fix benckmark error when benckmark=false

paddleocr.py

@@ -47,7 +47,7 @@ __all__ = [
 ]
 
 SUPPORT_DET_MODEL = ['DB']
-VERSION = '2.6.0.3'
+VERSION = '2.6.1.0'
 SUPPORT_REC_MODEL = ['CRNN', 'SVTR_LCNet']
 BASE_DIR = os.path.expanduser("~/.paddleocr/")
 

ppstructure/pdf2word/pdf2word.py

+# copyright (c) 2022 PaddlePaddle Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import sys
 import tarfile
 import os
@@ -20,7 +34,6 @@ root = os.path.abspath(os.path.join(file, '../../'))
 sys.path.append(file)
 sys.path.insert(0, root)
 
-
 from ppstructure.predict_system import StructureSystem, save_structure_res
 from ppstructure.utility import parse_args, draw_structure_result
 from ppocr.utils.network import download_with_progressbar
@@ -32,13 +45,17 @@ __VERSION__ = "0.2.2"
 
 URLs_EN = {
     # 下载超英文轻量级PP-OCRv3模型的检测模型并解压
-    "en_PP-OCRv3_det_infer": "https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar",
+    "en_PP-OCRv3_det_infer":
+    "https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar",
     # 下载英文轻量级PP-OCRv3模型的识别模型并解压
-    "en_PP-OCRv3_rec_infer": "https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar",
+    "en_PP-OCRv3_rec_infer":
+    "https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar",
     # 下载超轻量级英文表格英文模型并解压
-    "en_ppstructure_mobile_v2.0_SLANet_infer": "https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar",
+    "en_ppstructure_mobile_v2.0_SLANet_infer":
+    "https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar",
     # 英文版面分析模型
-    "picodet_lcnet_x1_0_fgd_layout_infer": "https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_infer.tar",
+    "picodet_lcnet_x1_0_fgd_layout_infer":
+    "https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_infer.tar",
 }
 DICT_EN = {
     "rec_char_dict_path": "en_dict.txt",
@@ -47,13 +64,17 @@ DICT_EN = {
 
 URLs_CN = {
     # 下载超中文轻量级PP-OCRv3模型的检测模型并解压
-    "cn_PP-OCRv3_det_infer": "https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar",
+    "cn_PP-OCRv3_det_infer":
+    "https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar",
     # 下载中文轻量级PP-OCRv3模型的识别模型并解压
-    "cn_PP-OCRv3_rec_infer": "https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar",
+    "cn_PP-OCRv3_rec_infer":
+    "https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar",
     # 下载超轻量级英文表格英文模型并解压
-    "cn_ppstructure_mobile_v2.0_SLANet_infer": "https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar",
+    "cn_ppstructure_mobile_v2.0_SLANet_infer":
+    "https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar",
     # 中文版面分析模型
-    "picodet_lcnet_x1_0_fgd_layout_cdla_infer": "https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_cdla_infer.tar",
+    "picodet_lcnet_x1_0_fgd_layout_cdla_infer":
+    "https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_fgd_layout_cdla_infer.tar",
 }
 DICT_CN = {
     "rec_char_dict_path": "ppocr_keys_v1.txt",
@@ -61,7 +82,6 @@ DICT_CN = {
 }
 
 
-
 def QImageToCvMat(incomingImage) -> np.array:
     '''  
     Converts a QImage into an opencv MAT format  
@@ -120,7 +140,7 @@ class Worker(QThread):
         self.outputDir = None
         self.totalPageCnt = 0
         self.pageCnt = 0
-        self.setStackSize(1024*1024)
+        self.setStackSize(1024 * 1024)
 
     def setImagePath(self, imagePaths):
         self.imagePaths = imagePaths
@@ -167,8 +187,8 @@ class Worker(QThread):
             try:
                 convert_info_docx(imgs, all_res, self.outputDir, img_name)
             except Exception as ex:
-                print("error in layout recovery image:{}, err msg: {}".
-                    format(img_name, ex))
+                print("error in layout recovery image:{}, err msg: {}".format(
+                    img_name, ex))
         print("Predict time : {:.3f}s".format(time_dict['all']))
         print('result save to {}'.format(self.outputDir))
 
@@ -185,10 +205,11 @@ class Worker(QThread):
                     and os.path.basename(image_file)[-3:] == 'pdf':
                     self.totalPageCnt += 1
                     self.progressBarRange.emit(self.totalPageCnt)
-                    print('===============using use_pdf2docx_api===============')
+                    print(
+                        '===============using use_pdf2docx_api===============')
                     img_name = os.path.basename(image_file).split('.')[0]
-                    docx_file = os.path.join(
-                        self.outputDir, '{}.docx'.format(img_name))
+                    docx_file = os.path.join(self.outputDir,
+                                             '{}.docx'.format(img_name))
                     cv = Converter(image_file)
                     cv.convert(docx_file)
                     cv.close()
@@ -201,7 +222,8 @@ class Worker(QThread):
                     if len(imgs) == 0:
                         continue
                     img_name = os.path.basename(image_file).split('.')[0]
-                    os.makedirs(os.path.join(self.outputDir, img_name), exist_ok=True)
+                    os.makedirs(
+                        os.path.join(self.outputDir, img_name), exist_ok=True)
                     self.ppocrPrecitor(imgs, img_name)
                 # file processed
             self.endsignal.emit()
@@ -222,8 +244,7 @@ class APP_Image2Doc(QWidget):
         self.screenShot = None
         self.save_pdf = False
         self.output_dir = None
-        self.vis_font_path = os.path.join(root,
-                "doc", "fonts", "simfang.ttf")
+        self.vis_font_path = os.path.join(root, "doc", "fonts", "simfang.ttf")
         self.use_pdf2docx_api = False
 
         # ProgressBar
@@ -245,8 +266,10 @@ class APP_Image2Doc(QWidget):
         }
 
         # 设置工作进程
-        self._thread = Worker(predictors, self.save_pdf, self.vis_font_path, self.use_pdf2docx_api)
-        self._thread.progressBarValue.connect(self.handleProgressBarUpdateSingal)
+        self._thread = Worker(predictors, self.save_pdf, self.vis_font_path,
+                              self.use_pdf2docx_api)
+        self._thread.progressBarValue.connect(
+            self.handleProgressBarUpdateSingal)
         self._thread.endsignal.connect(self.handleEndsignalSignal)
         # self._thread.finished.connect(QObject.deleteLater)
         self._thread.progressBarRange.connect(self.handleProgressBarRangeSingal)
@@ -294,8 +317,7 @@ class APP_Image2Doc(QWidget):
         # ProgressBar
         layout.addWidget(self.pb, 2, 0, 1, 5)
         # time estimate label
-        self.timeEstLabel = QLabel(
-            ("Time Left: --"))
+        self.timeEstLabel = QLabel(("Time Left: --"))
         layout.addWidget(self.timeEstLabel, 3, 0, 1, 5)
 
         self.setLayout(layout)
@@ -303,11 +325,8 @@ class APP_Image2Doc(QWidget):
     def downloadModels(self, URLs):
         # using custom model
         tar_file_name_list = [
-            'inference.pdiparams', 
-            'inference.pdiparams.info', 
-            'inference.pdmodel',
-            'model.pdiparams', 
-            'model.pdiparams.info', 
+            'inference.pdiparams', 'inference.pdiparams.info',
+            'inference.pdmodel', 'model.pdiparams', 'model.pdiparams.info',
             'model.pdmodel'
         ]
         model_path = os.path.join(root, 'inference')
@@ -325,7 +344,8 @@ class APP_Image2Doc(QWidget):
                 try:
                     download_with_progressbar(url, tarpath)
                 except Exception as e:
-                    print("Error occurred when downloading file, error message:")
+                    print(
+                        "Error occurred when downloading file, error message:")
                     print(e)
 
             # unzip model tar
@@ -341,8 +361,7 @@ class APP_Image2Doc(QWidget):
                         if filename is None:
                             continue
                         file = tarObj.extractfile(member)
-                        with open(
-                                os.path.join(storage_dir, filename),
+                        with open(os.path.join(storage_dir, filename),
                                   'wb') as f:
                             f.write(file.read())
             except Exception as e:
@@ -356,37 +375,40 @@ class APP_Image2Doc(QWidget):
         args.ocr = True
         args.recovery = True
         args.save_pdf = self.save_pdf
-        args.table_char_dict_path = os.path.join(root, 
-                "ppocr", "utils", "dict", "table_structure_dict.txt")
+        args.table_char_dict_path = os.path.join(root, "ppocr", "utils", "dict",
+                                                 "table_structure_dict.txt")
         if lang == 'EN':
-            args.det_model_dir = os.path.join(root,  # 此处从这里找到模型存放位置
-                "inference", "en_PP-OCRv3_det_infer")
-            args.rec_model_dir = os.path.join(root, 
-                "inference", "en_PP-OCRv3_rec_infer")
-            args.table_model_dir = os.path.join(root, 
-                "inference", "en_ppstructure_mobile_v2.0_SLANet_infer")
+            args.det_model_dir = os.path.join(
+                root,  # 此处从这里找到模型存放位置
+                "inference",
+                "en_PP-OCRv3_det_infer")
+            args.rec_model_dir = os.path.join(root, "inference",
+                                              "en_PP-OCRv3_rec_infer")
+            args.table_model_dir = os.path.join(
+                root, "inference", "en_ppstructure_mobile_v2.0_SLANet_infer")
             args.output = os.path.join(root, "output")  # 结果保存路径
-            args.layout_model_dir = os.path.join(root,
-                "inference", "picodet_lcnet_x1_0_fgd_layout_infer")
+            args.layout_model_dir = os.path.join(
+                root, "inference", "picodet_lcnet_x1_0_fgd_layout_infer")
             lang_dict = DICT_EN
         elif lang == 'CN':
-            args.det_model_dir = os.path.join(root,  # 此处从这里找到模型存放位置
-                "inference", "cn_PP-OCRv3_det_infer")
-            args.rec_model_dir = os.path.join(root, 
-                "inference", "cn_PP-OCRv3_rec_infer")
-            args.table_model_dir = os.path.join(root, 
-                "inference", "cn_ppstructure_mobile_v2.0_SLANet_infer")
+            args.det_model_dir = os.path.join(
+                root,  # 此处从这里找到模型存放位置
+                "inference",
+                "cn_PP-OCRv3_det_infer")
+            args.rec_model_dir = os.path.join(root, "inference",
+                                              "cn_PP-OCRv3_rec_infer")
+            args.table_model_dir = os.path.join(
+                root, "inference", "cn_ppstructure_mobile_v2.0_SLANet_infer")
             args.output = os.path.join(root, "output")  # 结果保存路径
-            args.layout_model_dir = os.path.join(root,
-                "inference", "picodet_lcnet_x1_0_fgd_layout_cdla_infer")
+            args.layout_model_dir = os.path.join(
+                root, "inference", "picodet_lcnet_x1_0_fgd_layout_cdla_infer")
             lang_dict = DICT_CN
         else:
             raise ValueError("Unsupported language")
-        args.rec_char_dict_path = os.path.join(root, 
-                "ppocr", "utils", 
+        args.rec_char_dict_path = os.path.join(root, "ppocr", "utils",
                                                lang_dict['rec_char_dict_path'])
-        args.layout_dict_path = os.path.join(root,
-                "ppocr", "utils", "dict", "layout_dict", 
+        args.layout_dict_path = os.path.join(root, "ppocr", "utils", "dict",
+                                             "layout_dict",
                                              lang_dict['layout_dict_path'])
         # init predictor
         return StructureSystem(args)
@@ -395,8 +417,8 @@ class APP_Image2Doc(QWidget):
         '''
         可以多选图像文件
         '''
-        selectedFiles = QFileDialog.getOpenFileNames(self, 
-            "多文件选择", "/", "图片文件 (*.png *.jpeg *.jpg *.bmp *.pdf)")[0]
+        selectedFiles = QFileDialog.getOpenFileNames(
+            self, "多文件选择", "/", "图片文件 (*.png *.jpeg *.jpg *.bmp *.pdf)")[0]
         if len(selectedFiles) > 0:
             self.imagePaths = selectedFiles
             self.screenShot = None  # discard screenshot temp image
@@ -416,17 +438,18 @@ class APP_Image2Doc(QWidget):
 
     def handleStartSignal(self, lang='EN', pdfParser=False):
         if self.screenShot:  # for screenShot
-            img_name = 'screenshot_' + time.strftime("%Y%m%d%H%M%S", time.localtime())
+            img_name = 'screenshot_' + time.strftime("%Y%m%d%H%M%S",
+                                                     time.localtime())
             image = QImageToCvMat(self.screenShot)
             self.predictAndSave(image, img_name, lang)
             # update Progress Bar
             self.pb.setValue(1)
-            QMessageBox.information(self, 
-                u'Information', "文档提取完成")
-        elif len(self.imagePaths) > 0 : # for image file selection
+            QMessageBox.information(self, u'Information', "文档提取完成")
+        elif len(self.imagePaths) > 0:  # for image file selection
             # Must set image path list and language before start
             self.output_dir = os.path.join(
-                os.path.dirname(self.imagePaths[0]), "output")  # output_dir shold be same as imagepath
+                os.path.dirname(self.imagePaths[0]),
+                "output")  # output_dir shold be same as imagepath
             self._thread.setOutputDir(self.output_dir)
             self._thread.setImagePath(self.imagePaths)
             self._thread.setLang(lang)
@@ -439,11 +462,9 @@ class APP_Image2Doc(QWidget):
             # 启动工作进程
             self._thread.start()
             self.time_start = time.time()  # log start time
-            QMessageBox.information(self, 
-                u'Information', "开始转换")
+            QMessageBox.information(self, u'Information', "开始转换")
         else:
-            QMessageBox.warning(self, 
-                u'Information', "请选择要识别的文件或截图")
+            QMessageBox.warning(self, u'Information', "请选择要识别的文件或截图")
 
     def handleShowResultSignal(self):
         if self.output_dir is None:
@@ -454,15 +475,16 @@ class APP_Image2Doc(QWidget):
             else:
                 os.system('open ' + os.path.normpath(self.output_dir))
         else:
-            QMessageBox.information(self, 
-                u'Information', "输出文件不存在")
+            QMessageBox.information(self, u'Information', "输出文件不存在")
 
     def handleProgressBarUpdateSingal(self, i):
         self.pb.setValue(i)
         # calculate time left of recognition
         lenbar = self.pb.maximum()
-        avg_time = (time.time() - self.time_start) / i  # Use average time to prevent time fluctuations
-        time_left = str(datetime.timedelta(seconds=avg_time * (lenbar - i))).split(".")[0]  # Remove microseconds
+        avg_time = (time.time() - self.time_start
+                    ) / i  # Use average time to prevent time fluctuations
+        time_left = str(datetime.timedelta(seconds=avg_time * (
+            lenbar - i))).split(".")[0]  # Remove microseconds
         self.timeEstLabel.setText(f"Time Left: {time_left}")  # show time left
 
     def handleProgressBarRangeSingal(self, max):

ppstructure/recovery/requirements.txt

@@ -3,3 +3,4 @@ PyMuPDF==1.19.0
 beautifulsoup4
 fonttools>=4.24.0
 fire>=0.3.0
+pdf2docx
\ No newline at end of file

ppstructure/table/predict_table.py

@@ -60,11 +60,15 @@ class TableSystem(object):
         self.args = args
         if not args.show_log:
             logger.setLevel(logging.INFO)
+        benchmark_tmp = False
+        if args.benchmark:
+            benchmark_tmp = args.benchmark
             args.benchmark = False
         self.text_detector = predict_det.TextDetector(copy.deepcopy(
             args)) if text_detector is None else text_detector
         self.text_recognizer = predict_rec.TextRecognizer(copy.deepcopy(
             args)) if text_recognizer is None else text_recognizer
+        if benchmark_tmp:
             args.benchmark = True
         self.table_structurer = predict_strture.TableStructurer(args)
         if args.table_algorithm in ['TableMaster']: