first commit

2025-07-02 08:57:16 +03:00
commit 56532cc9a9
1901 changed files with 457695 additions and 0 deletions
--- a/deploy/hubserving/kie_ser/init.py
+++ b/deploy/hubserving/kie_ser/init.py
@@ -0,0 +1,13 @@
+# 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.
--- a/deploy/hubserving/kie_ser/config.json
+++ b/deploy/hubserving/kie_ser/config.json
@@ -0,0 +1,15 @@
+{
+    "modules_info": {
+        "kie_ser": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8871,
+    "use_multiprocess": false,
+    "workers": 2
+}
--- a/deploy/hubserving/kie_ser/module.py
+++ b/deploy/hubserving/kie_ser/module.py
@@ -0,0 +1,152 @@
+# 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,
+    ):
+        # default 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 = KIESer()
+    ocr._initialize()
+    image_path = [
+        "./doc/imgs/11.jpg",
+        "./doc/imgs/12.jpg",
+    ]
+    res = ocr.predict(paths=image_path)
+    print(res)
--- a/deploy/hubserving/kie_ser/params.py
+++ b/deploy/hubserving/kie_ser/params.py
@@ -0,0 +1,38 @@
+# 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
--- a/deploy/hubserving/kie_ser_re/init.py
+++ b/deploy/hubserving/kie_ser_re/init.py
@@ -0,0 +1,13 @@
+# 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.
--- a/deploy/hubserving/kie_ser_re/config.json
+++ b/deploy/hubserving/kie_ser_re/config.json
@@ -0,0 +1,15 @@
+{
+    "modules_info": {
+        "kie_ser_re": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8872,
+    "use_multiprocess": false,
+    "workers": 2
+}
--- a/deploy/hubserving/kie_ser_re/module.py
+++ b/deploy/hubserving/kie_ser_re/module.py
@@ -0,0 +1,154 @@
+# 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,
+    ):
+        # default 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 = KIESerRE()
+    ocr._initialize()
+    image_path = [
+        "./doc/imgs/11.jpg",
+        "./doc/imgs/12.jpg",
+    ]
+    res = ocr.predict(paths=image_path)
+    print(res)
--- a/deploy/hubserving/kie_ser_re/params.py
+++ b/deploy/hubserving/kie_ser_re/params.py
@@ -0,0 +1,40 @@
+# 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
--- a/deploy/hubserving/ocr_cls/init.py
+++ b/deploy/hubserving/ocr_cls/init.py
@@ -0,0 +1,13 @@
+# 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.
--- a/deploy/hubserving/ocr_cls/config.json
+++ b/deploy/hubserving/ocr_cls/config.json
@@ -0,0 +1,15 @@
+{
+    "modules_info": {
+        "ocr_cls": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8866,
+    "use_multiprocess": false,
+    "workers": 2
+}
--- a/deploy/hubserving/ocr_cls/module.py
+++ b/deploy/hubserving/ocr_cls/module.py
@@ -0,0 +1,160 @@
+# 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 paddlehub
+from paddlehub.common.logger import logger
+from paddlehub.module.module import moduleinfo, runnable, serving
+import cv2
+import paddlehub as hub
+
+from tools.infer.utility import base64_to_cv2
+from tools.infer.predict_cls import TextClassifier
+from tools.infer.utility import parse_args
+from deploy.hubserving.ocr_cls.params import read_params
+
+
+@moduleinfo(
+    name="ocr_cls",
+    version="1.0.0",
+    summary="ocr angle cls service",
+    author="paddle-dev",
+    author_email="paddle-dev@baidu.com",
+    type="cv/text_angle_cls",
+)
+class OCRCls(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.text_classifier = TextClassifier(cfg)
+
+    def merge_configs(
+        self,
+    ):
+        # default 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 text angle 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 text detection box 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."
+
+        img_list = []
+        for img in predicted_data:
+            if img is None:
+                continue
+            img_list.append(img)
+
+        rec_res_final = []
+        try:
+            img_list, cls_res, predict_time = self.text_classifier(img_list)
+            for dno in range(len(cls_res)):
+                angle, score = cls_res[dno]
+                rec_res_final.append(
+                    {
+                        "angle": angle,
+                        "confidence": float(score),
+                    }
+                )
+        except Exception as e:
+            print(e)
+            return [[]]
+
+        return [rec_res_final]
+
+    @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 = OCRCls()
+    ocr._initialize()
+    image_path = [
+        "./doc/imgs_words/ch/word_1.jpg",
+        "./doc/imgs_words/ch/word_2.jpg",
+        "./doc/imgs_words/ch/word_3.jpg",
+    ]
+    res = ocr.predict(paths=image_path)
+    print(res)
--- a/deploy/hubserving/ocr_cls/params.py
+++ b/deploy/hubserving/ocr_cls/params.py
@@ -0,0 +1,37 @@
+# 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
+
+
+class Config(object):
+    pass
+
+
+def read_params():
+    cfg = Config()
+
+    # params for text classifier
+    cfg.cls_model_dir = "./inference/ch_ppocr_mobile_v2.0_cls_infer/"
+    cfg.cls_image_shape = "3, 48, 192"
+    cfg.label_list = ["0", "180"]
+    cfg.cls_batch_num = 30
+    cfg.cls_thresh = 0.9
+
+    cfg.use_pdserving = False
+    cfg.use_tensorrt = False
+
+    return cfg
--- a/deploy/hubserving/ocr_det/init.py
+++ b/deploy/hubserving/ocr_det/init.py
@@ -0,0 +1,13 @@
+# 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.
--- a/deploy/hubserving/ocr_det/config.json
+++ b/deploy/hubserving/ocr_det/config.json
@@ -0,0 +1,15 @@
+{
+    "modules_info": {
+        "ocr_det": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8865,
+    "use_multiprocess": false,
+    "workers": 2    
+}
--- a/deploy/hubserving/ocr_det/module.py
+++ b/deploy/hubserving/ocr_det/module.py
@@ -0,0 +1,155 @@
+# 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 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 tools.infer.predict_det import TextDetector
+from tools.infer.utility import parse_args
+from deploy.hubserving.ocr_system.params import read_params
+
+
+@moduleinfo(
+    name="ocr_det",
+    version="1.0.0",
+    summary="ocr detection service",
+    author="paddle-dev",
+    author_email="paddle-dev@baidu.com",
+    type="cv/text_detection",
+)
+class OCRDet(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.text_detector = TextDetector(cfg)
+
+    def merge_configs(
+        self,
+    ):
+        # default 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 text box 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 text detection box 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
+            dt_boxes, elapse = self.text_detector(img)
+            logger.info("Predict time : {}".format(elapse))
+
+            rec_res_final = []
+            for dno in range(len(dt_boxes)):
+                rec_res_final.append(
+                    {"text_region": dt_boxes[dno].astype(np.int32).tolist()}
+                )
+            all_results.append(rec_res_final)
+        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 = OCRDet()
+    ocr._initialize()
+    image_path = [
+        "./doc/imgs/11.jpg",
+        "./doc/imgs/12.jpg",
+    ]
+    res = ocr.predict(paths=image_path)
+    print(res)
--- a/deploy/hubserving/ocr_det/params.py
+++ b/deploy/hubserving/ocr_det/params.py
@@ -0,0 +1,48 @@
+# 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
+
+
+class Config(object):
+    pass
+
+
+def read_params():
+    cfg = Config()
+
+    # params for text detector
+    cfg.det_algorithm = "DB"
+    cfg.det_model_dir = "./inference/PP-OCRv3_mobile_det_infer/"
+    cfg.det_limit_side_len = 960
+    cfg.det_limit_type = "max"
+
+    # DB params
+    cfg.det_db_thresh = 0.3
+    cfg.det_db_box_thresh = 0.6
+    cfg.det_db_unclip_ratio = 1.5
+    cfg.use_dilation = False
+    cfg.det_db_score_mode = "fast"
+
+    # #EAST params
+    # cfg.det_east_score_thresh = 0.8
+    # cfg.det_east_cover_thresh = 0.1
+    # cfg.det_east_nms_thresh = 0.2
+
+    cfg.use_pdserving = False
+    cfg.use_tensorrt = False
+
+    return cfg
--- a/deploy/hubserving/ocr_rec/init.py
+++ b/deploy/hubserving/ocr_rec/init.py
@@ -0,0 +1,13 @@
+# 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.
--- a/deploy/hubserving/ocr_rec/config.json
+++ b/deploy/hubserving/ocr_rec/config.json
@@ -0,0 +1,15 @@
+{
+    "modules_info": {
+        "ocr_rec": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8867,
+    "use_multiprocess": false,
+    "workers": 2
+}
--- a/deploy/hubserving/ocr_rec/module.py
+++ b/deploy/hubserving/ocr_rec/module.py
@@ -0,0 +1,160 @@
+# 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 paddlehub
+from paddlehub.common.logger import logger
+from paddlehub.module.module import moduleinfo, runnable, serving
+import cv2
+import paddlehub as hub
+
+from tools.infer.utility import base64_to_cv2
+from tools.infer.predict_rec import TextRecognizer
+from tools.infer.utility import parse_args
+from deploy.hubserving.ocr_rec.params import read_params
+
+
+@moduleinfo(
+    name="ocr_rec",
+    version="1.0.0",
+    summary="ocr recognition service",
+    author="paddle-dev",
+    author_email="paddle-dev@baidu.com",
+    type="cv/text_recognition",
+)
+class OCRRec(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.text_recognizer = TextRecognizer(cfg)
+
+    def merge_configs(
+        self,
+    ):
+        # default 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 text box 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 text detection box 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."
+
+        img_list = []
+        for img in predicted_data:
+            if img is None:
+                continue
+            img_list.append(img)
+
+        rec_res_final = []
+        try:
+            rec_res, predict_time = self.text_recognizer(img_list)
+            for dno in range(len(rec_res)):
+                text, score = rec_res[dno]
+                rec_res_final.append(
+                    {
+                        "text": text,
+                        "confidence": float(score),
+                    }
+                )
+        except Exception as e:
+            print(e)
+            return [[]]
+
+        return [rec_res_final]
+
+    @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 = OCRRec()
+    ocr._initialize()
+    image_path = [
+        "./doc/imgs_words/ch/word_1.jpg",
+        "./doc/imgs_words/ch/word_2.jpg",
+        "./doc/imgs_words/ch/word_3.jpg",
+    ]
+    res = ocr.predict(paths=image_path)
+    print(res)
--- a/deploy/hubserving/ocr_rec/params.py
+++ b/deploy/hubserving/ocr_rec/params.py
@@ -0,0 +1,41 @@
+# 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
+
+
+class Config(object):
+    pass
+
+
+def read_params():
+    cfg = Config()
+
+    # params for text recognizer
+    cfg.rec_algorithm = "CRNN"
+    cfg.rec_model_dir = "./inference/ch_PP-OCRv3_rec_infer/"
+
+    cfg.rec_image_shape = "3, 48, 320"
+    cfg.rec_batch_num = 6
+    cfg.max_text_length = 25
+
+    cfg.rec_char_dict_path = "./ppocr/utils/ppocr_keys_v1.txt"
+    cfg.use_space_char = True
+
+    cfg.use_pdserving = False
+    cfg.use_tensorrt = False
+
+    return cfg
--- a/deploy/hubserving/ocr_system/init.py
+++ b/deploy/hubserving/ocr_system/init.py
@@ -0,0 +1,13 @@
+# 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.
--- a/deploy/hubserving/ocr_system/config.json
+++ b/deploy/hubserving/ocr_system/config.json
@@ -0,0 +1,15 @@
+{
+    "modules_info": {
+        "ocr_system": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8868,
+    "use_multiprocess": false,
+    "workers": 2
+}
--- a/deploy/hubserving/ocr_system/module.py
+++ b/deploy/hubserving/ocr_system/module.py
@@ -0,0 +1,165 @@
+# 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 tools.infer.predict_system import TextSystem
+from tools.infer.utility import parse_args
+from deploy.hubserving.ocr_system.params import read_params
+
+
+@moduleinfo(
+    name="ocr_system",
+    version="1.0.0",
+    summary="ocr system service",
+    author="paddle-dev",
+    author_email="paddle-dev@baidu.com",
+    type="cv/PP-OCR_system",
+)
+class OCRSystem(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.text_sys = TextSystem(cfg)
+
+    def merge_configs(
+        self,
+    ):
+        # default 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()
+            dt_boxes, rec_res, _ = self.text_sys(img)
+            elapse = time.time() - starttime
+            logger.info("Predict time: {}".format(elapse))
+
+            dt_num = len(dt_boxes)
+            rec_res_final = []
+
+            for dno in range(dt_num):
+                text, score = rec_res[dno]
+                rec_res_final.append(
+                    {
+                        "text": text,
+                        "confidence": float(score),
+                        "text_region": dt_boxes[dno].astype(np.int32).tolist(),
+                    }
+                )
+            all_results.append(rec_res_final)
+        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)
--- a/deploy/hubserving/ocr_system/params.py
+++ b/deploy/hubserving/ocr_system/params.py
@@ -0,0 +1,68 @@
+# 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
+
+
+class Config(object):
+    pass
+
+
+def read_params():
+    cfg = Config()
+
+    # params for text detector
+    cfg.det_algorithm = "DB"
+    cfg.det_model_dir = "./inference/PP-OCRv3_mobile_det_infer/"
+    cfg.det_limit_side_len = 960
+    cfg.det_limit_type = "max"
+
+    # DB params
+    cfg.det_db_thresh = 0.3
+    cfg.det_db_box_thresh = 0.5
+    cfg.det_db_unclip_ratio = 1.6
+    cfg.use_dilation = False
+    cfg.det_db_score_mode = "fast"
+
+    # EAST params
+    cfg.det_east_score_thresh = 0.8
+    cfg.det_east_cover_thresh = 0.1
+    cfg.det_east_nms_thresh = 0.2
+
+    # params for text recognizer
+    cfg.rec_algorithm = "CRNN"
+    cfg.rec_model_dir = "./inference/ch_PP-OCRv3_rec_infer/"
+
+    cfg.rec_image_shape = "3, 48, 320"
+    cfg.rec_batch_num = 6
+    cfg.max_text_length = 25
+
+    cfg.rec_char_dict_path = "./ppocr/utils/ppocr_keys_v1.txt"
+    cfg.use_space_char = True
+
+    # params for text classifier
+    cfg.use_angle_cls = True
+    cfg.cls_model_dir = "./inference/ch_ppocr_mobile_v2.0_cls_infer/"
+    cfg.cls_image_shape = "3, 48, 192"
+    cfg.label_list = ["0", "180"]
+    cfg.cls_batch_num = 30
+    cfg.cls_thresh = 0.9
+
+    cfg.use_pdserving = False
+    cfg.use_tensorrt = False
+    cfg.drop_score = 0.5
+
+    return cfg
--- a/deploy/hubserving/readme.md
+++ b/deploy/hubserving/readme.md
@@ -0,0 +1,250 @@
+[English](readme_en.md) | 简体中文
+
+- [基于PaddleHub Serving的服务部署](#基于paddlehub-serving的服务部署)
+  - [1. 近期更新](#1-近期更新)
+  - [2. 快速启动服务](#2-快速启动服务)
+    - [2.1 安装PaddleHub](#21-安装PaddleHub)
+    - [2.2 下载推理模型](#22-下载推理模型)
+    - [2.3 安装服务模块](#23-安装服务模块)
+    - [2.4 启动服务](#24-启动服务)
+      - [2.4.1. 命令行命令启动（仅支持CPU）](#241-命令行命令启动仅支持cpu)
+      - [2.4.2 配置文件启动（支持CPU、GPU）](#242-配置文件启动支持cpugpu)
+  - [3. 发送预测请求](#3-发送预测请求)
+  - [4. 返回结果格式说明](#4-返回结果格式说明)
+  - [5. 自定义修改服务模块](#5-自定义修改服务模块)
+
+
+PaddleOCR提供2种服务部署方式：
+- 基于PaddleHub Serving的部署：代码路径为`./deploy/hubserving`，按照本教程使用；
+- 基于PaddleServing的部署：代码路径为`./deploy/pdserving`，使用方法参考[文档](../../deploy/pdserving/README_CN.md)。
+
+# 基于PaddleHub Serving的服务部署
+
+hubserving服务部署目录下包括文本检测、文本方向分类，文本识别、文本检测+文本方向分类+文本识别3阶段串联，版面分析、表格识别和PP-Structure七种服务包，请根据需求选择相应的服务包进行安装和启动。目录结构如下：
+```
+deploy/hubserving/
+  └─  ocr_cls     文本方向分类模块服务包
+  └─  ocr_det     文本检测模块服务包
+  └─  ocr_rec     文本识别模块服务包
+  └─  ocr_system  文本检测+文本方向分类+文本识别串联服务包
+  └─  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：
+```
+deploy/hubserving/ocr_system/
+  └─  __init__.py    空文件，必选
+  └─  config.json    配置文件，可选，使用配置启动服务时作为参数传入
+  └─  module.py      主模块，必选，包含服务的完整逻辑
+  └─  params.py      参数文件，必选，包含模型路径、前后处理参数等参数
+```
+## 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。
+
+## 2. 快速启动服务
+以下步骤以检测+识别2阶段串联服务为例，如果只需要检测服务或识别服务，替换相应文件路径即可。
+### 2.1 安装PaddleHub
+paddlehub 需要 python>3.6.2
+```bash
+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：
+| 模型 | 路径 |
+| ------- | - |
+| 检测模型 | `./inference/PP-OCRv3_mobile_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。
+
+### 2.3 安装服务模块
+PaddleOCR提供5种服务模块，根据需要安装所需模块。
+
+在Linux环境（Windows环境请将`/`替换为`\`）下，安装模块命令如下表：
+| 服务模块 | 命令 |
+| ------- | - |
+| 检测 | `hub install deploy/hubserving/ocr_det` |
+| 分类 | `hub install deploy/hubserving/ocr_cls` |
+| 识别 | `hub install deploy/hubserving/ocr_rec` |
+| 检测+识别串联 | `hub install deploy/hubserving/ocr_system` |
+| 表格识别 | `hub install deploy/hubserving/structure_table` |
+| PP-Structure | `hub install deploy/hubserving/structure_system` |
+| 版面分析 | `hub install deploy/hubserving/structure_layout` |
+| 关键信息抽取SER | `hub install deploy/hubserving/kie_ser` |
+| 关键信息抽取SER+RE | `hub install deploy/hubserving/kie_ser_re` |
+
+### 2.4 启动服务
+#### 2.4.1. 命令行命令启动（仅支持CPU）
+**启动命令：**
+```bash
+hub serving start --modules Module1==Version1, Module2==Version2, ... \
+                  --port 8866 \
+                  --use_multiprocess \
+                  --workers \
+```
+
+**参数：**
+|参数|用途|
+|---|---|
+|`--modules`/`-m`|PaddleHub Serving预安装模型，以多个Module==Version键值对的形式列出<br>**当不指定Version时，默认选择最新版本**|
+|`--port`/`-p`|服务端口，默认为8866|
+|`--use_multiprocess`|是否启用并发方式，默认为单进程方式，推荐多核CPU机器使用此方式<br>**Windows操作系统只支持单进程方式**|
+|`--workers`|在并发方式下指定的并发任务数，默认为`2*cpu_count-1`，其中`cpu_count`为CPU核数|
+
+如启动串联服务：
+```bash
+hub serving start -m ocr_system
+```
+
+这样就完成了一个服务化API的部署，使用默认端口号8866。
+
+#### 2.4.2 配置文件启动（支持CPU、GPU）
+**启动命令：**
+```bash
+hub serving start -c config.json
+```
+
+其中，`config.json`格式如下：
+```json
+{
+    "modules_info": {
+        "ocr_system": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8868,
+    "use_multiprocess": false,
+    "workers": 2
+}
+```
+
+- `init_args`中的可配参数与`module.py`中的`_initialize`函数接口一致。
+
+   **当`use_gpu`为`true`时，表示使用GPU启动服务。**
+- `predict_args`中的可配参数与`module.py`中的`predict`函数接口一致。
+
+**注意：**
+- 使用配置文件启动服务时，其他参数会被忽略。
+- 如果使用GPU预测(即，`use_gpu`置为`true`)，则需要在启动服务之前，设置CUDA_VISIBLE_DEVICES环境变量，如：
+  ```bash
+  export CUDA_VISIBLE_DEVICES=0
+  ```
+- **`use_gpu`不可与`use_multiprocess`同时为`true`**。
+
+如，使用GPU 3号卡启动串联服务：
+```bash
+export CUDA_VISIBLE_DEVICES=3
+hub serving start -c deploy/hubserving/ocr_system/config.json
+```
+
+## 3. 发送预测请求
+配置好服务端，可使用以下命令发送预测请求，获取预测结果：
+```bash
+python tools/test_hubserving.py --server_url=server_url --image_dir=image_path
+```
+
+需要给脚本传递2个参数：
+- `server_url`：服务地址，格式为`http://[ip_address]:[port]/predict/[module_name]`
+
+   例如，如果使用配置文件启动分类，检测、识别，检测+分类+识别3阶段，表格识别和PP-Structure服务
+
+   并为每个服务修改了port，那么发送请求的url将分别是：
+   ```
+   http://127.0.0.1:8865/predict/ocr_det
+   http://127.0.0.1:8866/predict/ocr_cls
+   http://127.0.0.1:8867/predict/ocr_rec
+   http://127.0.0.1:8868/predict/ocr_system
+   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`
+
+访问示例：
+```bash
+python tools/test_hubserving.py --server_url=http://127.0.0.1:8868/predict/ocr_system --image_dir=./doc/imgs/ --visualize=false
+```
+
+## 4. 返回结果格式说明
+返回结果为列表（list），列表中的每一项为词典（dict），词典一共可能包含3种字段，信息如下：
+|字段名称|数据类型|意义|
+|---|---|---|
+|angle|str|文本角度|
+|text|str|文本内容|
+|confidence|float| 文本识别置信度或文本角度分类置信度|
+|text_region|list|文本位置坐标|
+|html|str|表格的html字符串|
+|regions|list|版面分析+表格识别+OCR的结果，每一项为一个list<br>包含表示区域坐标的`bbox`，区域类型的`type`和区域结果的`res`三个字段|
+|layout|list|版面分析的结果，每一项一个dict，包含版面区域坐标的`bbox`，区域类型的`label`|
+
+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 |kie_ser |kie_re |
+|---             |---     |---     |---     |---        |---             |---              |---              |---     |---    |
+|angle           |        |✔       |        |✔          |                |                 |                 |
+|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。
+
+## 5. 自定义修改服务模块
+如果需要修改服务逻辑，一般需要操作以下步骤（以修改`deploy/hubserving/ocr_system`为例）：
+
+1. 停止服务：
+   ```bash
+   hub serving stop --port/-p XXXX
+   ```
+2. 到`deploy/hubserving/ocr_system`下的`module.py`和`params.py`等文件中根据实际需求修改代码。
+
+   例如，如果需要替换部署服务所用模型，则需要到`params.py`中修改模型路径参数`det_model_dir`和`rec_model_dir`，如果需要关闭文本方向分类器，则将参数`use_angle_cls`置为`False`
+
+   当然，同时可能还需要修改其他相关参数，请根据实际情况修改调试。
+
+   **强烈建议修改后先直接运行`module.py`调试，能正确运行预测后再启动服务测试。**
+
+   **注意：** PPOCR-v3识别模型使用的图片输入shape为`3,48,320`,因此需要修改`params.py`中的`cfg.rec_image_shape = "3, 48, 320"`，如果不使用PPOCR-v3识别模型，则无需修改该参数。
+3. （可选）如果想要重命名模块需要更改`module.py`文件中的以下行：
+   - [`from deploy.hubserving.ocr_system.params import read_params`中的`ocr_system`](https://github.com/PaddlePaddle/PaddleOCR/blob/a923f35de57b5e378f8dd16e54d0a3e4f51267fd/deploy/hubserving/ocr_system/module.py#L35)
+   - [`name="ocr_system",`中的`ocr_system`](https://github.com/PaddlePaddle/PaddleOCR/blob/a923f35de57b5e378f8dd16e54d0a3e4f51267fd/deploy/hubserving/ocr_system/module.py#L39)
+4. （可选）可能需要删除`__pycache__`目录以强制刷新CPython缓存：
+   ```bash
+   find deploy/hubserving/ocr_system -name '__pycache__' -exec rm -r {} \;
+   ```
+5. 安装修改后的新服务包：
+   ```bash
+   hub install deploy/hubserving/ocr_system
+   ```
+6. 重新启动服务：
+   ```bash
+   hub serving start -m ocr_system
+   ```
--- a/deploy/hubserving/readme_en.md
+++ b/deploy/hubserving/readme_en.md
@@ -0,0 +1,249 @@
+English | [简体中文](readme.md)
+
+- [Service deployment based on PaddleHub Serving](#service-deployment-based-on-paddlehub-serving)
+  - [1. Update](#1-update)
+  - [2. Quick start service](#2-quick-start-service)
+    - [2.1 Install PaddleHub](#21-install-paddlehub)
+    - [2.2 Download inference model](#22-download-inference-model)
+    - [2.3 Install Service Module](#23-install-service-module)
+    - [2.4 Start service](#24-start-service)
+      - [2.4.1 Start with command line parameters (CPU only)](#241-start-with-command-line-parameters-cpu-only)
+      - [2.4.2 Start with configuration file（CPU and GPU）](#242-start-with-configuration-filecpugpu)
+  - [3. Send prediction requests](#3-send-prediction-requests)
+  - [4. Returned result format](#4-returned-result-format)
+  - [5. User-defined service module modification](#5-user-defined-service-module-modification)
+
+PaddleOCR provides 2 service deployment methods:
+- Based on **PaddleHub Serving**: Code path is `./deploy/hubserving`. Please follow this tutorial.
+- Based on **PaddleServing**: Code path is `./deploy/pdserving`. Please refer to the [tutorial](../../deploy/pdserving/README.md) for usage.
+
+# Service deployment based on PaddleHub Serving
+
+The hubserving service deployment directory includes seven service packages: text detection, text angle class, text recognition, text detection+text angle class+text recognition three-stage series connection, layout analysis, table recognition, and PP-Structure. Please select the corresponding service package to install and start the service according to your needs. The directory is as follows:
+```
+deploy/hubserving/
+  └─  ocr_det     text detection module service package
+  └─  ocr_cls     text angle class module service package
+  └─  ocr_rec     text recognition module service package
+  └─  ocr_system  text detection+text angle class+text recognition three-stage series connection service package
+  └─  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:
+```
+deploy/hubserving/ocr_system/
+  └─  __init__.py    Empty file, required
+  └─  config.json    Configuration file, optional, passed in as a parameter when using configuration to start the service
+  └─  module.py      Main module file, required, contains the complete logic of the service
+  └─  params.py      Parameter file, required, including parameters such as model path, pre and post-processing parameters
+```
+## 1. Update
+
+* 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
+The following steps take the 2-stage series service as an example. If only the detection service or recognition service is needed, replace the corresponding file path.
+
+### 2.1 Install PaddleHub
+```bash
+pip3 install paddlehub==2.1.0 --upgrade
+```
+
+### 2.2 Download inference model
+Before installing the service module, you need to prepare the inference model and put it in the correct path. By default, the PP-OCRv3 models are used, and the default model path is:
+| Model | Path |
+| ------- | - |
+| text detection model | ./inference/PP-OCRv3_mobile_det_infer/ |
+| 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.
+
+### 2.3 Install Service Module
+PaddleOCR provides 5 kinds of service modules, install the required modules according to your needs.
+
+* On the Linux platform(replace `/` with `\` if using Windows), the examples are as the following table:
+| Service model | Command |
+| text detection | `hub install deploy/hubserving/ocr_det` |
+| text angle class: | `hub install deploy/hubserving/ocr_cls` |
+| text recognition: | `hub install deploy/hubserving/ocr_rec` |
+| 2-stage series: | `hub install deploy/hubserving/ocr_system` |
+| table recognition | `hub install deploy/hubserving/structure_table` |
+| PP-Structure | `hub install deploy/hubserving/structure_system` |
+| KIE(SER) | `hub install deploy/hubserving/kie_ser` |
+| KIE(SER+RE) | `hub install deploy/hubserving/kie_ser_re` |
+
+### 2.4 Start service
+#### 2.4.1 Start with command line parameters (CPU only)
+**start command:**
+```bash
+hub serving start --modules Module1==Version1, Module2==Version2, ... \
+                  --port 8866 \
+                  --use_multiprocess \
+                  --workers \
+```
+
+**Parameters:**
+|parameters|usage|
+|---|---|
+|`--modules`/`-m`|PaddleHub Serving pre-installed model, listed in the form of multiple Module==Version key-value pairs<br>**When Version is not specified, the latest version is selected by default**|
+|`--port`/`-p`|Service port, default is 8866|
+|`--use_multiprocess`|Enable concurrent mode, by default using the single-process mode, this mode is recommended for multi-core CPU machines<br>**Windows operating system only supports single-process mode**|
+|`--workers`|The number of concurrent tasks specified in concurrent mode, the default is `2*cpu_count-1`, where `cpu_count` is the number of CPU cores|
+
+For example, start the 2-stage series service:
+```bash
+hub serving start -m ocr_system
+```
+
+This completes the deployment of a service API, using the default port number 8866.
+
+#### 2.4.2 Start with configuration file（CPU and GPU）
+**start command:**
+```bash
+hub serving start --config/-c config.json
+```
+
+In which the format of `config.json` is as follows:
+```json
+{
+    "modules_info": {
+        "ocr_system": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8868,
+    "use_multiprocess": false,
+    "workers": 2
+}
+```
+- The configurable parameters in `init_args` are consistent with the `_initialize` function interface in `module.py`.
+
+  **When `use_gpu` is `true`, it means that the GPU is used to start the service**.
+- The configurable parameters in `predict_args` are consistent with the `predict` function interface in `module.py`.
+
+  **Note:**
+  - When using the configuration file to start the service, other parameters will be ignored.
+  - If you use GPU prediction (that is, `use_gpu` is set to `true`), you need to set the environment variable CUDA_VISIBLE_DEVICES before starting the service, such as:
+    ```bash
+    export CUDA_VISIBLE_DEVICES=0
+    ```
+  - **`use_gpu` and `use_multiprocess` cannot be `true` at the same time.**
+
+For example, use GPU card No. 3 to start the 2-stage series service:
+```bash
+export CUDA_VISIBLE_DEVICES=3
+hub serving start -c deploy/hubserving/ocr_system/config.json
+```
+
+## 3. Send prediction requests
+After the service starts, you can use the following command to send a prediction request to obtain the prediction result:
+```bash
+python tools/test_hubserving.py --server_url=server_url --image_dir=image_path
+```
+
+Two parameters need to be passed to the script:
+- **server_url**:service address, the format of which is
+`http://[ip_address]:[port]/predict/[module_name]`
+
+  For example, if using the configuration file to start the text angle classification, text detection, text recognition, detection+classification+recognition 3 stages, table recognition and PP-Structure service,
+
+  also modified the port for each service, then the `server_url` to send the request will be:
+
+  ```
+  http://127.0.0.1:8865/predict/ocr_det
+  http://127.0.0.1:8866/predict/ocr_cls
+  http://127.0.0.1:8867/predict/ocr_rec
+  http://127.0.0.1:8868/predict/ocr_system
+  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, which can be a single image path or an image directory path
+- **visualize**:Whether to visualize the results, the default value is False
+- **output**:The folder to save the Visualization result, the default value is `./hubserving_result`
+
+Example:
+```bash
+python tools/test_hubserving.py --server_url=http://127.0.0.1:8868/predict/ocr_system --image_dir=./doc/imgs/ --visualize=false`
+```
+
+## 4. Returned result format
+The returned result is a list. Each item in the list is a dictionary which may contain three fields. The information is as follows:
+
+|field name|data type|description|
+|----|----|----|
+|angle|str|angle|
+|text|str|text content|
+|confidence|float|text recognition confidence|
+|text_region|list|text location coordinates|
+|html|str|table HTML string|
+|regions|list|The result of layout analysis + table recognition + OCR, each item is a list<br>including `bbox` indicating area coordinates, `type` of area type and `res` of area results|
+|layout|list|The result of layout analysis, each item is a dict, including `bbox` indicating area coordinates, `label` of area type|
+
+The fields returned by different modules are different. For example, the results returned by the text recognition service module do not contain `text_region`, detailed table is as follows:
+
+|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.
+
+## 5. User-defined service module modification
+If you need to modify the service logic, the following steps are generally required (take the modification of `deploy/hubserving/ocr_system` for example):
+
+1. Stop service:
+```bash
+hub serving stop --port/-p XXXX
+```
+2. Modify the code in the corresponding files under `deploy/hubserving/ocr_system`, such as `module.py` and `params.py`, to your actual needs.
+
+   For example, if you need to replace the model used by the deployed service, you need to modify model path parameters `det_model_dir` and `rec_model_dir` in `params.py`. If you want to turn off the text direction classifier, set the parameter `use_angle_cls` to `False`.
+
+   Of course, other related parameters may need to be modified at the same time. Please modify and debug according to the actual situation.
+
+   **It is suggested to run `module.py` directly for debugging after modification before starting the service test.**
+
+   **Note** The image input shape used by the PPOCR-v3 recognition model is `3, 48, 320`, so you need to modify `cfg.rec_image_shape = "3, 48, 320"` in `params.py`, if you do not use the PPOCR-v3 recognition model, then there is no need to modify this parameter.
+3. (Optional) If you want to rename the module, the following lines should be modified:
+   - [`ocr_system` within `from deploy.hubserving.ocr_system.params import read_params`](https://github.com/PaddlePaddle/PaddleOCR/blob/a923f35de57b5e378f8dd16e54d0a3e4f51267fd/deploy/hubserving/ocr_system/module.py#L35)
+   - [`ocr_system` within `name="ocr_system",`](https://github.com/PaddlePaddle/PaddleOCR/blob/a923f35de57b5e378f8dd16e54d0a3e4f51267fd/deploy/hubserving/ocr_system/module.py#L39)
+4. (Optional) It may require you to delete the directory `__pycache__` to force flush build cache of CPython:
+   ```bash
+   find deploy/hubserving/ocr_system -name '__pycache__' -exec rm -r {} \;
+   ```
+5. Install modified service module:
+   ```bash
+   hub install deploy/hubserving/ocr_system/
+   ```
+6. Restart service:
+   ```bash
+   hub serving start -m ocr_system
+   ```
--- a/deploy/hubserving/structure_layout/init.py
+++ b/deploy/hubserving/structure_layout/init.py
@@ -0,0 +1,13 @@
+# 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.
--- a/deploy/hubserving/structure_layout/config.json
+++ b/deploy/hubserving/structure_layout/config.json
@@ -0,0 +1,15 @@
+{
+    "modules_info": {
+        "structure_layout": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8871,
+    "use_multiprocess": false,
+    "workers": 2
+}
--- a/deploy/hubserving/structure_layout/module.py
+++ b/deploy/hubserving/structure_layout/module.py
@@ -0,0 +1,148 @@
+# 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 paddlehub as hub
+
+from tools.infer.utility import base64_to_cv2
+from ppstructure.layout.predict_layout import LayoutPredictor as _LayoutPredictor
+from ppstructure.utility import parse_args
+from deploy.hubserving.structure_layout.params import read_params
+
+
+@moduleinfo(
+    name="structure_layout",
+    version="1.0.0",
+    summary="PP-Structure layout service",
+    author="paddle-dev",
+    author_email="paddle-dev@baidu.com",
+    type="cv/structure_layout",
+)
+class LayoutPredictor(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.layout_predictor = _LayoutPredictor(cfg)
+
+    def merge_configs(self):
+        # default 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 layout results 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()
+            res, _ = self.layout_predictor(img)
+            elapse = time.time() - starttime
+            logger.info("Predict time: {}".format(elapse))
+
+            for item in res:
+                item["bbox"] = item["bbox"].tolist()
+            all_results.append({"layout": 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__":
+    layout = LayoutPredictor()
+    layout._initialize()
+    image_path = ["./ppstructure/docs/table/1.png"]
+    res = layout.predict(paths=image_path)
+    print(res)
--- a/deploy/hubserving/structure_layout/params.py
+++ b/deploy/hubserving/structure_layout/params.py
@@ -0,0 +1,32 @@
+# 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
+
+
+class Config(object):
+    pass
+
+
+def read_params():
+    cfg = Config()
+
+    # params for layout analysis
+    cfg.layout_model_dir = "./inference/picodet_lcnet_x1_0_fgd_layout_infer/"
+    cfg.layout_dict_path = "./ppocr/utils/dict/layout_dict/layout_publaynet_dict.txt"
+    cfg.layout_score_threshold = 0.5
+    cfg.layout_nms_threshold = 0.5
+    return cfg
--- a/deploy/hubserving/structure_system/init.py
+++ b/deploy/hubserving/structure_system/init.py
@@ -0,0 +1,13 @@
+# 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.
--- a/deploy/hubserving/structure_system/config.json
+++ b/deploy/hubserving/structure_system/config.json
@@ -0,0 +1,15 @@
+{
+    "modules_info": {
+        "structure_system": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8870,
+    "use_multiprocess": false,
+    "workers": 2
+}
--- a/deploy/hubserving/structure_system/module.py
+++ b/deploy/hubserving/structure_system/module.py
@@ -0,0 +1,154 @@
+# 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.predict_system import StructureSystem as PPStructureSystem
+from ppstructure.predict_system import save_structure_res
+from ppstructure.utility import parse_args
+from deploy.hubserving.structure_system.params import read_params
+
+
+@moduleinfo(
+    name="structure_system",
+    version="1.0.0",
+    summary="PP-Structure system service",
+    author="paddle-dev",
+    author_email="paddle-dev@baidu.com",
+    type="cv/structure_system",
+)
+class StructureSystem(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.table_sys = PPStructureSystem(cfg)
+
+    def merge_configs(self):
+        # default 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()
+            res, _ = self.table_sys(img)
+            elapse = time.time() - starttime
+            logger.info("Predict time: {}".format(elapse))
+
+            # parse result
+            res_final = []
+            for region in res:
+                region.pop("img")
+                res_final.append(region)
+            all_results.append({"regions": res_final})
+        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__":
+    structure_system = StructureSystem()
+    structure_system._initialize()
+    image_path = ["./ppstructure/docs/table/1.png"]
+    res = structure_system.predict(paths=image_path)
+    print(res)
--- a/deploy/hubserving/structure_system/params.py
+++ b/deploy/hubserving/structure_system/params.py
@@ -0,0 +1,33 @@
+# 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.structure_table.params import read_params as table_read_params
+
+
+def read_params():
+    cfg = table_read_params()
+
+    # params for layout parser model
+    cfg.layout_model_dir = ""
+    cfg.layout_dict_path = "./ppocr/utils/dict/layout_publaynet_dict.txt"
+    cfg.layout_score_threshold = 0.5
+    cfg.layout_nms_threshold = 0.5
+
+    cfg.mode = "structure"
+    cfg.output = "./output"
+    return cfg
--- a/deploy/hubserving/structure_table/init.py
+++ b/deploy/hubserving/structure_table/init.py
@@ -0,0 +1,13 @@
+# 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.
--- a/deploy/hubserving/structure_table/config.json
+++ b/deploy/hubserving/structure_table/config.json
@@ -0,0 +1,15 @@
+{
+    "modules_info": {
+        "structure_table": {
+            "init_args": {
+                "version": "1.0.0",
+                "use_gpu": true
+            },
+            "predict_args": {
+            }
+        }
+    },
+    "port": 8869,
+    "use_multiprocess": false,
+    "workers": 2
+}
--- a/deploy/hubserving/structure_table/module.py
+++ b/deploy/hubserving/structure_table/module.py
@@ -0,0 +1,148 @@
+# 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.table.predict_table import TableSystem as _TableSystem
+from ppstructure.predict_system import save_structure_res
+from ppstructure.utility import parse_args
+from deploy.hubserving.structure_table.params import read_params
+
+
+@moduleinfo(
+    name="structure_table",
+    version="1.0.0",
+    summary="PP-Structure table service",
+    author="paddle-dev",
+    author_email="paddle-dev@baidu.com",
+    type="cv/structure_table",
+)
+class TableSystem(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.table_sys = _TableSystem(cfg)
+
+    def merge_configs(self):
+        # default 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()
+            res, _ = self.table_sys(img)
+            elapse = time.time() - starttime
+            logger.info("Predict time: {}".format(elapse))
+
+            all_results.append({"html": res["html"]})
+        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__":
+    table_system = TableSystem()
+    table_system._initialize()
+    image_path = ["./ppstructure/docs/table/table.jpg"]
+    res = table_system.predict(paths=image_path)
+    print(res)
--- a/deploy/hubserving/structure_table/params.py
+++ b/deploy/hubserving/structure_table/params.py
@@ -0,0 +1,30 @@
+# 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
+
+
+def read_params():
+    cfg = pp_ocr_read_params()
+
+    # params for table structure model
+    cfg.table_max_len = 488
+    cfg.table_model_dir = "./inference/en_ppocr_mobile_v2.0_table_structure_infer/"
+    cfg.table_char_dict_path = "./ppocr/utils/dict/table_structure_dict.txt"
+    cfg.show_log = False
+    return cfg