add ser+re hub serving (#7844)

* add ser+re hub serving

* fix

deploy/hubserving/kie_ser/__init__.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# 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.
\ No newline at end of file

deploy/hubserving/kie_ser/config.json

+{
+    "modules_info": {
+        "kie_ser": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8871,
+    "use_multiprocess": false,
+    "workers": 2
+}
+

deploy/hubserving/kie_ser/module.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import os
+import sys
+sys.path.insert(0, ".")
+import copy
+
+import time
+import paddlehub
+from paddlehub.common.logger import logger
+from paddlehub.module.module import moduleinfo, runnable, serving
+import cv2
+import numpy as np
+import paddlehub as hub
+
+from tools.infer.utility import base64_to_cv2
+from ppstructure.kie.predict_kie_token_ser import SerPredictor
+from ppstructure.utility import parse_args
+
+from deploy.hubserving.kie_ser.params import read_params
+
+
+@moduleinfo(
+    name="kie_ser",
+    version="1.0.0",
+    summary="kie ser service",
+    author="paddle-dev",
+    author_email="paddle-dev@baidu.com",
+    type="cv/KIE_SER")
+class KIESer(hub.Module):
+    def _initialize(self, use_gpu=False, enable_mkldnn=False):
+        """
+        initialize with the necessary elements
+        """
+        cfg = self.merge_configs()
+
+        cfg.use_gpu = use_gpu
+        if use_gpu:
+            try:
+                _places = os.environ["CUDA_VISIBLE_DEVICES"]
+                int(_places[0])
+                print("use gpu: ", use_gpu)
+                print("CUDA_VISIBLE_DEVICES: ", _places)
+                cfg.gpu_mem = 8000
+            except:
+                raise RuntimeError(
+                    "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES via export CUDA_VISIBLE_DEVICES=cuda_device_id."
+                )
+        cfg.ir_optim = True
+        cfg.enable_mkldnn = enable_mkldnn
+
+        self.ser_predictor = SerPredictor(cfg)
+
+    def merge_configs(self, ):
+        # deafult cfg
+        backup_argv = copy.deepcopy(sys.argv)
+        sys.argv = sys.argv[:1]
+        cfg = parse_args()
+
+        update_cfg_map = vars(read_params())
+
+        for key in update_cfg_map:
+            cfg.__setattr__(key, update_cfg_map[key])
+
+        sys.argv = copy.deepcopy(backup_argv)
+        return cfg
+
+    def read_images(self, paths=[]):
+        images = []
+        for img_path in paths:
+            assert os.path.isfile(
+                img_path), "The {} isn't a valid file.".format(img_path)
+            img = cv2.imread(img_path)
+            if img is None:
+                logger.info("error in loading image:{}".format(img_path))
+                continue
+            images.append(img)
+        return images
+
+    def predict(self, images=[], paths=[]):
+        """
+        Get the chinese texts in the predicted images.
+        Args:
+            images (list(numpy.ndarray)): images data, shape of each is [H, W, C]. If images not paths
+            paths (list[str]): The paths of images. If paths not images
+        Returns:
+            res (list): The result of chinese texts and save path of images.
+        """
+        if images != [] and isinstance(images, list) and paths == []:
+            predicted_data = images
+        elif images == [] and isinstance(paths, list) and paths != []:
+            predicted_data = self.read_images(paths)
+        else:
+            raise TypeError("The input data is inconsistent with expectations.")
+
+        assert predicted_data != [], "There is not any image to be predicted. Please check the input data."
+
+        all_results = []
+        for img in predicted_data:
+            if img is None:
+                logger.info("error in loading image")
+                all_results.append([])
+                continue
+            starttime = time.time()
+            ser_res, _, elapse = self.ser_predictor(img)
+            elapse = time.time() - starttime
+            logger.info("Predict time: {}".format(elapse))
+            all_results.append(ser_res)
+        return all_results
+
+    @serving
+    def serving_method(self, images, **kwargs):
+        """
+        Run as a service.
+        """
+        images_decode = [base64_to_cv2(image) for image in images]
+        results = self.predict(images_decode, **kwargs)
+        return results
+
+
+if __name__ == '__main__':
+    ocr = OCRSystem()
+    ocr._initialize()
+    image_path = [
+        './doc/imgs/11.jpg',
+        './doc/imgs/12.jpg',
+    ]
+    res = ocr.predict(paths=image_path)
+    print(res)

deploy/hubserving/kie_ser/params.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from deploy.hubserving.ocr_system.params import read_params as pp_ocr_read_params
+
+
+class Config(object):
+    pass
+
+
+def read_params():
+    cfg = pp_ocr_read_params()
+
+    # SER params
+    cfg.kie_algorithm = "LayoutXLM"
+    cfg.use_visual_backbone = False
+
+    cfg.ser_model_dir = "./inference/ser_vi_layoutxlm_xfund_infer"
+    cfg.ser_dict_path = "train_data/XFUND/class_list_xfun.txt"
+    cfg.vis_font_path = "./doc/fonts/simfang.ttf"
+    cfg.ocr_order_method = "tb-yx"
+
+    return cfg

deploy/hubserving/kie_ser_re/__init__.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# 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.
\ No newline at end of file

deploy/hubserving/kie_ser_re/config.json

+{
+    "modules_info": {
+        "kie_ser_re": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8872,
+    "use_multiprocess": false,
+    "workers": 2
+}
+

deploy/hubserving/kie_ser_re/module.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import os
+import sys
+sys.path.insert(0, ".")
+import copy
+
+import time
+import paddlehub
+from paddlehub.common.logger import logger
+from paddlehub.module.module import moduleinfo, runnable, serving
+import cv2
+import numpy as np
+import paddlehub as hub
+
+from tools.infer.utility import base64_to_cv2
+from ppstructure.kie.predict_kie_token_ser_re import SerRePredictor
+from ppstructure.utility import parse_args
+
+from deploy.hubserving.kie_ser_re.params import read_params
+
+
+@moduleinfo(
+    name="kie_ser_re",
+    version="1.0.0",
+    summary="kie ser re service",
+    author="paddle-dev",
+    author_email="paddle-dev@baidu.com",
+    type="cv/KIE_SER_RE")
+class KIESerRE(hub.Module):
+    def _initialize(self, use_gpu=False, enable_mkldnn=False):
+        """
+        initialize with the necessary elements
+        """
+        cfg = self.merge_configs()
+
+        cfg.use_gpu = use_gpu
+        if use_gpu:
+            try:
+                _places = os.environ["CUDA_VISIBLE_DEVICES"]
+                int(_places[0])
+                print("use gpu: ", use_gpu)
+                print("CUDA_VISIBLE_DEVICES: ", _places)
+                cfg.gpu_mem = 8000
+            except:
+                raise RuntimeError(
+                    "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES via export CUDA_VISIBLE_DEVICES=cuda_device_id."
+                )
+        cfg.ir_optim = True
+        cfg.enable_mkldnn = enable_mkldnn
+
+        self.ser_re_predictor = SerRePredictor(cfg)
+
+    def merge_configs(self, ):
+        # deafult cfg
+        backup_argv = copy.deepcopy(sys.argv)
+        sys.argv = sys.argv[:1]
+        cfg = parse_args()
+
+        update_cfg_map = vars(read_params())
+
+        for key in update_cfg_map:
+            cfg.__setattr__(key, update_cfg_map[key])
+
+        sys.argv = copy.deepcopy(backup_argv)
+        return cfg
+
+    def read_images(self, paths=[]):
+        images = []
+        for img_path in paths:
+            assert os.path.isfile(
+                img_path), "The {} isn't a valid file.".format(img_path)
+            img = cv2.imread(img_path)
+            if img is None:
+                logger.info("error in loading image:{}".format(img_path))
+                continue
+            images.append(img)
+        return images
+
+    def predict(self, images=[], paths=[]):
+        """
+        Get the chinese texts in the predicted images.
+        Args:
+            images (list(numpy.ndarray)): images data, shape of each is [H, W, C]. If images not paths
+            paths (list[str]): The paths of images. If paths not images
+        Returns:
+            res (list): The result of chinese texts and save path of images.
+        """
+        if images != [] and isinstance(images, list) and paths == []:
+            predicted_data = images
+        elif images == [] and isinstance(paths, list) and paths != []:
+            predicted_data = self.read_images(paths)
+        else:
+            raise TypeError("The input data is inconsistent with expectations.")
+
+        assert predicted_data != [], "There is not any image to be predicted. Please check the input data."
+
+        all_results = []
+        for img in predicted_data:
+            if img is None:
+                logger.info("error in loading image")
+                all_results.append([])
+                continue
+            print(img.shape)
+            starttime = time.time()
+            re_res, _ = self.ser_re_predictor(img)
+            print(re_res)
+            elapse = time.time() - starttime
+            logger.info("Predict time: {}".format(elapse))
+            all_results.append(re_res)
+        return all_results
+
+    @serving
+    def serving_method(self, images, **kwargs):
+        """
+        Run as a service.
+        """
+        images_decode = [base64_to_cv2(image) for image in images]
+        results = self.predict(images_decode, **kwargs)
+        return results
+
+
+if __name__ == '__main__':
+    ocr = OCRSystem()
+    ocr._initialize()
+    image_path = [
+        './doc/imgs/11.jpg',
+        './doc/imgs/12.jpg',
+    ]
+    res = ocr.predict(paths=image_path)
+    print(res)

deploy/hubserving/kie_ser_re/params.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from deploy.hubserving.ocr_system.params import read_params as pp_ocr_read_params
+
+
+class Config(object):
+    pass
+
+
+def read_params():
+    cfg = pp_ocr_read_params()
+
+    # SER params
+    cfg.kie_algorithm = "LayoutXLM"
+    cfg.use_visual_backbone = False
+
+    cfg.ser_model_dir = "./inference/ser_vi_layoutxlm_xfund_infer"
+    cfg.re_model_dir = "./inference/re_vi_layoutxlm_xfund_infer"
+
+    cfg.ser_dict_path = "train_data/XFUND/class_list_xfun.txt"
+    cfg.vis_font_path = "./doc/fonts/simfang.ttf"
+    cfg.ocr_order_method = "tb-yx"
+
+    return cfg

deploy/hubserving/readme.md

@@ -30,6 +30,8 @@ deploy/hubserving/
   └─  structure_layout  版面分析服务包
   └─  structure_table  表格识别服务包
   └─  structure_system  PP-Structure服务包
+  └─  kie_ser  关键信息抽取-SER服务包
+  └─  kie_ser_re  关键信息抽取-SER+RE服务包
 ```
 
 每个服务包下包含3个文件。以2阶段串联服务包为例，目录如下：
@@ -42,6 +44,7 @@ deploy/hubserving/ocr_system/
 ```
 ## 1. 近期更新
 
+* 2022.10.09 新增关键信息抽取服务。
 * 2022.08.23 新增版面分析服务。
 * 2022.05.05 新增PP-OCRv3检测和识别模型。
 * 2022.03.30 新增PP-Structure和表格识别两种服务。
@@ -57,12 +60,15 @@ pip3 install paddlehub==2.1.0 --upgrade -i https://mirror.baidu.com/pypi/simple
 
 ### 2.2 下载推理模型
 安装服务模块前，需要准备推理模型并放到正确路径。默认使用的是PP-OCRv3模型，默认模型路径为：
+
 ```
 检测模型：./inference/ch_PP-OCRv3_det_infer/
 识别模型：./inference/ch_PP-OCRv3_rec_infer/
 方向分类器：./inference/ch_ppocr_mobile_v2.0_cls_infer/
 版面分析模型：./inference/picodet_lcnet_x1_0_fgd_layout_infer/
 表格结构识别模型：./inference/ch_ppstructure_mobile_v2.0_SLANet_infer/
+关键信息抽取SER模型：./inference/ser_vi_layoutxlm_xfund_infer/
+关键信息抽取RE模型：./inference/re_vi_layoutxlm_xfund_infer/
 ```
 
 **模型路径可在`params.py`中查看和修改。** 更多模型可以从PaddleOCR提供的模型库[PP-OCR](../../doc/doc_ch/models_list.md)和[PP-Structure](../../ppstructure/docs/models_list.md)下载，也可以替换成自己训练转换好的模型。
@@ -92,6 +98,12 @@ hub install deploy/hubserving/structure_system/
 
 # 或，安装版面分析服务模块：  
 hub install deploy/hubserving/structure_layout/
+
+# 或，安装关键信息抽取SER服务模块：  
+hub install deploy/hubserving/kie_ser/
+
+# 或，安装关键信息抽取SER+RE服务模块：  
+hub install deploy/hubserving/kie_ser_re/
 ```
 
 * 在Windows环境下(文件夹的分隔符为`\`)，安装示例如下：
@@ -116,6 +128,12 @@ hub install deploy\hubserving\structure_system\
 
 # 或，安装版面分析服务模块：
 hub install deploy\hubserving\structure_layout\
+
+# 或，安装关键信息抽取SER服务模块：  
+hub install deploy\hubserving\kie_ser\
+
+# 或，安装关键信息抽取SER+RE服务模块：  
+hub install deploy\hubserving\kie_ser_re\
 ```
 
 ### 2.4 启动服务
@@ -194,6 +212,8 @@ hub serving start -c deploy/hubserving/ocr_system/config.json
 `http://127.0.0.1:8869/predict/structure_table`  
 `http://127.0.0.1:8870/predict/structure_system`  
 `http://127.0.0.1:8870/predict/structure_layout`  
+`http://127.0.0.1:8871/predict/kie_ser`  
+`http://127.0.0.1:8872/predict/kie_ser_re`
 - **image_dir**：测试图像路径，可以是单张图片路径，也可以是图像集合目录路径  
 - **visualize**：是否可视化结果，默认为False  
 - **output**：可视化结果保存路径，默认为`./hubserving_result`
@@ -216,15 +236,18 @@ hub serving start -c deploy/hubserving/ocr_system/config.json
 
 不同模块返回的字段不同，如，文本识别服务模块返回结果不含`text_region`字段，具体信息如下：
 
-| 字段名/模块名 | ocr_det | ocr_cls | ocr_rec | ocr_system | structure_table | structure_system | Structure_layout |
-|  ---  |  ---  |  ---  |  ---  |  ---  | ---  |  ---  |  ---  |
+| 字段名/模块名 | ocr_det | ocr_cls | ocr_rec | ocr_system | structure_table | structure_system | Structure_layout | kie_ser | kie_re |
+|  ---  |  ---  |  ---  |  ---  |  ---  | ---  |  ---  |  ---  | ---  |  ---  |
 |angle| | ✔ | | ✔ | |||
-|text| | |✔|✔| | ✔ |  |
-|confidence| |✔ |✔| | | ✔| |
-|text_region| ✔| | |✔ | | ✔| |
-|html| | | | |✔ |✔||
-|regions| | | | |✔ |✔ | |
-|layout| | | | | | | ✔ |
+|text| | |✔|✔| | ✔ |  | ✔ | ✔ |
+|confidence| |✔ |✔| | | ✔| |✔ | ✔ |
+|text_region| ✔| | |✔ | | ✔| |✔ | ✔ |
+|html| | | | |✔ |✔||| |
+|regions| | | | |✔ |✔ | || |
+|layout| | | | | | | ✔ || |
+|ser_res| | | | | | |  |  ✔ | |
+|re_res| | | | | | |  | |  ✔ |
+
 
 **说明：** 如果需要增加、删除、修改返回字段，可在相应模块的`module.py`文件中进行修改，完整流程参考下一节自定义修改服务模块。
 

deploy/hubserving/readme_en.md

@@ -30,6 +30,8 @@ deploy/hubserving/
   └─  structure_layout  layout analysis service package
   └─  structure_table  table recognition service package
   └─  structure_system  PP-Structure service package
+  └─  kie_ser  KIE(SER) service package
+  └─  kie_ser_re  KIE(SER+RE) service package
 ```
 
 Each service pack contains 3 files. Take the 2-stage series connection service package as an example, the directory is as follows:  
@@ -42,9 +44,10 @@ deploy/hubserving/ocr_system/
 ```
 ## 1. Update
 
-* 2022.05.05 add PP-OCRv3 text detection and recognition models.
-* 2022.03.30 add PP-Structure and table recognition services。
-* 2022.08.23 add layout analysis services。
+* 2022.10.09 add KIE services.
+* 2022.08.23 add layout analysis services.
+* 2022.03.30 add PP-Structure and table recognition services.
+* 2022.05.05 add PP-OCRv3 text detection and recognition services.
 
 
 ## 2. Quick start service
@@ -65,6 +68,8 @@ text recognition model: ./inference/ch_PP-OCRv3_rec_infer/
 text angle classifier: ./inference/ch_ppocr_mobile_v2.0_cls_infer/
 layout parse model: ./inference/picodet_lcnet_x1_0_fgd_layout_infer/
 tanle recognition: ./inference/ch_ppstructure_mobile_v2.0_SLANet_infer/
+KIE(SER): ./inference/ser_vi_layoutxlm_xfund_infer/
+KIE(SER+RE): ./inference/re_vi_layoutxlm_xfund_infer/
 ```  
 
 **The model path can be found and modified in `params.py`.** More models provided by PaddleOCR can be obtained from the [model library](../../doc/doc_en/models_list_en.md). You can also use models trained by yourself.
@@ -92,8 +97,11 @@ hub install deploy/hubserving/structure_table/
 # Or install PP-Structure service module
 hub install deploy/hubserving/structure_system/
 
-# Or install layout analysis service module
-hub install deploy/hubserving/structure_layout/
+# Or install KIE(SER) service module
+hub install deploy/hubserving/kie_ser/
+
+# Or install KIE(SER+RE) service module
+hub install deploy/hubserving/kie_ser_re/
 ```
 
 * On Windows platform, the examples are as follows.
@@ -118,6 +126,12 @@ hub install deploy\hubserving\structure_system\
 
 # Or install layout analysis service module
 hub install deploy\hubserving\structure_layout\
+
+# Or install KIE(SER) service module
+hub install deploy\hubserving\kie_ser\
+
+# Or install KIE(SER+RE) service module
+hub install deploy\hubserving\kie_ser_re\
 ```
 
 ### 2.4 Start service
@@ -201,6 +215,8 @@ For example, if using the configuration file to start the text angle classificat
 `http://127.0.0.1:8869/predict/structure_table`  
 `http://127.0.0.1:8870/predict/structure_system`  
 `http://127.0.0.1:8870/predict/structure_layout`  
+`http://127.0.0.1:8871/predict/kie_ser`  
+`http://127.0.0.1:8872/predict/kie_ser_re`
 - **image_dir**：Test image path, can be a single image path or an image directory path
 - **visualize**：Whether to visualize the results, the default value is False
 - **output**：The floder to save Visualization result, default value is `./hubserving_result`
@@ -225,15 +241,17 @@ The returned result is a list. Each item in the list is a dict. The dict may con
 
 The fields returned by different modules are different. For example, the results returned by the text recognition service module do not contain `text_region`. The details are as follows:
 
-| field name/module name | ocr_det | ocr_cls | ocr_rec | ocr_system | structure_table | structure_system | structure_layout |
-|  ---  |  ---  |  ---  |  ---  |  ---  | ---  |---  |---  |
-|angle| | ✔ | | ✔ | || |
-|text| | |✔|✔| | ✔ | |
-|confidence| |✔ |✔| | | ✔| |
-|text_region| ✔| | |✔ | | ✔| |
-|html| | | | |✔ |✔| |
-|regions| | | | |✔ |✔ | |
-|layout| | | | | | |✔ |
+| field name/module name | ocr_det | ocr_cls | ocr_rec | ocr_system | structure_table | structure_system | structure_layout | kie_ser | kie_re |
+|  ---  |  ---  |  ---  |  ---  |  ---  | ---  |  ---  |  ---  | ---  |  ---  |
+|angle| | ✔ | | ✔ | |||
+|text| | |✔|✔| | ✔ |  | ✔ | ✔ |
+|confidence| |✔ |✔| | | ✔| |✔ | ✔ |
+|text_region| ✔| | |✔ | | ✔| |✔ | ✔ |
+|html| | | | |✔ |✔||| |
+|regions| | | | |✔ |✔ | || |
+|layout| | | | | | | ✔ || |
+|ser_res| | | | | | |  |  ✔ | |
+|re_res| | | | | | |  | |  ✔ |
 
 **Note：** If you need to add, delete or modify the returned fields, you can modify the file `module.py` of the corresponding module. For the complete process, refer to the user-defined modification service module in the next section.
 

ppocr/data/imaug/label_ops.py

@@ -1089,7 +1089,7 @@ class VQATokenLabelEncode(object):
 
     def _load_ocr_info(self, data):
         if self.infer_mode:
-            ocr_result = self.ocr_engine.ocr(data['image'], cls=False)
+            ocr_result = self.ocr_engine.ocr(data['image'], cls=False)[0]
             ocr_info = []
             for res in ocr_result:
                 ocr_info.append({

ppstructure/kie/predict_kie_token_ser_re.py

@@ -50,7 +50,6 @@ class SerRePredictor(object):
             utility.create_predictor(args, 're', logger)
 
     def __call__(self, img):
-        ori_im = img.copy()
         starttime = time.time()
         ser_results, ser_inputs, _ = self.ser_engine(img)
         re_input, entity_idx_dict_batch = make_input(ser_inputs, ser_results)