Merge branch 'dygraph' of https://github.com/PaddlePaddle/PaddleOCR into update_requirements

0cd2527c · WenmuZhou · df05d1fd · 479b7672 · 0cd2527c · 0cd2527c
Commit 0cd2527c authored Apr 15, 2021 by WenmuZhou
20 changed files
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -5,3 +5,4 @@ recursive-include ppocr/utils *.txt utility.py logging.py
 recursive-include ppocr/data/ *.py
 recursive-include ppocr/postprocess *.py
 recursive-include tools/infer *.py
+recursive-include ppocr/utils/e2e_utils/ *.py
\ No newline at end of file
--- a/PPOCRLabel/PPOCRLabel.py
+++ b/PPOCRLabel/PPOCRLabel.py
@@ -206,7 +206,7 @@ class MainWindow(QMainWindow, WindowMixin):
        self.labelList = EditInList()
        labelListContainer = QWidget()
        labelListContainer.setLayout(listLayout)
-        self.labelList.itemActivated.connect(self.labelSelectionChanged)
+        #self.labelList.itemActivated.connect(self.labelSelectionChanged)
        self.labelList.itemSelectionChanged.connect(self.labelSelectionChanged)
        self.labelList.clicked.connect(self.labelList.item_clicked)
        # Connect to itemChanged to detect checkbox changes.
@@ -219,7 +219,7 @@ class MainWindow(QMainWindow, WindowMixin):
        ################## detection box ####################
        self.BoxList = QListWidget()
-        self.BoxList.itemActivated.connect(self.boxSelectionChanged)
+        #self.BoxList.itemActivated.connect(self.boxSelectionChanged)
        self.BoxList.itemSelectionChanged.connect(self.boxSelectionChanged)
        self.BoxList.itemDoubleClicked.connect(self.editBox)
        # Connect to itemChanged to detect checkbox changes.
@@ -435,7 +435,7 @@ class MainWindow(QMainWindow, WindowMixin):
        ######## New actions #######
        AutoRec = action(getStr('autoRecognition'), self.autoRecognition,
-                      'Ctrl+Shift+A', 'Auto', getStr('autoRecognition'), enabled=False)
+                      '', 'Auto', getStr('autoRecognition'), enabled=False)
        reRec = action(getStr('reRecognition'), self.reRecognition, 
                      'Ctrl+Shift+R', 'reRec', getStr('reRecognition'), enabled=False)
@@ -444,7 +444,7 @@ class MainWindow(QMainWindow, WindowMixin):
                            'Ctrl+R', 'reRec', getStr('singleRe'), enabled=False)
        createpoly = action(getStr('creatPolygon'), self.createPolygon,
-                            'q', 'new', 'Creat Polygon', enabled=True)
+                            'q', 'new', getStr('creatPolygon'), enabled=True)
        saveRec = action(getStr('saveRec'), self.saveRecResult,
                            '', 'save', getStr('saveRec'), enabled=False)
@@ -452,6 +452,12 @@ class MainWindow(QMainWindow, WindowMixin):
        saveLabel = action(getStr('saveLabel'), self.saveLabelFile, #
                            'Ctrl+S', 'save', getStr('saveLabel'), enabled=False)
+        undoLastPoint = action(getStr("undoLastPoint"), self.canvas.undoLastPoint,
+                               'Ctrl+Z', "undo", getStr("undoLastPoint"), enabled=False)
+        undo = action(getStr("undo"), self.undoShapeEdit,
+                      'Ctrl+Z', "undo", getStr("undo"), enabled=False)
        self.editButton.setDefaultAction(edit)
        self.newButton.setDefaultAction(create)
        self.DelButton.setDefaultAction(deleteImg)
@@ -512,10 +518,11 @@ class MainWindow(QMainWindow, WindowMixin):
                              zoom=zoom, zoomIn=zoomIn, zoomOut=zoomOut, zoomOrg=zoomOrg,
                              fitWindow=fitWindow, fitWidth=fitWidth,
                              zoomActions=zoomActions, saveLabel=saveLabel,
+                              undo=undo, undoLastPoint=undoLastPoint,
                              fileMenuActions=(
                                  opendir, saveLabel,  resetAll, quit),
                              beginner=(), advanced=(),
-                              editMenu=(createpoly, edit, copy, delete,singleRere,
+                              editMenu=(createpoly, edit, copy, delete,singleRere,None, undo, undoLastPoint,
                                        None, color1, self.drawSquaresOption),
                              beginnerContext=(create, edit, copy, delete, singleRere),
                              advancedContext=(createMode, editMode, edit, copy,
@@ -549,8 +556,13 @@ class MainWindow(QMainWindow, WindowMixin):
        self.labelDialogOption.setChecked(settings.get(SETTING_PAINT_LABEL, False))
        self.labelDialogOption.triggered.connect(self.speedChoose)
+        self.autoSaveOption = QAction(getStr('autoSaveMode'), self)
+        self.autoSaveOption.setCheckable(True)
+        self.autoSaveOption.setChecked(settings.get(SETTING_PAINT_LABEL, False))
+        self.autoSaveOption.triggered.connect(self.autoSaveFunc)
        addActions(self.menus.file,
-                   (opendir, None, saveLabel, saveRec, None, resetAll, deleteImg, quit))
+                   (opendir, None, saveLabel, saveRec, self.autoSaveOption, None, resetAll, deleteImg, quit))
        addActions(self.menus.help, (showSteps, showInfo))
        addActions(self.menus.view, (
@@ -566,9 +578,9 @@ class MainWindow(QMainWindow, WindowMixin):
        # Custom context menu for the canvas widget:
        addActions(self.canvas.menus[0], self.actions.beginnerContext)
-        addActions(self.canvas.menus[1], (
+        #addActions(self.canvas.menus[1], (
-            action('&Copy here', self.copyShape),
+         #   action('&Copy here', self.copyShape),
-            action('&Move here', self.moveShape)))
+          #  action('&Move here', self.moveShape)))
        self.statusBar().showMessage('%s started.' % __appname__)
@@ -758,6 +770,7 @@ class MainWindow(QMainWindow, WindowMixin):
        self.canvas.setEditing(False)
        self.canvas.fourpoint = True
        self.actions.create.setEnabled(False)
+        self.actions.undoLastPoint.setEnabled(True)
    def toggleDrawingSensitive(self, drawing=True):
        """In the middle of drawing, toggling between modes should be disabled."""
@@ -866,10 +879,11 @@ class MainWindow(QMainWindow, WindowMixin):
            self.updateComboBox()
    def updateBoxlist(self):
-        shape = self.canvas.selectedShape
+        for shape in self.canvas.selectedShapes+[self.canvas.hShape]:
            item = self.shapesToItemsbox[shape]  # listitem
            text = [(int(p.x()), int(p.y())) for p in shape.points]
            item.setText(str(text))
+        self.actions.undo.setEnabled(True)
        self.setDirty()
    def indexTo5Files(self, currIndex):
@@ -902,23 +916,27 @@ class MainWindow(QMainWindow, WindowMixin):
        if len(self.mImgList) > 0:
            self.zoomWidget.setValue(self.zoomWidgetValue + self.imgsplider.value())
-    # React to canvas signals.
-    def shapeSelectionChanged(self, selected=False):
+    def shapeSelectionChanged(self, selected_shapes):
-        if self._noSelectionSlot:
+        self._noSelectionSlot = True
-            self._noSelectionSlot = False
+        for shape in self.canvas.selectedShapes:
-        else:
+            shape.selected = False
-            shape = self.canvas.selectedShape
-            if shape:
-                self.shapesToItems[shape].setSelected(True)
-                self.shapesToItemsbox[shape].setSelected(True)  # ADD
-            else:
        self.labelList.clearSelection()
-        self.actions.delete.setEnabled(selected)
+        self.canvas.selectedShapes = selected_shapes
-        self.actions.copy.setEnabled(selected)
+        for shape in self.canvas.selectedShapes:
-        self.actions.edit.setEnabled(selected)
+            shape.selected = True
-        self.actions.shapeLineColor.setEnabled(selected)
+            self.shapesToItems[shape].setSelected(True)
-        self.actions.shapeFillColor.setEnabled(selected)
+            self.shapesToItemsbox[shape].setSelected(True)
-        self.actions.singleRere.setEnabled(selected)
+        self.labelList.scrollToItem(self.currentItem()) # QAbstractItemView.EnsureVisible
+        self.BoxList.scrollToItem(self.currentBox())
+        self._noSelectionSlot = False
+        n_selected = len(selected_shapes)
+        self.actions.singleRere.setEnabled(n_selected)
+        self.actions.delete.setEnabled(n_selected)
+        self.actions.copy.setEnabled(n_selected)
+        self.actions.edit.setEnabled(n_selected == 1)
    def addLabel(self, shape):
        shape.paintLabel = self.displayLabelOption.isChecked()
@@ -941,10 +959,11 @@ class MainWindow(QMainWindow, WindowMixin):
            action.setEnabled(True)
        self.updateComboBox()
-    def remLabel(self, shape):
+    def remLabels(self, shapes):
-        if shape is None:
+        if shapes is None:
            # print('rm empty label')
            return
+        for shape in shapes:
            item = self.shapesToItems[shape]
            self.labelList.takeItem(self.labelList.row(item))
            del self.shapesToItems[shape]
@@ -1001,7 +1020,7 @@ class MainWindow(QMainWindow, WindowMixin):
        item.setText(str([(int(p.x()), int(p.y())) for p in shape.points]))
        self.updateComboBox()
-    def updateComboBox(self):
+    def updateComboBox(self): # TODO：貌似没用
        # Get the unique labels and add them to the Combobox.
        itemsTextList = [str(self.labelList.item(i).text()) for i in range(self.labelList.count())]
@@ -1054,26 +1073,38 @@ class MainWindow(QMainWindow, WindowMixin):
            return False
    def copySelectedShape(self):
-        self.addLabel(self.canvas.copySelectedShape())
+        for shape in self.canvas.copySelectedShape():
+            self.addLabel(shape)
        # fix copy and delete
-        self.shapeSelectionChanged(True)
+        #self.shapeSelectionChanged(True)
    def labelSelectionChanged(self):
-        item = self.currentItem()
+        if self._noSelectionSlot:
-        self.labelList.scrollToItem(item, QAbstractItemView.EnsureVisible)
+            return
-        if item and self.canvas.editing():
+        if self.canvas.editing():
-            self._noSelectionSlot = True
+            selected_shapes = []
-            self.canvas.selectShape(self.itemsToShapes[item])
+            for item in self.labelList.selectedItems():
-            shape = self.itemsToShapes[item]
+                selected_shapes.append(self.itemsToShapes[item])
+            if selected_shapes:
+                self.canvas.selectShapes(selected_shapes)
+            else:
+                self.canvas.deSelectShape()
    def boxSelectionChanged(self):
-        item = self.currentBox()
+        if self._noSelectionSlot:
-        self.BoxList.scrollToItem(item, QAbstractItemView.EnsureVisible)
+            #self.BoxList.scrollToItem(self.currentBox(), QAbstractItemView.PositionAtCenter)
-        if item and self.canvas.editing():
+            return
-            self._noSelectionSlot = True
+        if self.canvas.editing():
-            self.canvas.selectShape(self.itemsToShapesbox[item])
+            selected_shapes = []
-            shape = self.itemsToShapesbox[item]
+            for item in self.BoxList.selectedItems():
+                selected_shapes.append(self.itemsToShapesbox[item])
+            if selected_shapes:
+                self.canvas.selectShapes(selected_shapes)
+            else:
+                self.canvas.deSelectShape()
    def labelItemChanged(self, item):
        shape = self.itemsToShapes[item]
@@ -1113,6 +1144,8 @@ class MainWindow(QMainWindow, WindowMixin):
            if self.beginner():  # Switch to edit mode.
                self.canvas.setEditing(True)
                self.actions.create.setEnabled(True)
+                self.actions.undoLastPoint.setEnabled(False)
+                self.actions.undo.setEnabled(True)
            else:
                self.actions.editMode.setEnabled(True)
            self.setDirty()
@@ -1548,6 +1581,7 @@ class MainWindow(QMainWindow, WindowMixin):
                self.fileListWidget.insertItem(int(currIndex), item)
                self.openNextImg()
                self.actions.saveRec.setEnabled(True)
+                self.actions.saveLabel.setEnabled(True)
        elif mode == 'Auto':
            if annotationFilePath and self.saveLabels(annotationFilePath, mode=mode):
@@ -1643,7 +1677,8 @@ class MainWindow(QMainWindow, WindowMixin):
            self.setDirty()
    def deleteSelectedShape(self):
-        self.remLabel(self.canvas.deleteSelected())
+        self.remLabels(self.canvas.deleteSelected())
+        self.actions.undo.setEnabled(True)
        self.setDirty()
        if self.noShapes():
            for action in self.actions.onShapesPresent:
@@ -1653,7 +1688,7 @@ class MainWindow(QMainWindow, WindowMixin):
        color = self.colorDialog.getColor(self.lineColor, u'Choose line color',
                                          default=DEFAULT_LINE_COLOR)
        if color:
-            self.canvas.selectedShape.line_color = color
+            for shape in self.canvas.selectedShapes: shape.line_color = color
            self.canvas.update()
            self.setDirty()
@@ -1661,7 +1696,7 @@ class MainWindow(QMainWindow, WindowMixin):
        color = self.colorDialog.getColor(self.fillColor, u'Choose fill color',
                                          default=DEFAULT_FILL_COLOR)
        if color:
-            self.canvas.selectedShape.fill_color = color
+            for shape in self.canvas.selectedShapes: shape.fill_color = color
            self.canvas.update()
            self.setDirty()
@@ -1785,7 +1820,7 @@ class MainWindow(QMainWindow, WindowMixin):
    def singleRerecognition(self):
        img = cv2.imread(self.filePath)
-        shape = self.canvas.selectedShape
+        for shape in self.canvas.selectedShapes:
            box = [[int(p.x()), int(p.y())] for p in shape.points]
            assert len(box) == 4
            img_crop = get_rotate_crop_image(img, np.array(box, np.float32))
@@ -1914,8 +1949,8 @@ class MainWindow(QMainWindow, WindowMixin):
        self.savePPlabel()
    def saveRecResult(self):
-        if None in [self.PPlabelpath, self.PPlabel, self.fileStatedict]:
+        if {} in [self.PPlabelpath, self.PPlabel, self.fileStatedict]:
-            QMessageBox.information(self, "Information", "Save file first")
+            QMessageBox.information(self, "Information", "Check the image first")
            return
        rec_gt_dir = os.path.dirname(self.PPlabelpath) + '/rec_gt.txt'
@@ -1953,6 +1988,33 @@ class MainWindow(QMainWindow, WindowMixin):
            self.canvas.newShape.disconnect()
            self.canvas.newShape.connect(partial(self.newShape, False))
+    def autoSaveFunc(self):
+        if self.autoSaveOption.isChecked():
+            self.autoSaveNum = 1 # Real auto_Save
+            try:
+                self.saveLabelFile()
+            except:
+                pass
+            print('The program will automatically save once after confirming an image')
+        else:
+            self.autoSaveNum = 5 # Used for backup
+            print('The program will automatically save once after confirming 5 images (default)')
+    def undoShapeEdit(self):
+        self.canvas.restoreShape()
+        self.labelList.clear()
+        self.BoxList.clear()
+        self.loadShapes(self.canvas.shapes)
+        self.actions.undo.setEnabled(self.canvas.isShapeRestorable)
+    def loadShapes(self, shapes, replace=True):
+        self._noSelectionSlot = True
+        for shape in shapes:
+            self.addLabel(shape)
+        self.labelList.clearSelection()
+        self._noSelectionSlot = False
+        self.canvas.loadShapes(shapes, replace=replace)
 def inverted(color):
    return QColor(*[255 - v for v in color.getRgb()])

--- a/PPOCRLabel/README.md
+++ b/PPOCRLabel/README.md
@@ -8,6 +8,10 @@ PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field, w
 ### Recent Update
+- 2021.2.5: New batch processing and undo functions (by [Evezerest](https://github.com/Evezerest)):
+  - Batch processing function: Press and hold the Ctrl key to select the box, you can move, copy, and delete in batches.
+  - Undo function: In the process of drawing a four-point label box or after editing the box, press Ctrl+Z to undo the previous operation.
+  - Fix image rotation and size problems, optimize the process of editing the mark frame (by [ninetailskim](https://github.com/ninetailskim)、 [edencfc](https://github.com/edencfc)).
 - 2021.1.11: Optimize the labeling experience (by [edencfc](https://github.com/edencfc)),
  - Users can choose whether to pop up the label input dialog after drawing the detection box in "View - Pop-up Label Input Dialog".
  - The recognition result scrolls synchronously when users click related detection box.
@@ -16,7 +20,6 @@ PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field, w
 ### TODO:
 - Lock box mode: For the same scene data, the size and position of the locked detection box can be transferred between different pictures.
- Experience optimization: Add undo, batch operation include move, copy, delete and so on, optimize the annotation process.
 ## Installation
@@ -76,12 +79,11 @@ python3 PPOCRLabel.py
 7. Double click the result in 'recognition result' list to manually change inaccurate recognition results.
-8. Click "Check", the image status will switch to "√",then the program automatically jump to the next(The results will not be written directly to the file at this time).
+8. Click "Check", the image status will switch to "√",then the program automatically jump to the next.
 9. Click "Delete Image" and the image will be deleted to the recycle bin.
-10. Labeling result: the user can save manually through the menu "File - Save Label", while the program will also save automatically after every 5 images confirmed by the user.the manually checked label will be stored in *Label.txt* under the opened picture folder.
+10. Labeling result: the user can save manually through the menu "File - Save Label", while the program will also save automatically if "File - Auto Save Label Mode" is selected. The manually checked label will be stored in *Label.txt* under the opened picture folder. Click "PaddleOCR"-"Save Recognition Results" in the menu bar, the recognition training data of such pictures will be saved in the *crop_img* folder, and the recognition label will be saved in *rec_gt.txt*<sup>[4]</sup>.
-    Click "PaddleOCR"-"Save Recognition Results" in the menu bar, the recognition training data of such pictures will be saved in the *crop_img* folder, and the recognition label will be saved in *rec_gt.txt*<sup>[4]</sup>.
 ### Note
@@ -89,8 +91,7 @@ python3 PPOCRLabel.py
 [2] The image status indicates whether the user has saved the image manually. If it has not been saved manually it is "X", otherwise it is "√", PPOCRLabel will not relabel pictures with a status of "√".
-[3] After clicking "Re-recognize", the model will overwrite ALL recognition results in the picture.
+[3] After clicking "Re-recognize", the model will overwrite ALL recognition results in the picture. Therefore, if the recognition result has been manually changed before, it may change after re-recognition.
-Therefore, if the recognition result has been manually changed before, it may change after re-recognition.
 [4] The files produced by PPOCRLabel can be found under the opened picture folder including the following, please do not manually change the contents, otherwise it will cause the program to be abnormal.
@@ -107,13 +108,14 @@ Therefore, if the recognition result has been manually changed before, it may ch
 ### Shortcut keys
 | Shortcut keys            | Description                                      |
-| ---------------- | ------------------------------------------------ |
+| ------------------------ | ------------------------------------------------ |
-| Ctrl + shift + A | Automatically label all unchecked images         |
+| Ctrl + Shift + R         | Re-recognize all the labels of the current image |
-| Ctrl + shift + R | Re-recognize all the labels of the current image |
 | W                        | Create a rect box                                |
 | Q                        | Create a four-points box                         |
 | Ctrl + E                 | Edit label of the selected box                   |
 | Ctrl + R                 | Re-recognize the selected box                    |
+| Ctrl + C                 | Copy and paste the selected box                  |
+| Ctrl + Left Mouse Button | Multi select the label box                       |
 | Backspace                | Delete the selected box                          |
 | Ctrl + V                 | Check image                                      |
 | Ctrl + Shift + d         | Delete image                                     |
@@ -136,7 +138,7 @@ Therefore, if the recognition result has been manually changed before, it may ch
 PPOCRLabel supports three ways to save Label.txt
- Automatically save: When it detects that the user has manually checked 5 pictures, the program automatically writes the annotations into Label.txt. The user can change the value of ``self.autoSaveNum`` in ``PPOCRLabel.py`` to set the number of images to be automatically saved after confirmation.
+- Automatically save: After selecting "File - Auto Save Label Mode", the program will automatically write the annotations into Label.txt every time the user confirms an image. If this option is not turned on, it will be automatically saved after detecting that the user has manually checked 5 images.
 - Manual save: Click "File-Save Marking Results" to manually save the label.
 - Close application save

--- a/PPOCRLabel/README_ch.md
+++ b/PPOCRLabel/README_ch.md
@@ -8,6 +8,10 @@ PPOCRLabel是一款适用于OCR领域的半自动化图形标注工具，内置P
 #### 近期更新
+- 2021.2.5：新增批处理与撤销功能（by [Evezerest](https://github.com/Evezerest))
+  - 批处理功能：按住Ctrl键选择标记框后可批量移动、复制、删除。
+  - 撤销功能：在绘制四点标注框过程中或对框进行编辑操作后，按下Ctrl+Z可撤销上一部操作。
+  - 修复图像旋转和尺寸问题、优化编辑标记框过程（by [ninetailskim](https://github.com/ninetailskim)、 [edencfc](https://github.com/edencfc)）
 - 2021.1.11：优化标注体验（by [edencfc](https://github.com/edencfc)）：
  - 用户可在“视图 - 弹出标记输入框”选择在画完检测框后标记输入框是否弹出。
  - 识别结果与检测框同步滚动。
@@ -17,9 +21,8 @@ PPOCRLabel是一款适用于OCR领域的半自动化图形标注工具，内置P
 #### 尽请期待
 - 锁定框模式：针对同一场景数据，被锁定的检测框的大小与位置能在不同图片之间传递。
- 体验优化：增加撤销操作，批量移动、复制、删除等功能。优化标注流程。
-如果您对以上内容感兴趣或对完善工具有不一样的想法，欢迎加入我们的队伍与我们共同开发
+如果您对以上内容感兴趣或对完善工具有不一样的想法，欢迎加入我们的SIG队伍与我们共同开发。可以在[此处](https://github.com/PaddlePaddle/PaddleOCR/issues/1728)完成问卷和前置任务，经过我们确认相关内容后即可正式加入，享受SIG福利，共同为OCR开源事业贡献（特别说明：针对PPOCRLabel的改进也属于PaddleOCR前置任务）
 ## 安装
@@ -65,9 +68,9 @@ python3 PPOCRLabel.py --lang ch
 5. 标记框绘制完成后，用户点击 “确认”，检测框会先被预分配一个 “待识别” 标签。
 6. 重新识别：将图片中的所有检测画绘制/调整完成后，点击 “重新识别”，PPOCR模型会对当前图片中的**所有检测框**重新识别<sup>[3]</sup>。
 7. 内容更改：双击识别结果，对不准确的识别结果进行手动更改。
-8. 确认标记：点击 “确认”，图片状态切换为 “√”，跳转至下一张（此时不会直接将结果写入文件）。
+8. **确认标记**：点击 “确认”，图片状态切换为 “√”，跳转至下一张。
 9. 删除：点击 “删除图像”，图片将会被删除至回收站。
-10. 保存结果：用户可以通过菜单中“文件-保存标记结果”手动保存，同时程序也会在用户每确认5张图片后自动保存一次。手动确认过的标记将会被存放在所打开图片文件夹下的*Label.txt*中。在菜单栏点击 “文件” - "保存识别结果"后，会将此类图片的识别训练数据保存在*crop_img*文件夹下，识别标签保存在*rec_gt.txt*中<sup>[4]</sup>。
+10. 保存结果：用户可以通过菜单中“文件-保存标记结果”手动保存，同时也可以点击“文件 - 自动保存标记结果”开启自动保存。手动确认过的标记将会被存放在所打开图片文件夹下的*Label.txt*中。在菜单栏点击 “文件” - "保存识别结果"后，会将此类图片的识别训练数据保存在*crop_img*文件夹下，识别标签保存在*rec_gt.txt*中<sup>[4]</sup>。
 ### 注意
@@ -93,12 +96,13 @@ python3 PPOCRLabel.py --lang ch
 | 快捷键           | 说明                         |
 | ---------------- | ---------------------------- |
-| Ctrl + shift + A | 自动标注所有未确认过的图片   |
 | Ctrl + shift + R | 对当前图片的所有标记重新识别 |
 | W                | 新建矩形框                   |
 | Q                | 新建四点框                   |
 | Ctrl + E         | 编辑所选框标签               |
 | Ctrl + R         | 重新识别所选标记             |
+| Ctrl + C         | 复制并粘贴选中的标记框       |
+| Ctrl + 鼠标左键  | 多选标记框                   |
 | Backspace        | 删除所选框                   |
 | Ctrl + V         | 确认本张图片标记             |
 | Ctrl + Shift + d | 删除本张图片                 |
@@ -120,7 +124,7 @@ python3 PPOCRLabel.py --lang ch
 PPOCRLabel支持三种保存方式：
- 程序自动保存：当检测到用户手动确认过5张图片后，程序自动将标记结果写入Label.txt中。其中用户可通过更改```PPOCRLabel.py```中的```self.autoSaveNum```的数值设置确认几张图片后进行自动保存。
+- 自动保存：点击“文件 - 自动保存标记结果”后，用户每确认过一张图片，程序自动将标记结果写入Label.txt中。若未开启此选项，则检测到用户手动确认过5张图片后进行自动保存。
 - 手动保存：点击“文件 - 保存标记结果”手动保存标记。
 - 关闭应用程序保存

--- a/PPOCRLabel/libs/canvas.py
+++ b/PPOCRLabel/libs/canvas.py
@@ -37,7 +37,8 @@ class Canvas(QWidget):
    zoomRequest = pyqtSignal(int)
    scrollRequest = pyqtSignal(int, int)
    newShape = pyqtSignal()
-    selectionChanged = pyqtSignal(bool)
+    # selectionChanged = pyqtSignal(bool)
+    selectionChanged = pyqtSignal(list)
    shapeMoved = pyqtSignal()
    drawingPolygon = pyqtSignal(bool)
@@ -51,9 +52,11 @@ class Canvas(QWidget):
        # Initialise local state.
        self.mode = self.EDIT
        self.shapes = []
+        self.shapesBackups = []
        self.current = None
+        self.selectedShapes = []
        self.selectedShape = None  # save the selected shape here
-        self.selectedShapeCopy = None
+        self.selectedShapesCopy = []
        self.drawingLineColor = QColor(0, 0, 255)
        self.drawingRectColor = QColor(0, 0, 255)
        self.line = Shape(line_color=self.drawingLineColor)
@@ -77,6 +80,7 @@ class Canvas(QWidget):
        self.drawSquare = False
        self.fourpoint = True # ADD
        self.pointnum = 0
+        self.movingShape = False
        #initialisation for panning
        self.pan_initial_pos = QPoint()
@@ -149,37 +153,20 @@ class Canvas(QWidget):
                    clipped_x = min(max(0, pos.x()), size.width())
                    clipped_y = min(max(0, pos.y()), size.height())
                    pos = QPointF(clipped_x, clipped_y)
-                elif len(self.current) > 1 and self.closeEnough(pos, self.current[0]) and not self.fourpoint:
+                elif len(self.current) > 1 and self.closeEnough(pos, self.current[0]):
                    # Attract line to starting point and colorise to alert the
                    # user:
                    pos = self.current[0]
                    color = self.current.line_color
                    self.overrideCursor(CURSOR_POINT)
                    self.current.highlightVertex(0, Shape.NEAR_VERTEX)
-                elif ( # ADD
-                        len(self.current) > 1
-                        and self.fourpoint
-                        and self.closeEnough(pos, self.current[0])
-                ):
-                    # Attract line to starting point and
-                    # colorise to alert the user.
-                    pos = self.current[0]
-                    self.overrideCursor(CURSOR_POINT)
-                    self.current.highlightVertex(0, Shape.NEAR_VERTEX)
                if self.drawSquare:
-                    initPos = self.current[0]
+                    self.line.points = [self.current[0], pos]
-                    minX = initPos.x()
+                    self.line.close()
-                    minY = initPos.y()
-                    min_size = min(abs(pos.x() - minX), abs(pos.y() - minY))
-                    directionX = -1 if pos.x() - minX < 0 else 1
-                    directionY = -1 if pos.y() - minY < 0 else 1
-                    self.line[1] = QPointF(minX + directionX * min_size, minY + directionY * min_size)
                elif self.fourpoint:
-                    # self.line[self.pointnum] = pos # OLD
                    self.line[0] = self.current[-1]
                    self.line[1] = pos
@@ -196,12 +183,14 @@ class Canvas(QWidget):
        # Polygon copy moving.
        if Qt.RightButton & ev.buttons():
-            if self.selectedShapeCopy and self.prevPoint:
+            if self.selectedShapesCopy and self.prevPoint:
                self.overrideCursor(CURSOR_MOVE)
-                self.boundedMoveShape(self.selectedShapeCopy, pos)
+                self.boundedMoveShape(self.selectedShapesCopy, pos)
                self.repaint()
-            elif self.selectedShape:
+            elif self.selectedShapes:
-                self.selectedShapeCopy = self.selectedShape.copy()
+                self.selectedShapesCopy = [
+                    s.copy() for s in self.selectedShapes
+                ]
                self.repaint()
            return
@@ -211,11 +200,13 @@ class Canvas(QWidget):
                self.boundedMoveVertex(pos)
                self.shapeMoved.emit()
                self.repaint()
-            elif self.selectedShape and self.prevPoint:
+                self.movingShape = True
+            elif self.selectedShapes and self.prevPoint:
                self.overrideCursor(CURSOR_MOVE)
-                self.boundedMoveShape(self.selectedShape, pos)
+                self.boundedMoveShape(self.selectedShapes, pos)
                self.shapeMoved.emit()
                self.repaint()
+                self.movingShape = True
            else:
                #pan
                delta_x = pos.x() - self.pan_initial_pos.x()
@@ -263,65 +254,60 @@ class Canvas(QWidget):
    def mousePressEvent(self, ev):
        pos = self.transformPos(ev.pos())
        if ev.button() == Qt.LeftButton:
            if self.drawing():
                # self.handleDrawing(pos) # OLD
+                if self.current:
+                    if self.fourpoint: # ADD IF
-                if self.current and self.fourpoint: # ADD IF
                        # Add point to existing shape.
-                    print('Adding points in mousePressEvent is ', self.line[1])
+                        # print('Adding points in mousePressEvent is ', self.line[1])
                        self.current.addPoint(self.line[1])
                        self.line[0] = self.current[-1]
                        if self.current.isClosed():
                            # print('1111')
                            self.finalise()
+                    elif self.drawSquare: # 增加
+                        assert len(self.current.points) == 1
+                        self.current.points = self.line.points
+                        self.finalise()
                elif not self.outOfPixmap(pos):
                    # Create new shape.
-                    self.current = Shape()# self.current = Shape(shape_type=self.createMode)
+                    self.current = Shape()
                    self.current.addPoint(pos)
-                    # if self.createMode == "point":
-                    #     self.finalise()
-                    # else:
-                    #     if self.createMode == "circle":
-                    #         self.current.shape_type = "circle"
                    self.line.points = [pos, pos]
                    self.setHiding()
                    self.drawingPolygon.emit(True)
                    self.update()
            else:
-                selection = self.selectShapePoint(pos)
+                group_mode = int(ev.modifiers()) == Qt.ControlModifier
+                self.selectShapePoint(pos, multiple_selection_mode=group_mode)
                self.prevPoint = pos
-                if selection is None:
-                    #pan
-                    QApplication.setOverrideCursor(QCursor(Qt.OpenHandCursor))
                self.pan_initial_pos = pos
        elif ev.button() == Qt.RightButton and self.editing():
-            self.selectShapePoint(pos)
+            group_mode = int(ev.modifiers()) == Qt.ControlModifier
+            self.selectShapePoint(pos, multiple_selection_mode=group_mode)
            self.prevPoint = pos
        self.update()
    def mouseReleaseEvent(self, ev):
        if ev.button() == Qt.RightButton:
-            menu = self.menus[bool(self.selectedShapeCopy)]
+            menu = self.menus[bool(self.selectedShapesCopy)]
            self.restoreCursor()
            if not menu.exec_(self.mapToGlobal(ev.pos()))\
-               and self.selectedShapeCopy:
+               and self.selectedShapesCopy:
                # Cancel the move by deleting the shadow copy.
-                self.selectedShapeCopy = None
+                # self.selectedShapeCopy = None
+                self.selectedShapesCopy = []
                self.repaint()
-        elif ev.button() == Qt.LeftButton and self.selectedShape: # OLD
+        elif ev.button() == Qt.LeftButton and self.selectedShapes:
            if self.selectedVertex():
                self.overrideCursor(CURSOR_POINT)
            else:
                self.overrideCursor(CURSOR_GRAB)
        elif ev.button() == Qt.LeftButton and not self.fourpoint:
            pos = self.transformPos(ev.pos())
            if self.drawing():
@@ -330,24 +316,37 @@ class Canvas(QWidget):
                #pan
                QApplication.restoreOverrideCursor() # ?
+        if self.movingShape and self.hShape:
+             index = self.shapes.index(self.hShape)
+             if (
+                 self.shapesBackups[-1][index].points
+                 != self.shapes[index].points
+             ):
+                 self.storeShapes()
+                 self.shapeMoved.emit() # connect to updateBoxlist in PPOCRLabel.py
+             self.movingShape = False
    def endMove(self, copy=False):
-        assert self.selectedShape and self.selectedShapeCopy
+        assert self.selectedShapes and self.selectedShapesCopy
-        shape = self.selectedShapeCopy
+        assert len(self.selectedShapesCopy) == len(self.selectedShapes)
-        #del shape.fill_color
-        #del shape.line_color
        if copy:
+            for i, shape in enumerate(self.selectedShapesCopy):
                self.shapes.append(shape)
-            self.selectedShape.selected = False
+                self.selectedShapes[i].selected = False
-            self.selectedShape = shape
+                self.selectedShapes[i] = shape
-            self.repaint()
        else:
-            self.selectedShape.points = [p for p in shape.points]
+            for i, shape in enumerate(self.selectedShapesCopy):
-        self.selectedShapeCopy = None
+                self.selectedShapes[i].points = shape.points
+        self.selectedShapesCopy = []
+        self.repaint()
+        self.storeShapes()
+        return True
    def hideBackroundShapes(self, value):
        self.hideBackround = value
-        if self.selectedShape:
+        if self.selectedShapes:
            # Only hide other shapes if there is a current selection.
            # Otherwise the user will not be able to select a shape.
            self.setHiding(True)
@@ -363,7 +362,7 @@ class Canvas(QWidget):
                if self.pointnum == 3:
                    self.finalise()
-            else: # 按住送掉后跳到这里
+            else:
                initPos = self.current[0]
                print('initPos', self.current[0])
                minX = initPos.x()
@@ -399,28 +398,33 @@ class Canvas(QWidget):
                self.current.popPoint()
            self.finalise()
-    def selectShape(self, shape):
+    def selectShapes(self, shapes):
-        self.deSelectShape()
+        for s in shapes: s.seleted = True
-        shape.selected = True
-        self.selectedShape = shape
        self.setHiding()
-        self.selectionChanged.emit(True)
+        self.selectionChanged.emit(shapes)
        self.update()
-    def selectShapePoint(self, point):
+    def selectShapePoint(self, point, multiple_selection_mode):
        """Select the first shape created which contains this point."""
-        self.deSelectShape()
        if self.selectedVertex():  # A vertex is marked for selection.
            index, shape = self.hVertex, self.hShape
            shape.highlightVertex(index, shape.MOVE_VERTEX)
-            self.selectShape(shape)
            return self.hVertex
+        else:
            for shape in reversed(self.shapes):
                if self.isVisible(shape) and shape.containsPoint(point):
-                self.selectShape(shape)
                    self.calculateOffsets(shape, point)
-                return self.selectedShape
+                    self.setHiding()
-        return None
+                    if multiple_selection_mode:
+                        if shape not in self.selectedShapes: # list
+                            self.selectionChanged.emit(
+                                self.selectedShapes + [shape]
+                            )
+                    else:
+                        self.selectionChanged.emit([shape])
+                    return
+        self.deSelectShape()
    def calculateOffsets(self, shape, point):
        rect = shape.boundingRect()
@@ -465,8 +469,9 @@ class Canvas(QWidget):
        else:
            shiftPos = pos - point
+        if [shape[0].x(), shape[0].y(), shape[2].x(), shape[2].y()] \
+                == [shape[3].x(),shape[1].y(),shape[1].x(),shape[3].y()]:
            shape.moveVertexBy(index, shiftPos)
            lindex = (index + 1) % 4
            rindex = (index + 3) % 4
            lshift = None
@@ -480,7 +485,12 @@ class Canvas(QWidget):
            shape.moveVertexBy(rindex, rshift)
            shape.moveVertexBy(lindex, lshift)
-    def boundedMoveShape(self, shape, pos):
+        else:
+            shape.moveVertexBy(index, shiftPos)
+    def boundedMoveShape(self, shapes, pos):
+        if type(shapes).__name__ != 'list': shapes = [shapes]
        if self.outOfPixmap(pos):
            return False  # No need to move
        o1 = pos + self.offsets[0]
@@ -497,40 +507,49 @@ class Canvas(QWidget):
        #self.calculateOffsets(self.selectedShape, pos)
        dp = pos - self.prevPoint
        if dp:
+            for shape in shapes:
                shape.moveBy(dp)
            self.prevPoint = pos
            return True
        return False
    def deSelectShape(self):
-        if self.selectedShape:
+        if self.selectedShapes:
-            self.selectedShape.selected = False
+            for shape in self.selectedShapes: shape.selected=False
-            self.selectedShape = None
            self.setHiding(False)
-            self.selectionChanged.emit(False)
+            self.selectionChanged.emit([])
            self.update()
    def deleteSelected(self):
-        if self.selectedShape:
+        deleted_shapes = []
-            shape = self.selectedShape
+        if self.selectedShapes:
-            self.shapes.remove(self.selectedShape)
+            for shape in self.selectedShapes:
-            self.selectedShape = None
+                self.shapes.remove(shape)
+                deleted_shapes.append(shape)
+            self.storeShapes()
+            self.selectedShapes = []
            self.update()
-            return shape
+        return deleted_shapes
+    def storeShapes(self):
+        shapesBackup = []
+        for shape in self.shapes:
+            shapesBackup.append(shape.copy())
+        if len(self.shapesBackups) >= 10:
+            self.shapesBackups = self.shapesBackups[-9:]
+        self.shapesBackups.append(shapesBackup)
    def copySelectedShape(self):
-        if self.selectedShape:
+        if self.selectedShapes:
-            shape = self.selectedShape.copy()
+            self.selectedShapesCopy = [s.copy() for s in self.selectedShapes]
-            self.deSelectShape()
+            self.boundedShiftShapes(self.selectedShapesCopy)
-            self.shapes.append(shape)
+            self.endMove(copy=True)
-            shape.selected = True
+        return self.selectedShapes
-            self.selectedShape = shape
-            self.boundedShiftShape(shape)
-            return shape
-    def boundedShiftShape(self, shape):
+    def boundedShiftShapes(self, shapes):
        # Try to move in one direction, and if it fails in another.
        # Give up if both fail.
+        for shape in shapes:
            point = shape[0]
            offset = QPointF(2.0, 2.0)
            self.calculateOffsets(shape, point)
@@ -560,8 +579,9 @@ class Canvas(QWidget):
        if self.current:
            self.current.paint(p)
            self.line.paint(p)
-        if self.selectedShapeCopy:
+        if self.selectedShapesCopy:
-            self.selectedShapeCopy.paint(p)
+            for s in self.selectedShapesCopy:
+                s.paint(p)
        # Paint rect
        if self.current is not None and len(self.line) == 2 and not self.fourpoint:
@@ -739,6 +759,7 @@ class Canvas(QWidget):
        if fill_color:
            self.shapes[-1].fill_color = fill_color
+        self.storeShapes()
        return self.shapes[-1]
@@ -749,6 +770,17 @@ class Canvas(QWidget):
        self.line.points = [self.current[-1], self.current[0]]
        self.drawingPolygon.emit(True)
+    def undoLastPoint(self):
+        if not self.current or self.current.isClosed():
+            return
+        self.current.popPoint()
+        if len(self.current) > 0:
+            self.line[0] = self.current[-1]
+        else:
+            self.current = None
+            self.drawingPolygon.emit(False)
+        self.repaint()
    def resetAllLines(self):
        assert self.shapes
        self.current = self.shapes.pop()
@@ -762,11 +794,18 @@ class Canvas(QWidget):
    def loadPixmap(self, pixmap):
        self.pixmap = pixmap
        self.shapes = []
-        self.repaint() # 这函数在哪
+        self.repaint()
-    def loadShapes(self, shapes):
+    def loadShapes(self, shapes, replace=True):
+        if replace:
            self.shapes = list(shapes)
+        else:
+            self.shapes.extend(shapes)
        self.current = None
+        self.hShape = None
+        self.hVertex = None
+        # self.hEdge = None
+        self.storeShapes()
        self.repaint()
    def setShapeVisible(self, shape, value):
@@ -793,6 +832,24 @@ class Canvas(QWidget):
        self.restoreCursor()
        self.pixmap = None
        self.update()
+        self.shapesBackups = []
    def setDrawingShapeToSquare(self, status):
        self.drawSquare = status
+    def restoreShape(self):
+        if not self.isShapeRestorable:
+            return
+        self.shapesBackups.pop()  # latest
+        shapesBackup = self.shapesBackups.pop()
+        self.shapes = shapesBackup
+        self.selectedShapes = []
+        for shape in self.shapes:
+            shape.selected = False
+        self.repaint()
+    @property
+    def isShapeRestorable(self):
+        if len(self.shapesBackups) < 2:
+            return False
+        return True
\ No newline at end of file
--- a/PPOCRLabel/libs/resources.py
+++ b/PPOCRLabel/libs/resources.py
--- a/PPOCRLabel/libs/shape.py
+++ b/PPOCRLabel/libs/shape.py
@@ -82,7 +82,7 @@ class Shape(object):
        return False
    def addPoint(self, point):
-        if not self.reachMaxPoints():
+        if not self.reachMaxPoints():  # 4个点时发出close信号
            self.points.append(point)
    def popPoint(self):

--- a/PPOCRLabel/resources/strings/strings-zh-CN.properties
+++ b/PPOCRLabel/resources/strings/strings-zh-CN.properties
@@ -97,3 +97,6 @@ showBox=显示所有标注
 saveLabel=保存标记结果
 singleRe=重识别此区块
 labelDialogOption=弹出标记输入框
+undo=撤销
+undoLastPoint=撤销上个点
+autoSaveMode=自动保存标记结果
\ No newline at end of file
--- a/PPOCRLabel/resources/strings/strings.properties
+++ b/PPOCRLabel/resources/strings/strings.properties
@@ -97,3 +97,6 @@ showBox=Show All Box
 saveLabel=Save Label
 singleRe=Re-recognition RectBox
 labelDialogOption=Pop-up Label Input Dialog
+undo=Undo
+undoLastPoint=Undo Last Point
+autoSaveMode=Auto Save Label Mode
\ No newline at end of file
--- a/README.md
+++ b/README.md
@@ -42,7 +42,7 @@ The above pictures are the visualizations of the general ppocr_server model. For
 - Scan the QR code below with your Wechat, you can access to official technical exchange group. Look forward to your participation.
 <div align="center">
-<img src="./doc/joinus.PNG"  width = "200" height = "200" />
+<img src="https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.0/doc/joinus.PNG"  width = "200" height = "200" />
 </div>
@@ -93,7 +93,7 @@ For a new language request, please refer to [Guideline for new language_requests
    - [Quick Inference Based on PIP](./doc/doc_en/whl_en.md)
    - [Python Inference](./doc/doc_en/inference_en.md)
    - [C++ Inference](./deploy/cpp_infer/readme_en.md)
-    - [Serving](./deploy/hubserving/readme_en.md)
+    - [Serving](./deploy/pdserving/README.md)
    - [Mobile](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/lite/readme_en.md)
    - [Benchmark](./doc/doc_en/benchmark_en.md)  
 - Data Annotation and Synthesis

--- a/README_ch.md
+++ b/README_ch.md
@@ -8,9 +8,10 @@ PaddleOCR同时支持动态图与静态图两种编程范式
 - 静态图版本：develop分支
 **近期更新**
+- 【预告】 PaddleOCR研发团队对最新发版内容技术深入解读，4月13日晚上19:00，[直播地址](https://live.bilibili.com/21689802)
+- 2021.4.8 release 2.1版本，新增AAAI 2021论文[端到端识别算法PGNet](./doc/doc_ch/pgnet.md)开源，[多语言模型](./doc/doc_ch/multi_languages.md)支持种类增加到80+。
 - 2021.2.1 [FAQ](./doc/doc_ch/FAQ.md)新增5个高频问题，总数162个，每周一都会更新，欢迎大家持续关注。
- 2021.1.26,28,29 PaddleOCR官方研发团队带来技术深入解读三日直播课，1月26日、28日、29日晚上19:30，[直播地址](https://live.bilibili.com/21689802)
+- 2021.1.21 更新多语言识别模型，目前支持语种超过27种，包括中文简体、中文繁体、英文、法文、德文、韩文、日文、意大利文、西班牙文、葡萄牙文、俄罗斯文、阿拉伯文等，后续计划可以参考[多语言研发计划](https://github.com/PaddlePaddle/PaddleOCR/issues/1048)
- 2021.1.21 更新多语言识别模型，目前支持语种超过27种，[多语言模型下载](./doc/doc_ch/models_list.md)，包括中文简体、中文繁体、英文、法文、德文、韩文、日文、意大利文、西班牙文、葡萄牙文、俄罗斯文、阿拉伯文等，后续计划可以参考[多语言研发计划](https://github.com/PaddlePaddle/PaddleOCR/issues/1048)
 - 2020.12.15 更新数据合成工具[Style-Text](./StyleText/README_ch.md)，可以批量合成大量与目标场景类似的图像，在多个场景验证，效果明显提升。
 - 2020.11.25 更新半自动标注工具[PPOCRLabel](./PPOCRLabel/README_ch.md)，辅助开发者高效完成标注任务，输出格式与PP-OCR训练任务完美衔接。
 - 2020.9.22 更新PP-OCR技术文章，https://arxiv.org/abs/2009.09941
@@ -46,7 +47,7 @@ PaddleOCR同时支持动态图与静态图两种编程范式
 - 微信扫描二维码加入官方交流群，获得更高效的问题答疑，与各行各业开发者充分交流，期待您的加入。
 <div align="center">
-<img src="./doc/joinus.PNG"  width = "200" height = "200" />
+<img src="https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.0/doc/joinus.PNG"  width = "200" height = "200" />
 </div>
 ## 快速体验
@@ -74,11 +75,13 @@ PaddleOCR同时支持动态图与静态图两种编程范式
 ## 文档教程
 - [快速安装](./doc/doc_ch/installation.md)
 - [中文OCR模型快速使用](./doc/doc_ch/quickstart.md)
+- [多语言OCR模型快速使用](./doc/doc_ch/multi_languages.md)
 - [代码组织结构](./doc/doc_ch/tree.md)
 - 算法介绍
    - [文本检测](./doc/doc_ch/algorithm_overview.md)
    - [文本识别](./doc/doc_ch/algorithm_overview.md)
    - [PP-OCR Pipline](#PP-OCR)
+    - [端到端PGNet算法](./doc/doc_ch/pgnet.md)
 - 模型训练/评估
    - [文本检测](./doc/doc_ch/detection.md)
    - [文本识别](./doc/doc_ch/recognition.md)
@@ -88,7 +91,7 @@ PaddleOCR同时支持动态图与静态图两种编程范式
    - [基于pip安装whl包快速推理](./doc/doc_ch/whl.md)
    - [基于Python脚本预测引擎推理](./doc/doc_ch/inference.md)
    - [基于C++预测引擎推理](./deploy/cpp_infer/readme.md)
-    - [服务化部署](./deploy/hubserving/readme.md)
+    - [服务化部署](./deploy/pdserving/README_CN.md)
    - [端侧部署](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/deploy/lite/readme.md)
    - [Benchmark](./doc/doc_ch/benchmark.md)
 - 数据集

--- a/StyleText/engine/predictors.py
+++ b/StyleText/engine/predictors.py
@@ -38,7 +38,15 @@ class StyleTextRecPredictor(object):
        self.std = config["Predictor"]["std"]
        self.expand_result = config["Predictor"]["expand_result"]
-    def predict(self, style_input, text_input):
+    def reshape_to_same_height(self, img_list):
+        h = img_list[0].shape[0]
+        for idx in range(1, len(img_list)):
+            new_w = round(1.0 * img_list[idx].shape[1] /
+                          img_list[idx].shape[0] * h)
+            img_list[idx] = cv2.resize(img_list[idx], (new_w, h))
+        return img_list
+    def predict_single_image(self, style_input, text_input):
        style_input = self.rep_style_input(style_input, text_input)
        tensor_style_input = self.preprocess(style_input)
        tensor_text_input = self.preprocess(text_input)
@@ -64,6 +72,21 @@ class StyleTextRecPredictor(object):
            "fake_bg": fake_bg,
        }
+    def predict(self, style_input, text_input_list):
+        if not isinstance(text_input_list, (tuple, list)):
+            return self.predict_single_image(style_input, text_input_list)
+        synth_result_list = []
+        for text_input in text_input_list:
+            synth_result = self.predict_single_image(style_input, text_input)
+            synth_result_list.append(synth_result)
+        for key in synth_result:
+            res = [r[key] for r in synth_result_list]
+            res = self.reshape_to_same_height(res)
+            synth_result[key] = np.concatenate(res, axis=1)
+        return synth_result
    def preprocess(self, img):
        img = (img.astype('float32') * self.scale - self.mean) / self.std
        img_height, img_width, channel = img.shape

--- a/StyleText/engine/synthesisers.py
+++ b/StyleText/engine/synthesisers.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
+import numpy as np
+import cv2
 from utils.config import ArgsParser, load_config, override_config
 from utils.logging import get_logger
@@ -36,8 +38,9 @@ class ImageSynthesiser(object):
        self.predictor = getattr(predictors, predictor_method)(self.config)
    def synth_image(self, corpus, style_input, language="en"):
-        corpus, text_input = self.text_drawer.draw_text(corpus, language)
+        corpus_list, text_input_list = self.text_drawer.draw_text(
-        synth_result = self.predictor.predict(style_input, text_input)
+            corpus, language, style_input_width=style_input.shape[1])
+        synth_result = self.predictor.predict(style_input, text_input_list)
        return synth_result
@@ -59,12 +62,15 @@ class DatasetSynthesiser(ImageSynthesiser):
        for i in range(self.output_num):
            style_data = self.style_sampler.sample()
            style_input = style_data["image"]
-            corpus_language, text_input_label = self.corpus_generator.generate(
+            corpus_language, text_input_label = self.corpus_generator.generate()
-            )
+            text_input_label_list, text_input_list = self.text_drawer.draw_text(
-            text_input_label, text_input = self.text_drawer.draw_text(
+                text_input_label,
-                text_input_label, corpus_language)
+                corpus_language,
+                style_input_width=style_input.shape[1])
-            synth_result = self.predictor.predict(style_input, text_input)
+            text_input_label = "".join(text_input_label_list)
+            synth_result = self.predictor.predict(style_input, text_input_list)
            fake_fusion = synth_result["fake_fusion"]
            self.writer.save_image(fake_fusion, text_input_label)
        self.writer.save_label()

--- a/StyleText/engine/text_drawers.py
+++ b/StyleText/engine/text_drawers.py
 from PIL import Image, ImageDraw, ImageFont
 import numpy as np
+import cv2
 from utils.logging import get_logger
@@ -28,7 +29,11 @@ class StdTextDrawer(object):
        else:
            return int((self.height - 4)**2 / font_height)
-    def draw_text(self, corpus, language="en", crop=True):
+    def draw_text(self,
+                  corpus,
+                  language="en",
+                  crop=True,
+                  style_input_width=None):
        if language not in self.support_languages:
            self.logger.warning(
                "language {} not supported, use en instead.".format(language))
@@ -37,21 +42,43 @@ class StdTextDrawer(object):
            width = min(self.max_width, len(corpus) * self.height) + 4
        else:
            width = len(corpus) * self.height + 4
+        if style_input_width is not None:
+            width = min(width, style_input_width)
+        corpus_list = []
+        text_input_list = []
+        while len(corpus) != 0:
            bg = Image.new("RGB", (width, self.height), color=(127, 127, 127))
            draw = ImageDraw.Draw(bg)
            char_x = 2
            font = self.font_dict[language]
-        for i, char_i in enumerate(corpus):
+            i = 0
+            while i < len(corpus):
+                char_i = corpus[i]
                char_size = font.getsize(char_i)[0]
+                # split when char_x exceeds char size and index is not 0 (at least 1 char should be wroten on the image)
+                if char_x + char_size >= width and i != 0:
+                    text_input = np.array(bg).astype(np.uint8)
+                    text_input = text_input[:, 0:char_x, :]
+                    corpus_list.append(corpus[0:i])
+                    text_input_list.append(text_input)
+                    corpus = corpus[i:]
+                    break
                draw.text((char_x, 2), char_i, fill=(0, 0, 0), font=font)
                char_x += char_size
-            if char_x >= width:
-                corpus = corpus[0:i + 1]
-                self.logger.warning("corpus length exceed limit: {}".format(
-                    corpus))
-                break
+                i += 1
+            # the whole text is shorter than style input
+            if i == len(corpus):
                text_input = np.array(bg).astype(np.uint8)
                text_input = text_input[:, 0:char_x, :]
-        return corpus, text_input
+                corpus_list.append(corpus[0:i])
+                text_input_list.append(text_input)
+                corpus = corpus[i:]
+                break
+        return corpus_list, text_input_list
--- a/configs/det/det_r50_vd_sast_icdar15.yml
+++ b/configs/det/det_r50_vd_sast_icdar15.yml
@@ -20,6 +20,7 @@ Global:
  infer_img:
  save_res_path: ./output/sast_r50_vd_ic15/predicts_sast.txt
 Architecture:
  model_type: det
  algorithm: SAST

--- a/configs/e2e/e2e_r50_vd_pg.yml
+++ b/configs/e2e/e2e_r50_vd_pg.yml
+Global:
+  use_gpu: True
+  epoch_num: 600
+  log_smooth_window: 20
+  print_batch_step: 10
+  save_model_dir: ./output/pgnet_r50_vd_totaltext/
+  save_epoch_step: 10
+  # evaluation is run every 0 iterationss after the 1000th iteration
+  eval_batch_step: [ 0, 1000 ]
+  # 1. If pretrained_model is saved in static mode, such as classification pretrained model
+  #    from static branch, load_static_weights must be set as True.
+  # 2. If you want to finetune the pretrained models we provide in the docs,
+  #    you should set load_static_weights as False.
+  load_static_weights: False
+  cal_metric_during_train: False
+  pretrained_model:
+  checkpoints:
+  save_inference_dir:
+  use_visualdl: False
+  infer_img:
+  valid_set: totaltext # two mode: totaltext valid curved words, partvgg valid non-curved words
+  save_res_path: ./output/pgnet_r50_vd_totaltext/predicts_pgnet.txt
+  character_dict_path: ppocr/utils/ic15_dict.txt
+  character_type: EN
+  max_text_length: 50 # the max length in seq
+  max_text_nums: 30 # the max seq nums in a pic
+  tcl_len: 64
+Architecture:
+  model_type: e2e
+  algorithm: PGNet
+  Transform:
+  Backbone:
+    name: ResNet
+    layers: 50
+  Neck:
+    name: PGFPN
+  Head:
+    name: PGHead
+Loss:
+  name: PGLoss
+  tcl_bs: 64
+  max_text_length: 50 # the same as Global: max_text_length
+  max_text_nums: 30 # the same as Global：max_text_nums
+  pad_num: 36 # the length of dict for pad
+Optimizer:
+  name: Adam
+  beta1: 0.9
+  beta2: 0.999
+  lr:
+    learning_rate: 0.001
+  regularizer:
+    name: 'L2'
+    factor: 0
+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
+Train:
+  dataset:
+    name: PGDataSet
+    label_file_list: [.././train_data/total_text/train/]
+    ratio_list: [1.0]
+    data_format: icdar #two data format: icdar/textnet
+    transforms:
+      - DecodeImage: # load image
+          img_mode: BGR
+          channel_first: False
+      - PGProcessTrain:
+          batch_size: 14  # same as loader: batch_size_per_card
+          min_crop_size: 24
+          min_text_size: 4
+          max_text_size: 512
+      - KeepKeys:
+          keep_keys: [ 'images', 'tcl_maps', 'tcl_label_maps', 'border_maps','direction_maps', 'training_masks', 'label_list', 'pos_list', 'pos_mask' ] # dataloader will return list in this order
+  loader:
+    shuffle: True
+    drop_last: True
+    batch_size_per_card: 14
+    num_workers: 16
+Eval:
+  dataset:
+    name: PGDataSet
+    data_dir: ./train_data/
+    label_file_list: [./train_data/total_text/test/]
+    transforms:
+      - DecodeImage: # load image
+          img_mode: RGB
+          channel_first: False
+      - E2ELabelEncode:
+      - E2EResizeForTest:
+          max_side_len: 768
+      - NormalizeImage:
+          scale: 1./255.
+          mean: [ 0.485, 0.456, 0.406 ]
+          std: [ 0.229, 0.224, 0.225 ]
+          order: 'hwc'
+      - ToCHWImage:
+      - KeepKeys:
+          keep_keys: [ 'image', 'shape', 'polys', 'strs', 'tags', 'img_id']
+  loader:
+    shuffle: False
+    drop_last: False
+    batch_size_per_card: 1 # must be 1
+    num_workers: 2
\ No newline at end of file
--- 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 +118,38 @@ class ArgsParser(ArgumentParser):
        return config
    def _set_language(self, type):
-        assert(type),"please use -l or --language to choose language type"
+        print("type:", 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):
@@ -111,10 +178,12 @@ def merge_config(config):
                else:
                    cur = cur[sub_key]
 def loss_file(path):
-    assert(
+    assert (
        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__':
@@ -126,27 +195,33 @@ if __name__ == '__main__':
    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)
+        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