur[sub_key] = value
                else:
                    cur = cur[sub_key]
 def loss_file(path):
-    assert(
+    assert (
-            os.path.exists(path)
+        os.path.exists(path)
-          ),"There is no such file:{},Please do not forget to put in the specified file".format(path)
+    ), "There is no such file:{},Please do not forget to put in the specified file".format(
+        path)
 if __name__ == '__main__':
    FLAGS = ArgsParser().parse_args()
    merge_config(FLAGS.opt)
    save_file_path = 'rec_{}_lite_train.yml'.format(FLAGS.language)
    if os.path.isfile(save_file_path):
        os.remove(save_file_path)
    if FLAGS.train:
        global_config['Train']['dataset']['label_file_list'] = [FLAGS.train]
-        train_label_path = os.path.join(project_path,FLAGS.train)
+        train_label_path = os.path.join(project_path, FLAGS.train)
        loss_file(train_label_path)
    if FLAGS.val:
        global_config['Eval']['dataset']['label_file_list'] = [FLAGS.val]
-        eval_label_path = os.path.join(project_path,FLAGS.val)
+        eval_label_path = os.path.join(project_path, FLAGS.val)
        loss_file(eval_label_path)
    if FLAGS.dict:
        global_config['Global']['character_dict_path'] = FLAGS.dict
-        dict_path = os.path.join(project_path,FLAGS.dict)
+        dict_path = os.path.join(project_path, FLAGS.dict)
        loss_file(dict_path)
    if FLAGS.data_dir:
        global_config['Eval']['dataset']['data_dir'] = FLAGS.data_dir
        global_config['Train']['dataset']['data_dir'] = FLAGS.data_dir
-        data_dir = os.path.join(project_path,FLAGS.data_dir)
+        data_dir = os.path.join(project_path, FLAGS.data_dir)
        loss_file(data_dir)
    with open(save_file_path, 'w') as f:
-        yaml.dump(dict(global_config), f, default_flow_style=False, sort_keys=False)
+        yaml.dump(
+            dict(global_config), f, default_flow_style=False, sort_keys=False)
    logging.info("Project path is          :{}".format(project_path))
-    logging.info("Train list path set to   :{}".format(global_config['Train']['dataset']['label_file_list'][0]))
+    logging.info("Train list path set to   :{}".format(global_config['Train'][
-    logging.info("Eval list path set to    :{}".format(global_config['Eval']['dataset']['label_file_list'][0]))
+        'dataset']['label_file_list'][0]))
-    logging.info("Dataset root path set to :{}".format(global_config['Eval']['dataset']['data_dir']))
+    logging.info("Eval list path set to    :{}".format(global_config['Eval'][
-    logging.info("Dict path set to         :{}".format(global_config['Global']['character_dict_path']))
+        'dataset']['label_file_list'][0]))
-    logging.info("Config file set to       :configs/rec/multi_language/{}".format(save_file_path))
+    logging.info("Dataset root path set to :{}".format(global_config['Eval'][
+        'dataset']['data_dir']))
+    logging.info("Dict path set to         :{}".format(global_config['Global'][
+        'character_dict_path']))
+    logging.info("Config file set to       :configs/rec/multi_language/{}".
+                 format(save_file_path))
--- a/configs/rec/multi_language/rec_arabic_lite_train.yml
+++ b/configs/rec/multi_language/rec_arabic_lite_train.yml
+Global:
+  use_gpu: true
+  epoch_num: 500
+  log_smooth_window: 20
+  print_batch_step: 10
+  save_model_dir: ./output/rec_arabic_lite
+  save_epoch_step: 3
+  eval_batch_step:
+  - 0
+  - 2000
+  cal_metric_during_train: true
+  pretrained_model: null
+  checkpoints: null
+  save_inference_dir: null
+  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
+Optimizer:
+  name: Adam
+  beta1: 0.9
+  beta2: 0.999
+  lr:
+    name: Cosine
+    learning_rate: 0.001
+  regularizer:
+    name: L2
+    factor: 1.0e-05
+Architecture:
+  model_type: rec
+  algorithm: CRNN
+  Transform: null
+  Backbone:
+    name: MobileNetV3
+    scale: 0.5
+    model_name: small
+    small_stride:
+    - 1
+    - 2
+    - 2
+    - 2
+  Neck:
+    name: SequenceEncoder
+    encoder_type: rnn
+    hidden_size: 48
+  Head:
+    name: CTCHead
+    fc_decay: 1.0e-05
+Loss:
+  name: CTCLoss
+PostProcess:
+  name: CTCLabelDecode
+Metric:
+  name: RecMetric
+  main_indicator: acc
+Train:
+  dataset:
+    name: SimpleDataSet
+    data_dir: train_data/
+    label_file_list:
+    - train_data/arabic_train.txt
+    transforms:
+    - DecodeImage:
+        img_mode: BGR
+        channel_first: false
+    - RecAug: null
+    - CTCLabelEncode: null
+    - RecResizeImg:
+        image_shape:
+        - 3
+        - 32
+        - 320
+    - KeepKeys:
+        keep_keys:
+        - image
+        - label
+        - length
+  loader:
+    shuffle: true
+    batch_size_per_card: 256
+    drop_last: true
+    num_workers: 8
+Eval:
+  dataset:
+    name: SimpleDataSet
+    data_dir: train_data/
+    label_file_list:
+    - train_data/arabic_val.txt
+    transforms:
+    - DecodeImage:
+        img_mode: BGR
+        channel_first: false
+    - CTCLabelEncode: null
+    - RecResizeImg:
+        image_shape:
+        - 3
+        - 32
+        - 320
+    - KeepKeys:
+        keep_keys:
+        - image
+        - label
+        - length
+  loader:
+    shuffle: false
+    drop_last: false
+    batch_size_per_card: 256
+    num_workers: 8
--- a/configs/rec/multi_language/rec_cyrillic_lite_train.yml
+++ b/configs/rec/multi_language/rec_cyrillic_lite_train.yml
+Global:
+  use_gpu: true
+  epoch_num: 500
+  log_smooth_window: 20
+  print_batch_step: 10
+  save_model_dir: ./output/rec_cyrillic_lite
+  save_epoch_step: 3
+  eval_batch_step:
+  - 0
+  - 2000
+  cal_metric_during_train: true
+  pretrained_model: null
+  checkpoints: null
+  save_inference_dir: null
+  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
+Optimizer:
+  name: Adam
+  beta1: 0.9
+  beta2: 0.999
+  lr:
+    name: Cosine
+    learning_rate: 0.001
+  regularizer:
+    name: L2
+    factor: 1.0e-05
+Architecture:
+  model_type: rec
+  algorithm: CRNN
+  Transform: null
+  Backbone:
+    name: MobileNetV3
+    scale: 0.5
+    model_name: small
+    small_stride:
+    - 1
+    - 2
+    - 2
+    - 2
+  Neck:
+    name: SequenceEncoder
+    encoder_type: rnn
+    hidden_size: 48
+  Head:
+    name: CTCHead
+    fc_decay: 1.0e-05
+Loss:
+  name: CTCLoss
+PostProcess:
+  name: CTCLabelDecode
+Metric:
+  name: RecMetric
+  main_indicator: acc
+Train:
+  dataset:
+    name: SimpleDataSet
+    data_dir: train_data/
+    label_file_list:
+    - train_data/cyrillic_train.txt
+    transforms:
+    - DecodeImage:
+        img_mode: BGR
+        channel_first: false
+    - RecAug: null
+    - CTCLabelEncode: null
+    - RecResizeImg:
+        image_shape:
+        - 3
+        - 32
+        - 320
+    - KeepKeys:
+        keep_keys:
+        - image
+        - label
+        - length
+  loader:
+    shuffle: true
+    batch_size_per_card: 256
+    drop_last: true
+    num_workers: 8
+Eval:
+  dataset:
+    name: SimpleDataSet
+    data_dir: train_data/
+    label_file_list:
+    - train_data/cyrillic_val.txt
+    transforms:
+    - DecodeImage:
+        img_mode: BGR
+        channel_first: false
+    - CTCLabelEncode: null
+    - RecResizeImg:
+        image_shape:
+        - 3
+        - 32
+        - 320
+    - KeepKeys:
+        keep_keys:
+        - image
+        - label
+        - length
+  loader:
+    shuffle: false
+    drop_last: false
+    batch_size_per_card: 256
+    num_workers: 8
--- a/configs/rec/multi_language/rec_devanagari_lite_train.yml
+++ b/configs/rec/multi_language/rec_devanagari_lite_train.yml
+Global:
+  use_gpu: true
+  epoch_num: 500
+  log_smooth_window: 20
+  print_batch_step: 10
+  save_model_dir: ./output/rec_devanagari_lite
+  save_epoch_step: 3
+  eval_batch_step:
+  - 0
+  - 2000
+  cal_metric_during_train: true
+  pretrained_model: null
+  checkpoints: null
+  save_inference_dir: null
+  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
+Optimizer:
+  name: Adam
+  beta1: 0.9
+  beta2: 0.999
+  lr:
+    name: Cosine
+    learning_rate: 0.001
+  regularizer:
+    name: L2
+    factor: 1.0e-05
+Architecture:
+  model_type: rec
+  algorithm: CRNN
+  Transform: null
+  Backbone:
+    name: MobileNetV3
+    scale: 0.5
+    model_name: small
+    small_stride:
+    - 1
+    - 2
+    - 2
+    - 2
+  Neck:
+    name: SequenceEncoder
+    encoder_type: rnn
+    hidden_size: 48
+  Head:
+    name: CTCHead
+    fc_decay: 1.0e-05
+Loss:
+  name: CTCLoss
+PostProcess:
+  name: CTCLabelDecode
+Metric:
+  name: RecMetric
+  main_indicator: acc
+Train:
+  dataset:
+    name: SimpleDataSet
+    data_dir: train_data/
+    label_file_list:
+    - train_data/devanagari_train.txt
+    transforms:
+    - DecodeImage:
+        img_mode: BGR
+        channel_first: false
+    - RecAug: null
+    - CTCLabelEncode: null
+    - RecResizeImg:
+        image_shape:
+        - 3
+        - 32
+        - 320
+    - KeepKeys:
+        keep_keys:
+        - image
+        - label
+        - length
+  loader:
+    shuffle: true
+    batch_size_per_card: 256
+    drop_last: true
+    num_workers: 8
+Eval:
+  dataset:
+    name: SimpleDataSet
+    data_dir: train_data/
+    label_file_list:
+    - train_data/devanagari_val.txt
+    transforms:
+    - DecodeImage:
+        img_mode: BGR
+        channel_first: false
+    - CTCLabelEncode: null
+    - RecResizeImg:
+        image_shape:
+        - 3
+        - 32
+        - 320
+    - KeepKeys:
+        keep_keys:
+        - image
+        - label
+        - length
+  loader:
+    shuffle: false
+    drop_last: false
+    batch_size_per_card: 256
+    num_workers: 8
--- a/configs/rec/multi_language/rec_en_number_lite_train.yml
+++ b/configs/rec/multi_language/rec_en_number_lite_train.yml
@@ -15,11 +15,11 @@ Global:
  use_visualdl: False
  infer_img:
  # for data or label process
-  character_dict_path: ppocr/utils/dict/en_dict.txt
+  character_dict_path: ppocr/utils/en_dict.txt
  character_type: EN
  max_text_length: 25
  infer_mode: False
-  use_space_char: False
+  use_space_char: True
 Optimizer:

--- a/configs/rec/multi_language/rec_latin_lite_train.yml
+++ b/configs/rec/multi_language/rec_latin_lite_train.yml
+Global:
+  use_gpu: true
+  epoch_num: 500
+  log_smooth_window: 20
+  print_batch_step: 10
+  save_model_dir: ./output/rec_latin_lite
+  save_epoch_step: 3
+  eval_batch_step:
+  - 0
+  - 2000
+  cal_metric_during_train: true
+  pretrained_model: null
+  checkpoints: null
+  save_inference_dir: null
+  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
+Optimizer:
+  name: Adam
+  beta1: 0.9
+  beta2: 0.999
+  lr:
+    name: Cosine
+    learning_rate: 0.001
+  regularizer:
+    name: L2
+    factor: 1.0e-05
+Architecture:
+  model_type: rec
+  algorithm: CRNN
+  Transform: null
+  Backbone:
+    name: MobileNetV3
+    scale: 0.5
+    model_name: small
+    small_stride:
+    - 1
+    - 2
+    - 2
+    - 2
+  Neck:
+    name: SequenceEncoder
+    encoder_type: rnn
+    hidden_size: 48
+  Head:
+    name: CTCHead
+    fc_decay: 1.0e-05
+Loss:
+  name: CTCLoss
+PostProcess:
+  name: CTCLabelDecode
+Metric:
+  name: RecMetric
+  main_indicator: acc
+Train:
+  dataset:
+    name: SimpleDataSet
+    data_dir: train_data/
+    label_file_list:
+    - train_data/latin_train.txt
+    transforms:
+    - DecodeImage:
+        img_mode: BGR
+        channel_first: false
+    - RecAug: null
+    - CTCLabelEncode: null
+    - RecResizeImg:
+        image_shape:
+        - 3
+        - 32
+        - 320
+    - KeepKeys:
+        keep_keys:
+        - image
+        - label
+        - length
+  loader:
+    shuffle: true
+    batch_size_per_card: 256
+    drop_last: true
+    num_workers: 8
+Eval:
+  dataset:
+    name: SimpleDataSet
+    data_dir: train_data/
+    label_file_list:
+    - train_data/latin_val.txt
+    transforms:
+    - DecodeImage:
+        img_mode: BGR
+        channel_first: false
+    - CTCLabelEncode: null
+    - RecResizeImg:
+        image_shape:
+        - 3
+        - 32
+        - 320
+    - KeepKeys:
+        keep_keys:
+        - image
+        - label
+        - length
+  loader:
+    shuffle: false
+    drop_last: false
+    batch_size_per_card: 256
+    num_workers: 8
--- a/deploy/cpp_infer/CMakeLists.txt
+++ b/deploy/cpp_infer/CMakeLists.txt
@@ -40,6 +40,7 @@ endif()
 if (WIN32)
  include_directories("${PADDLE_LIB}/paddle/fluid/inference")
  include_directories("${PADDLE_LIB}/paddle/include")
+  link_directories("${PADDLE_LIB}/paddle/lib")
  link_directories("${PADDLE_LIB}/paddle/fluid/inference")
  find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/build/ NO_DEFAULT_PATH)
@@ -140,22 +141,22 @@ else()
  endif ()
 endif()
-# Note: libpaddle_inference_api.so/a must put before libpaddle_fluid.so/a
+# Note: libpaddle_inference_api.so/a must put before libpaddle_inference.so/a
 if(WITH_STATIC_LIB)
  if(WIN32)
    set(DEPS
-        ${PADDLE_LIB}/paddle/lib/paddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
+        ${PADDLE_LIB}/paddle/lib/paddle_inference${CMAKE_STATIC_LIBRARY_SUFFIX})
  else()
    set(DEPS
-        ${PADDLE_LIB}/paddle/lib/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
+        ${PADDLE_LIB}/paddle/lib/libpaddle_inference${CMAKE_STATIC_LIBRARY_SUFFIX})
  endif()
 else()
  if(WIN32)
    set(DEPS
-        ${PADDLE_LIB}/paddle/lib/paddle_fluid${CMAKE_SHARED_LIBRARY_SUFFIX})
+        ${PADDLE_LIB}/paddle/lib/paddle_inference${CMAKE_SHARED_LIBRARY_SUFFIX})
  else()
    set(DEPS
-        ${PADDLE_LIB}/paddle/lib/libpaddle_fluid${CMAKE_SHARED_LIBRARY_SUFFIX})
+        ${PADDLE_LIB}/paddle/lib/libpaddle_inference${CMAKE_SHARED_LIBRARY_SUFFIX})
  endif()
 endif(WITH_STATIC_LIB)

--- a/deploy/cpp_infer/imgs/cpp_infer_pred_12.png
+++ b/deploy/cpp_infer/imgs/cpp_infer_pred_12.png
--- a/deploy/cpp_infer/readme.md
+++ b/deploy/cpp_infer/readme.md
@@ -74,9 +74,10 @@ opencv3/
 * 有2种方式获取Paddle预测库，下面进行详细介绍。
 #### 1.2.1 直接下载安装
-* [Paddle预测库官网](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/guides/05_inference_deployment/inference/build_and_install_lib_cn.html)上提供了不同cuda版本的Linux预测库，可以在官网查看并选择合适的预测库版本。
+* [Paddle预测库官网](https://www.paddlepaddle.org.cn/documentation/docs/zh/advanced_guide/inference_deployment/inference/build_and_install_lib_cn.html)上提供了不同cuda版本的Linux预测库，可以在官网查看并选择合适的预测库版本（*建议选择paddle版本>=2.0.1版本的预测库* ）。
 * 下载之后使用下面的方法解压。
@@ -130,8 +131,6 @@ build/paddle_inference_install_dir/
 其中`paddle`就是C++预测所需的Paddle库，`version.txt`中包含当前预测库的版本信息。
 ## 2 开始运行
 ### 2.1 将模型导出为inference model
@@ -232,7 +231,7 @@ visualize 1 # 是否对结果进行可视化，为1时，会在当前文件夹
 最终屏幕上会输出检测结果如下。
 <div align="center">
-    <img src="../imgs/cpp_infer_pred_12.png" width="600">
+    <img src="./imgs/cpp_infer_pred_12.png" width="600">
 </div>

--- a/deploy/cpp_infer/readme_en.md
+++ b/deploy/cpp_infer/readme_en.md
@@ -91,8 +91,8 @@ tar -xf paddle_inference.tgz
 Finally you can see the following files in the folder of `paddle_inference/`.
 #### 1.2.2 Compile from the source code
-* If you want to get the latest Paddle inference library features, you can download the latest code from Paddle github repository and compile the inference library from the source code.
+* If you want to get the latest Paddle inference library features, you can download the latest code from Paddle github repository and compile the inference library from the source code. It is recommended to download the inference library with paddle version greater than or equal to 2.0.1.
-* You can refer to [Paddle inference library] (https://www.paddlepaddle.org.cn/documentation/docs/en/develop/guides/05_inference_deployment/inference/build_and_install_lib_en.html) to get the Paddle source code from github, and then compile To generate the latest inference library. The method of using git to access the code is as follows.
+* You can refer to [Paddle inference library] (https://www.paddlepaddle.org.cn/documentation/docs/en/advanced_guide/inference_deployment/inference/build_and_install_lib_en.html) to get the Paddle source code from github, and then compile To generate the latest inference library. The method of using git to access the code is as follows.
 ```shell
@@ -238,7 +238,7 @@ visualize 1 # Whether to visualize the results，when it is set as 1, The predic
 The detection results will be shown on the screen, which is as follows.
 <div align="center">
-    <img src="../imgs/cpp_infer_pred_12.png" width="600">
+    <img src="./imgs/cpp_infer_pred_12.png" width="600">
 </div>

--- a/doc/doc_ch/inference.md
+++ b/doc/doc_ch/inference.md
@@ -13,7 +13,6 @@ inference 模型（`paddle.jit.save`保存的模型）
    - [检测模型转inference模型](#检测模型转inference模型)
    - [识别模型转inference模型](#识别模型转inference模型)  
    - [方向分类模型转inference模型](#方向分类模型转inference模型)
-    - [端到端模型转inference模型](#端到端模型转inference模型)
 - [二、文本检测模型推理](#文本检测模型推理)
    - [1. 超轻量中文检测模型推理](#超轻量中文检测模型推理)
@@ -28,13 +27,10 @@ inference 模型（`paddle.jit.save`保存的模型）
    - [4. 自定义文本识别字典的推理](#自定义文本识别字典的推理)
    - [5. 多语言模型的推理](#多语言模型的推理)
- [四、端到端模型推理](#端到端模型推理)
+- [四、方向分类模型推理](#方向识别模型推理)
-    - [1. PGNet端到端模型推理](#PGNet端到端模型推理)
- [五、方向分类模型推理](#方向识别模型推理)
    - [1. 方向分类模型推理](#方向分类模型推理)
- [六、文本检测、方向分类和文字识别串联推理](#文本检测、方向分类和文字识别串联推理)
+- [五、文本检测、方向分类和文字识别串联推理](#文本检测、方向分类和文字识别串联推理)
    - [1. 超轻量中文OCR模型推理](#超轻量中文OCR模型推理)
    - [2. 其他模型推理](#其他模型推理)
@@ -122,32 +118,6 @@ python3 tools/export_model.py -c configs/cls/cls_mv3.yml -o Global.pretrained_mo
    ├── inference.pdiparams.info    # 分类inference模型的参数信息，可忽略
    └── inference.pdmodel           # 分类inference模型的program文件
 ```
-<a name="端到端模型转inference模型"></a>
-### 端到端模型转inference模型
-下载端到端模型：
-```
-wget -P ./ch_lite/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_train.tar && tar xf ./ch_lite/ch_ppocr_mobile_v2.0_cls_train.tar -C ./ch_lite/
-```
-端到端模型转inference模型与检测的方式相同，如下：
-```
-# -c 后面设置训练算法的yml配置文件
-# -o 配置可选参数
-# Global.pretrained_model 参数设置待转换的训练模型地址，不用添加文件后缀 .pdmodel，.pdopt或.pdparams。
-# Global.load_static_weights 参数需要设置为 False。
-# Global.save_inference_dir参数设置转换的模型将保存的地址。
-python3 tools/export_model.py -c configs/e2e/e2e_r50_vd_pg.yml -o Global.pretrained_model=./ch_lite/ch_ppocr_mobile_v2.0_cls_train/best_accuracy Global.load_static_weights=False Global.save_inference_dir=./inference/e2e/
-```
-转换成功后，在目录下有三个文件：
-```
-/inference/e2e/
-    ├── inference.pdiparams         # 分类inference模型的参数文件
-    ├── inference.pdiparams.info    # 分类inference模型的参数信息，可忽略
-    └── inference.pdmodel           # 分类inference模型的program文件
-```
 <a name="文本检测模型推理"></a>
 ## 二、文本检测模型推理
@@ -362,38 +332,8 @@ python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/korean/1.jpg" -
 Predicts of ./doc/imgs_words/korean/1.jpg:('바탕으로', 0.9948904)
 ```
-<a name="端到端模型推理"></a>
-## 四、端到端模型推理
-端到端模型推理，默认使用PGNet模型的配置参数。当不使用PGNet模型时，在推理时，需要通过传入相应的参数进行算法适配，细节参考下文。
-<a name="PGNet端到端模型推理"></a>
-### 1. PGNet端到端模型推理
-#### (1). 四边形文本检测模型（ICDAR2015）  
-首先将PGNet端到端训练过程中保存的模型，转换成inference model。以基于Resnet50_vd骨干网络，在ICDAR2015英文数据集训练的模型为例([模型下载地址](https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/en_server_pgnetA.tar))，可以使用如下命令进行转换：
-```
-python3 tools/export_model.py -c configs/e2e/e2e_r50_vd_pg.yml -o Global.pretrained_model=./en_server_pgnetA/iter_epoch_450 Global.load_static_weights=False Global.save_inference_dir=./inference/e2e
-```
-**PGNet端到端模型推理，需要设置参数`--e2e_algorithm="PGNet"`**，可以执行如下命令：
-```
-python3 tools/infer/predict_e2e.py --e2e_algorithm="PGNet" --image_dir="./doc/imgs_en/img_10.jpg" --e2e_model_dir="./inference/e2e/"  --e2e_pgnet_polygon=False
-```
-可视化文本检测结果默认保存到`./inference_results`文件夹里面，结果文件的名称前缀为'e2e_res'。结果示例如下：
-![](../imgs_results/e2e_res_img_10_pgnet.jpg)
-#### (2). 弯曲文本检测模型（Total-Text）  
-和四边形文本检测模型共用一个推理模型
-**PGNet端到端模型推理，需要设置参数`--e2e_algorithm="PGNet"`，同时，还需要增加参数`--e2e_pgnet_polygon=True`，**可以执行如下命令：
-```
-python3.7 tools/infer/predict_e2e.py --e2e_algorithm="PGNet" --image_dir="./doc/imgs_en/img623.jpg" --e2e_model_dir="./inference/e2e/" --e2e_pgnet_polygon=True
-```
-可视化文本端到端结果默认保存到`./inference_results`文件夹里面，结果文件的名称前缀为'e2e_res'。结果示例如下：
-![](../imgs_results/e2e_res_img623_pgnet.jpg)
 <a name="方向分类模型推理"></a>
-## 五、方向分类模型推理
+## 四、方向分类模型推理
 下面将介绍方向分类模型推理。
@@ -418,7 +358,7 @@ Predicts of ./doc/imgs_words/ch/word_4.jpg:['0', 0.9999982]
 ```
 <a name="文本检测、方向分类和文字识别串联推理"></a>
-## 六、文本检测、方向分类和文字识别串联推理
+## 五、文本检测、方向分类和文字识别串联推理
 <a name="超轻量中文OCR模型推理"></a>
 ### 1. 超轻量中文OCR模型推理

--- a/doc/doc_ch/models_list.md
+++ b/doc/doc_ch/models_list.md
@@ -104,27 +104,16 @@ python3 generate_multi_language_configs.py -l it \
 | german_mobile_v2.0_rec |德文识别|[rec_german_lite_train.yml](../../configs/rec/multi_language/rec_german_lite_train.yml)|2.65M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_train.tar) |
 | korean_mobile_v2.0_rec |韩文识别|[rec_korean_lite_train.yml](../../configs/rec/multi_language/rec_korean_lite_train.yml)|3.9M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_train.tar) |
 | japan_mobile_v2.0_rec |日文识别|[rec_japan_lite_train.yml](../../configs/rec/multi_language/rec_japan_lite_train.yml)|4.23M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_train.tar) |
-| it_mobile_v2.0_rec |意大利文识别|rec_it_lite_train.yml|2.53M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/it_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/it_mobile_v2.0_rec_train.tar) |
-| xi_mobile_v2.0_rec |西班牙文识别|rec_xi_lite_train.yml|2.53M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/xi_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/xi_mobile_v2.0_rec_train.tar) |
-| pu_mobile_v2.0_rec |葡萄牙文识别|rec_pu_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/pu_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/pu_mobile_v2.0_rec_train.tar) |
-| ru_mobile_v2.0_rec |俄罗斯文识别|rec_ru_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ru_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ru_mobile_v2.0_rec_train.tar) |
-| ar_mobile_v2.0_rec |阿拉伯文识别|rec_ar_lite_train.yml|2.53M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ar_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ar_mobile_v2.0_rec_train.tar) |
-| hi_mobile_v2.0_rec |印地文识别|rec_hi_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/hi_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/hi_mobile_v2.0_rec_train.tar) |
 | chinese_cht_mobile_v2.0_rec |中文繁体识别|rec_chinese_cht_lite_train.yml|5.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_train.tar) |
-| ug_mobile_v2.0_rec |维吾尔文识别|rec_ug_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ug_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ug_mobile_v2.0_rec_train.tar) |
-| fa_mobile_v2.0_rec |波斯文识别|rec_fa_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/fa_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/fa_mobile_v2.0_rec_train.tar) |
-| ur_mobile_v2.0_rec |乌尔都文识别|rec_ur_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ur_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ur_mobile_v2.0_rec_train.tar) |
-| rs_mobile_v2.0_rec |塞尔维亚文（latin）识别|rec_rs_lite_train.yml|2.53M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/rs_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/rs_mobile_v2.0_rec_train.tar) |
-| oc_mobile_v2.0_rec |欧西坦文识别|rec_oc_lite_train.yml|2.53M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/oc_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/oc_mobile_v2.0_rec_train.tar) |
-| mr_mobile_v2.0_rec |马拉地文识别|rec_mr_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/mr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/mr_mobile_v2.0_rec_train.tar) |
-| ne_mobile_v2.0_rec |尼泊尔文识别|rec_ne_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ne_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ne_mobile_v2.0_rec_train.tar) |
-| rsc_mobile_v2.0_rec |塞尔维亚文（cyrillic）识别|rec_rsc_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/rsc_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/rsc_mobile_v2.0_rec_train.tar) |
-| bg_mobile_v2.0_rec |保加利亚文识别|rec_bg_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/bg_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/bg_mobile_v2.0_rec_train.tar) |
-| uk_mobile_v2.0_rec |乌克兰文识别|rec_uk_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/uk_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/uk_mobile_v2.0_rec_train.tar) |
-| be_mobile_v2.0_rec |白俄罗斯文识别|rec_be_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/be_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/be_mobile_v2.0_rec_train.tar) |
 | te_mobile_v2.0_rec |泰卢固文识别|rec_te_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_train.tar) |
 | ka_mobile_v2.0_rec |卡纳达文识别|rec_ka_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_train.tar) |
 | ta_mobile_v2.0_rec |泰米尔文识别|rec_ta_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_train.tar) |
+| latin_mobile_v2.0_rec |  拉丁文识别 |  [rec_latin_lite_train.yml](../../configs/rec/multi_language/rec_latin_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_train.tar) |
+| arabic_mobile_v2.0_rec |  阿拉伯字母 | [rec_arabic_lite_train.yml](../../configs/rec/multi_language/rec_arabic_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_train.tar) |
+| cyrillic_mobile_v2.0_rec | 斯拉夫字母 | [rec_cyrillic_lite_train.yml](../../configs/rec/multi_language/rec_cyrillic_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_train.tar) |
+| devanagari_mobile_v2.0_rec | 梵文字母 | [rec_devanagari_lite_train.yml](../../configs/rec/multi_language/rec_devanagari_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_train.tar) |
+更多支持语种请参考: [多语言模型](./multi_languages.md)
 <a name="文本方向分类模型"></a>