diff --git a/deploy/hubserving/.ipynb_checkpoints/serving-checkpoint.md b/deploy/hubserving/.ipynb_checkpoints/serving-checkpoint.md
new file mode 100644
index 0000000000000000000000000000000000000000..da043921388ad59a5b6b9e60ebd6f1200454ff25
--- /dev/null
+++ b/deploy/hubserving/.ipynb_checkpoints/serving-checkpoint.md
@@ -0,0 +1,109 @@
+# 服务部署
+
+PaddleOCR提供2种服务部署方式：
+- 基于HubServing的部署：已集成到PaddleOCR中（[code](https://github.com/PaddlePaddle/PaddleOCR/tree/develop/deploy/ocr_hubserving)），按照本教程使用；
+- 基于PaddleServing的部署：详见PaddleServing官网[demo](https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/ocr)，后续也将集成到PaddleOCR。
+
+服务部署目录下包括检测、识别、2阶段串联三种服务包，根据需求选择相应的服务包进行安装和启动。目录如下：
+```
+deploy/hubserving/
+ └─ ocr_det 检测模块服务包
+ └─ ocr_rec 识别模块服务包
+ └─ ocr_system 检测+识别串联服务包
+```
+
+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
+ └─ config.json 配置文件，启动服务时作为参数传入
+ └─ module.py 主模块，包含服务的完整逻辑
+```
+
+## 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。
+### 1. 安装paddlehub
+```pip3 install paddlehub --upgrade -i https://pypi.tuna.tsinghua.edu.cn/simple```
+
+### 2. 安装服务模块
+PaddleOCR提供3种服务模块，根据需要安装所需模块。如：
+
+安装检测服务模块：
+```hub install deploy/hubserving/ocr_det/```
+
+或，安装识别服务模块：
+```hub install deploy/hubserving/ocr_rec/```
+
+或，安装检测+识别串联服务模块：
+```hub install deploy/hubserving/ocr_system/```
+
+### 3. 修改配置文件
+在config.json中指定模型路径、是否使用GPU、是否对结果做可视化等参数，如，串联服务ocr_system的配置：
+```python
+{
+ "modules_info": {
+ "ocr_system": {
+ "init_args": {
+ "version": "1.0.0",
+ "det_model_dir": "./inference/det/",
+ "rec_model_dir": "./inference/rec/",
+ "use_gpu": true
+ },
+ "predict_args": {
+ "visualization": false
+ }
+ }
+ }
+}
+```
+其中，模型路径对应的模型为```inference模型```。
+
+### 4. 运行启动命令
+```hub serving start -m ocr_system --config hubserving/ocr_det/config.json```
+
+这样就完成了一个服务化API的部署，默认端口号为8866。
+
+**NOTE:** 如使用GPU预测(即，config中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：```export CUDA_VISIBLE_DEVICES=0```，否则不用设置。
+
+## 发送预测请求
+配置好服务端，以下数行代码即可实现发送预测请求，获取预测结果:
+
+```python
+import requests
+import json
+import cv2
+import base64
+
+def cv2_to_base64(image):
+ return base64.b64encode(image).decode('utf8')
+
+# 发送HTTP请求
+data = {'images':[cv2_to_base64(open("./doc/imgs/11.jpg", 'rb').read())]}
+headers = {"Content-type": "application/json"}
+# url = "http://127.0.0.1:8866/predict/ocr_det"
+# url = "http://127.0.0.1:8866/predict/ocr_rec"
+url = "http://127.0.0.1:8866/predict/ocr_system"
+r = requests.post(url=url, headers=headers, data=json.dumps(data))
+
+# 打印预测结果
+print(r.json()["results"])
+```
+
+你可能需要根据实际情况修改```url```字符串中的端口号和服务模块名称。
+
+上面所示代码都已写入测试脚本，可直接运行命令：```python tools/test_hubserving.py```
+
+## 自定义修改服务模块
+如果需要修改服务逻辑，你一般需要操作以下步骤：
+
+1、 停止服务
+```hub serving stop -m ocr_system```
+
+2、 到相应的module.py文件中根据实际需求修改代码
+
+3、 卸载旧服务包
+```hub uninstall ocr_system```
+
+4、 安装修改后的新服务包
+```hub install deploy/hubserving/ocr_system/```
+
diff --git a/deploy/hubserving/ocr_det/.ipynb_checkpoints/params-checkpoint.py b/deploy/hubserving/ocr_det/.ipynb_checkpoints/params-checkpoint.py
new file mode 100644
index 0000000000000000000000000000000000000000..0d32c1f51b23d72379361fb504b33558c52d783c
--- /dev/null
+++ b/deploy/hubserving/ocr_det/.ipynb_checkpoints/params-checkpoint.py
@@ -0,0 +1,41 @@
+# -*- coding:utf-8 -*-
+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/ch_det_mv3_db/"
+ cfg.det_model_dir = "./inference/det/"
+ cfg.det_max_side_len = 960
+
+ #DB parmas
+ cfg.det_db_thresh =0.3
+ cfg.det_db_box_thresh =0.5
+ cfg.det_db_unclip_ratio =2.0
+
+ # #EAST parmas
+ # 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_det_mv3_crnn/"
+ # cfg.rec_model_dir = "./inference/rec/"
+
+ # cfg.rec_image_shape = "3, 32, 320"
+ # cfg.rec_char_type = 'ch'
+ # cfg.rec_batch_num = 30
+ # cfg.rec_char_dict_path = "./ppocr/utils/ppocr_keys_v1.txt"
+ # cfg.use_space_char = True
+
+ return cfg
\ No newline at end of file
diff --git a/deploy/ocr_hubserving/ocr_det/__init__.py b/deploy/hubserving/ocr_det/__init__.py
similarity index 100%
rename from deploy/ocr_hubserving/ocr_det/__init__.py
rename to deploy/hubserving/ocr_det/__init__.py
diff --git a/deploy/ocr_hubserving/ocr_det/config.json b/deploy/hubserving/ocr_det/config.json
similarity index 76%
rename from deploy/ocr_hubserving/ocr_det/config.json
rename to deploy/hubserving/ocr_det/config.json
index f995d0ed2bd4da3aaf39e654a5c7ab51e377e367..9f6fd50f1d4c75da176d77b882a4c4262c9da434 100644
--- a/deploy/ocr_hubserving/ocr_det/config.json
+++ b/deploy/hubserving/ocr_det/config.json
@@ -3,12 +3,14 @@
"ocr_det": {
"init_args": {
"version": "1.0.0",
- "det_model_dir": "./inference/ch_det_mv3_db/",
"use_gpu": true
},
"predict_args": {
"visualization": false
}
}
- }
+ },
+ "port": 8866,
+ "use_multiprocess": false,
+ "workers": 2
}
diff --git a/deploy/ocr_hubserving/ocr_det/module.py b/deploy/hubserving/ocr_det/module.py
similarity index 75%
rename from deploy/ocr_hubserving/ocr_det/module.py
rename to deploy/hubserving/ocr_det/module.py
index 0ee32d38e5b6b4502592b62a3f129a0e11a8cd7a..6b7bafb83ebb9cca112659f95b6556797972efc1 100644
--- a/deploy/ocr_hubserving/ocr_det/module.py
+++ b/deploy/hubserving/ocr_det/module.py
@@ -22,8 +22,6 @@ import paddlehub as hub
from tools.infer.utility import draw_boxes, base64_to_cv2
from tools.infer.predict_det import TextDetector
-class Config(object):
- pass
@moduleinfo(
name="ocr_det",
@@ -33,43 +31,28 @@ class Config(object):
author_email="paddle-dev@baidu.com",
type="cv/text_recognition")
class OCRDet(hub.Module):
- def _initialize(self,
- det_model_dir="",
- det_algorithm="DB",
- use_gpu=False
- ):
+ def _initialize(self, use_gpu=False):
"""
initialize with the necessary elements
"""
- self.config = Config()
- self.config.use_gpu = use_gpu
+ from ocr_det.params import read_params
+ cfg = read_params()
+
+ 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."
)
- self.config.ir_optim = True
- self.config.gpu_mem = 8000
-
- #params for text detector
- self.config.det_algorithm = det_algorithm
- self.config.det_model_dir = det_model_dir
- # self.config.det_model_dir = "./inference/det/"
-
- #DB parmas
- self.config.det_db_thresh =0.3
- self.config.det_db_box_thresh =0.5
- self.config.det_db_unclip_ratio =2.0
+ cfg.ir_optim = True
- #EAST parmas
- self.config.det_east_score_thresh = 0.8
- self.config.det_east_cover_thresh = 0.1
- self.config.det_east_nms_thresh = 0.2
+ self.text_detector = TextDetector(cfg)
def read_images(self, paths=[]):
images = []
@@ -83,10 +66,9 @@ class OCRDet(hub.Module):
images.append(img)
return images
- def det_text(self,
+ def predict(self,
images=[],
paths=[],
- det_max_side_len=960,
draw_img_save='ocr_det_result',
visualization=False):
"""
@@ -94,10 +76,8 @@ class OCRDet(hub.Module):
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
- use_gpu (bool): Whether to use gpu. Default false.
- output_dir (str): The directory to store output images.
+ draw_img_save (str): The directory to store output images.
visualization (bool): Whether to save image or not.
- box_thresh(float): the threshold of the detected text box's confidence
Returns:
res (list): The result of text detection box and save path of images.
"""
@@ -111,8 +91,6 @@ class OCRDet(hub.Module):
assert predicted_data != [], "There is not any image to be predicted. Please check the input data."
- self.config.det_max_side_len = det_max_side_len
- text_detector = TextDetector(self.config)
all_results = []
for img in predicted_data:
result = {'save_path': ''}
@@ -121,7 +99,7 @@ class OCRDet(hub.Module):
result['data'] = []
all_results.append(result)
continue
- dt_boxes, elapse = text_detector(img)
+ dt_boxes, elapse = self.text_detector(img)
print("Predict time : ", elapse)
result['data'] = dt_boxes.astype(np.int).tolist()
@@ -146,7 +124,7 @@ class OCRDet(hub.Module):
Run as a service.
"""
images_decode = [base64_to_cv2(image) for image in images]
- results = self.det_text(images_decode, **kwargs)
+ results = self.predict(images_decode, **kwargs)
return results
@@ -156,5 +134,5 @@ if __name__ == '__main__':
'./doc/imgs/11.jpg',
'./doc/imgs/12.jpg',
]
- res = ocr.det_text(paths=image_path, visualization=True)
+ res = ocr.predict(paths=image_path, visualization=True)
print(res)
\ No newline at end of file
diff --git a/deploy/hubserving/ocr_det/params.py b/deploy/hubserving/ocr_det/params.py
new file mode 100644
index 0000000000000000000000000000000000000000..0b950114f82d88f20d2ce521628ea9dda7740ab4
--- /dev/null
+++ b/deploy/hubserving/ocr_det/params.py
@@ -0,0 +1,39 @@
+# -*- coding:utf-8 -*-
+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/ch_det_mv3_db/"
+ cfg.det_max_side_len = 960
+
+ #DB parmas
+ cfg.det_db_thresh =0.3
+ cfg.det_db_box_thresh =0.5
+ cfg.det_db_unclip_ratio =2.0
+
+ # #EAST parmas
+ # 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_det_mv3_crnn/"
+
+ # cfg.rec_image_shape = "3, 32, 320"
+ # cfg.rec_char_type = 'ch'
+ # cfg.rec_batch_num = 30
+ # cfg.rec_char_dict_path = "./ppocr/utils/ppocr_keys_v1.txt"
+ # cfg.use_space_char = True
+
+ return cfg
\ No newline at end of file
diff --git a/deploy/ocr_hubserving/ocr_rec/__init__.py b/deploy/hubserving/ocr_rec/__init__.py
similarity index 100%
rename from deploy/ocr_hubserving/ocr_rec/__init__.py
rename to deploy/hubserving/ocr_rec/__init__.py
diff --git a/deploy/ocr_hubserving/ocr_rec/config.json b/deploy/hubserving/ocr_rec/config.json
similarity index 74%
rename from deploy/ocr_hubserving/ocr_rec/config.json
rename to deploy/hubserving/ocr_rec/config.json
index 2cfbc0b558d49d54c341506f0e8789578e1b42cd..59d54e6c7545f300f134c9c2efaf546308b9c360 100644
--- a/deploy/ocr_hubserving/ocr_rec/config.json
+++ b/deploy/hubserving/ocr_rec/config.json
@@ -3,11 +3,13 @@
"ocr_rec": {
"init_args": {
"version": "1.0.0",
- "det_model_dir": "./inference/ch_rec_mv3_crnn/",
"use_gpu": true
},
"predict_args": {
}
}
- }
+ },
+ "port": 8867,
+ "use_multiprocess": false,
+ "workers": 2
}
diff --git a/deploy/ocr_hubserving/ocr_rec/module.py b/deploy/hubserving/ocr_rec/module.py
similarity index 74%
rename from deploy/ocr_hubserving/ocr_rec/module.py
rename to deploy/hubserving/ocr_rec/module.py
index b50016a37fc44291b5aa01bdf2b55bdab11c8fe5..77a907d6d29912dc0293c2f313215b40b7469ff3 100644
--- a/deploy/ocr_hubserving/ocr_rec/module.py
+++ b/deploy/hubserving/ocr_rec/module.py
@@ -22,8 +22,6 @@ import paddlehub as hub
from tools.infer.utility import base64_to_cv2
from tools.infer.predict_rec import TextRecognizer
-class Config(object):
- pass
@moduleinfo(
name="ocr_rec",
@@ -33,41 +31,28 @@ class Config(object):
author_email="paddle-dev@baidu.com",
type="cv/text_recognition")
class OCRRec(hub.Module):
- def _initialize(self,
- rec_model_dir="",
- rec_algorithm="CRNN",
- rec_char_dict_path="./ppocr/utils/ppocr_keys_v1.txt",
- rec_batch_num=30,
- use_gpu=False
- ):
+ def _initialize(self, use_gpu=False):
"""
initialize with the necessary elements
"""
- self.config = Config()
- self.config.use_gpu = use_gpu
+ from ocr_rec.params import read_params
+ cfg = read_params()
+
+ 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."
)
- self.config.ir_optim = True
- self.config.gpu_mem = 8000
+ cfg.ir_optim = True
- #params for text recognizer
- self.config.rec_algorithm = rec_algorithm
- self.config.rec_model_dir = rec_model_dir
- # self.config.rec_model_dir = "./inference/rec/"
-
- self.config.rec_image_shape = "3, 32, 320"
- self.config.rec_char_type = 'ch'
- self.config.rec_batch_num = rec_batch_num
- self.config.rec_char_dict_path = rec_char_dict_path
- self.config.use_space_char = True
+ self.text_recognizer = TextRecognizer(cfg)
def read_images(self, paths=[]):
images = []
@@ -81,7 +66,7 @@ class OCRRec(hub.Module):
images.append(img)
return images
- def rec_text(self,
+ def predict(self,
images=[],
paths=[]):
"""
@@ -102,14 +87,13 @@ class OCRRec(hub.Module):
assert predicted_data != [], "There is not any image to be predicted. Please check the input data."
- text_recognizer = TextRecognizer(self.config)
img_list = []
for img in predicted_data:
if img is None:
continue
img_list.append(img)
try:
- rec_res, predict_time = text_recognizer(img_list)
+ rec_res, predict_time = self.text_recognizer(img_list)
except Exception as e:
print(e)
return []
@@ -121,7 +105,7 @@ class OCRRec(hub.Module):
Run as a service.
"""
images_decode = [base64_to_cv2(image) for image in images]
- results = self.det_text(images_decode, **kwargs)
+ results = self.predict(images_decode, **kwargs)
return results
@@ -132,5 +116,5 @@ if __name__ == '__main__':
'./doc/imgs_words/ch/word_2.jpg',
'./doc/imgs_words/ch/word_3.jpg',
]
- res = ocr.rec_text(paths=image_path)
+ res = ocr.predict(paths=image_path)
print(res)
\ No newline at end of file
diff --git a/deploy/hubserving/ocr_rec/params.py b/deploy/hubserving/ocr_rec/params.py
new file mode 100644
index 0000000000000000000000000000000000000000..fe93fc0870a1bb1d050285ca858de4cddb6b3a61
--- /dev/null
+++ b/deploy/hubserving/ocr_rec/params.py
@@ -0,0 +1,39 @@
+# -*- coding:utf-8 -*-
+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/ch_det_mv3_db/"
+ # cfg.det_max_side_len = 960
+
+ # #DB parmas
+ # cfg.det_db_thresh =0.3
+ # cfg.det_db_box_thresh =0.5
+ # cfg.det_db_unclip_ratio =2.0
+
+ # #EAST parmas
+ # 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_rec_mv3_crnn/"
+
+ cfg.rec_image_shape = "3, 32, 320"
+ cfg.rec_char_type = 'ch'
+ cfg.rec_batch_num = 30
+ cfg.rec_char_dict_path = "./ppocr/utils/ppocr_keys_v1.txt"
+ cfg.use_space_char = True
+
+ return cfg
\ No newline at end of file
diff --git a/deploy/ocr_hubserving/ocr_system/__init__.py b/deploy/hubserving/ocr_system/__init__.py
similarity index 100%
rename from deploy/ocr_hubserving/ocr_system/__init__.py
rename to deploy/hubserving/ocr_system/__init__.py
diff --git a/deploy/ocr_hubserving/ocr_system/config.json b/deploy/hubserving/ocr_system/config.json
similarity index 65%
rename from deploy/ocr_hubserving/ocr_system/config.json
rename to deploy/hubserving/ocr_system/config.json
index 364c7426a44a6b67576508c89cd993368624726f..21c701c60ec93828497892160bcf52f4dc558f04 100644
--- a/deploy/ocr_hubserving/ocr_system/config.json
+++ b/deploy/hubserving/ocr_system/config.json
@@ -3,14 +3,15 @@
"ocr_system": {
"init_args": {
"version": "1.0.0",
- "det_model_dir": "./inference/ch_det_mv3_db/",
- "rec_model_dir": "./inference/ch_rec_mv3_crnn/",
"use_gpu": true
},
"predict_args": {
"visualization": false
}
}
- }
+ },
+ "port": 8868,
+ "use_multiprocess": false,
+ "workers": 2
}
diff --git a/deploy/ocr_hubserving/ocr_system/module.py b/deploy/hubserving/ocr_system/module.py
similarity index 72%
rename from deploy/ocr_hubserving/ocr_system/module.py
rename to deploy/hubserving/ocr_system/module.py
index dc5ab211b937c114cb87e9bcc058af583f606d6b..a70697f46fa64bf2922a3308986e4417a9b9037c 100644
--- a/deploy/ocr_hubserving/ocr_system/module.py
+++ b/deploy/hubserving/ocr_system/module.py
@@ -23,9 +23,6 @@ from tools.infer.utility import draw_ocr, base64_to_cv2
from tools.infer.predict_system import TextSystem
-class Config(object):
- pass
-
@moduleinfo(
name="ocr_system",
version="1.0.0",
@@ -34,58 +31,28 @@ class Config(object):
author_email="paddle-dev@baidu.com",
type="cv/text_recognition")
class OCRSystem(hub.Module):
- def _initialize(self,
- det_model_dir="",
- det_algorithm="DB",
- rec_model_dir="",
- rec_algorithm="CRNN",
- rec_char_dict_path="./ppocr/utils/ppocr_keys_v1.txt",
- rec_batch_num=30,
- use_gpu=False
- ):
+ def _initialize(self, use_gpu=False):
"""
initialize with the necessary elements
"""
- self.config = Config()
- self.config.use_gpu = use_gpu
+ from ocr_system.params import read_params
+ cfg = read_params()
+
+ 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."
)
- self.config.ir_optim = True
- self.config.gpu_mem = 8000
-
- #params for text detector
- self.config.det_algorithm = det_algorithm
- self.config.det_model_dir = det_model_dir
- # self.config.det_model_dir = "./inference/det/"
-
- #DB parmas
- self.config.det_db_thresh =0.3
- self.config.det_db_box_thresh =0.5
- self.config.det_db_unclip_ratio =2.0
-
- #EAST parmas
- self.config.det_east_score_thresh = 0.8
- self.config.det_east_cover_thresh = 0.1
- self.config.det_east_nms_thresh = 0.2
-
- #params for text recognizer
- self.config.rec_algorithm = rec_algorithm
- self.config.rec_model_dir = rec_model_dir
- # self.config.rec_model_dir = "./inference/rec/"
-
- self.config.rec_image_shape = "3, 32, 320"
- self.config.rec_char_type = 'ch'
- self.config.rec_batch_num = rec_batch_num
- self.config.rec_char_dict_path = rec_char_dict_path
- self.config.use_space_char = True
+ cfg.ir_optim = True
+
+ self.text_sys = TextSystem(cfg)
def read_images(self, paths=[]):
images = []
@@ -99,10 +66,9 @@ class OCRSystem(hub.Module):
images.append(img)
return images
- def recognize_text(self,
+ def predict(self,
images=[],
paths=[],
- det_max_side_len=960,
draw_img_save='ocr_result',
visualization=False,
text_thresh=0.5):
@@ -111,11 +77,8 @@ class OCRSystem(hub.Module):
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
- use_gpu (bool): Whether to use gpu.
- batch_size(int): the program deals once with one
- output_dir (str): The directory to store output images.
+ draw_img_save (str): The directory to store output images.
visualization (bool): Whether to save image or not.
- box_thresh(float): the threshold of the detected text box's confidence
text_thresh(float): the threshold of the recognize chinese texts' confidence
Returns:
res (list): The result of chinese texts and save path of images.
@@ -130,8 +93,6 @@ class OCRSystem(hub.Module):
assert predicted_data != [], "There is not any image to be predicted. Please check the input data."
- self.config.det_max_side_len = det_max_side_len
- text_sys = TextSystem(self.config)
cnt = 0
all_results = []
for img in predicted_data:
@@ -142,7 +103,7 @@ class OCRSystem(hub.Module):
all_results.append(result)
continue
starttime = time.time()
- dt_boxes, rec_res = text_sys(img)
+ dt_boxes, rec_res = self.text_sys(img)
elapse = time.time() - starttime
cnt += 1
print("Predict time of image %d: %.3fs" % (cnt, elapse))
@@ -187,7 +148,7 @@ class OCRSystem(hub.Module):
Run as a service.
"""
images_decode = [base64_to_cv2(image) for image in images]
- results = self.recognize_text(images_decode, **kwargs)
+ results = self.predict(images_decode, **kwargs)
return results
@@ -197,5 +158,5 @@ if __name__ == '__main__':
'./doc/imgs/11.jpg',
'./doc/imgs/12.jpg',
]
- res = ocr.recognize_text(paths=image_path, visualization=True)
+ res = ocr.predict(paths=image_path, visualization=False)
print(res)
\ No newline at end of file
diff --git a/deploy/hubserving/ocr_system/params.py b/deploy/hubserving/ocr_system/params.py
new file mode 100644
index 0000000000000000000000000000000000000000..5b3bb1ea44b6cd262283797807c2c77646202fe8
--- /dev/null
+++ b/deploy/hubserving/ocr_system/params.py
@@ -0,0 +1,39 @@
+# -*- coding:utf-8 -*-
+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/ch_det_mv3_db/"
+ cfg.det_max_side_len = 960
+
+ #DB parmas
+ cfg.det_db_thresh =0.3
+ cfg.det_db_box_thresh =0.5
+ cfg.det_db_unclip_ratio =2.0
+
+ #EAST parmas
+ 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_rec_mv3_crnn/"
+
+ cfg.rec_image_shape = "3, 32, 320"
+ cfg.rec_char_type = 'ch'
+ cfg.rec_batch_num = 30
+ cfg.rec_char_dict_path = "./ppocr/utils/ppocr_keys_v1.txt"
+ cfg.use_space_char = True
+
+ return cfg
\ No newline at end of file
diff --git a/doc/doc_ch/serving.md b/doc/doc_ch/serving.md
index da043921388ad59a5b6b9e60ebd6f1200454ff25..69860e6783041ff37a89e951af8db3fcc61c43cb 100644
--- a/doc/doc_ch/serving.md
+++ b/doc/doc_ch/serving.md
@@ -1,7 +1,7 @@
# 服务部署
PaddleOCR提供2种服务部署方式：
-- 基于HubServing的部署：已集成到PaddleOCR中（[code](https://github.com/PaddlePaddle/PaddleOCR/tree/develop/deploy/ocr_hubserving)），按照本教程使用；
+- 基于HubServing的部署：已集成到PaddleOCR中（[code](https://github.com/PaddlePaddle/PaddleOCR/tree/develop/deploy/hubserving)），按照本教程使用；
- 基于PaddleServing的部署：详见PaddleServing官网[demo](https://github.com/PaddlePaddle/Serving/tree/develop/python/examples/ocr)，后续也将集成到PaddleOCR。
服务部署目录下包括检测、识别、2阶段串联三种服务包，根据需求选择相应的服务包进行安装和启动。目录如下：
@@ -15,12 +15,13 @@ deploy/hubserving/
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
- └─ config.json 配置文件，启动服务时作为参数传入
- └─ module.py 主模块，包含服务的完整逻辑
+ └─ __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
```
-## 启动服务
+## 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。
### 1. 安装paddlehub
```pip3 install paddlehub --upgrade -i https://pypi.tuna.tsinghua.edu.cn/simple```
@@ -31,39 +32,71 @@ PaddleOCR提供3种服务模块，根据需要安装所需模块。如：
安装检测服务模块：
```hub install deploy/hubserving/ocr_det/```
-或，安装识别服务模块：
+或，安装识别服务模块：
```hub install deploy/hubserving/ocr_rec/```
或，安装检测+识别串联服务模块：
```hub install deploy/hubserving/ocr_system/```
-### 3. 修改配置文件
-在config.json中指定模型路径、是否使用GPU、是否对结果做可视化等参数，如，串联服务ocr_system的配置：
+### 3. 启动服务
+#### 方式1. 命令行命令启动（仅支持CPU）
+**启动命令：**
+```shell
+$ hub serving start --modules [Module1==Version1, Module2==Version2, ...] \
+ --port XXXX \
+ --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
*`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
*`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： ```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。
+
+#### 方式2. 配置文件启动（支持CPU、GPU）
+**启动命令：**
+```hub serving start --config/-c config.json```
+
+其中，`config.json`格式如下：
```python
{
"modules_info": {
"ocr_system": {
"init_args": {
"version": "1.0.0",
- "det_model_dir": "./inference/det/",
- "rec_model_dir": "./inference/rec/",
"use_gpu": true
},
"predict_args": {
"visualization": false
}
}
- }
+ },
+ "port": 8868,
+ "use_multiprocess": false,
+ "workers": 2
}
```
-其中，模型路径对应的模型为```inference模型```。
-### 4. 运行启动命令
-```hub serving start -m ocr_system --config hubserving/ocr_det/config.json```
+- `init_args`中的可配参数与`module.py`中的`_initialize`函数接口一致。其中，**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。
-这样就完成了一个服务化API的部署，默认端口号为8866。
+**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：```export CUDA_VISIBLE_DEVICES=0```，否则不用设置。
-**NOTE:** 如使用GPU预测(即，config中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：```export CUDA_VISIBLE_DEVICES=0```，否则不用设置。
+如，使用GPU 3号卡启动串联服务：
+```shell
+export CUDA_VISIBLE_DEVICES=3
+hub serving start -c deploy/hubserving/ocr_system/config.json
+```
## 发送预测请求
配置好服务端，以下数行代码即可实现发送预测请求，获取预测结果:
@@ -89,21 +122,25 @@ r = requests.post(url=url, headers=headers, data=json.dumps(data))
print(r.json()["results"])
```
-你可能需要根据实际情况修改```url```字符串中的端口号和服务模块名称。
+你可能需要根据实际情况修改`url`字符串中的端口号和服务模块名称。
上面所示代码都已写入测试脚本，可直接运行命令：```python tools/test_hubserving.py```
## 自定义修改服务模块
-如果需要修改服务逻辑，你一般需要操作以下步骤：
+如果需要修改服务逻辑，你一般需要操作以下步骤（以修改`ocr_system`为例）：
-1、 停止服务
-```hub serving stop -m ocr_system```
+- 1、 停止服务
+```hub serving stop --port/-p XXXX```
-2、 到相应的module.py文件中根据实际需求修改代码
+- 2、 到相应的`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`，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。 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。
-3、 卸载旧服务包
+- 3、 卸载旧服务包
```hub uninstall ocr_system```
-4、 安装修改后的新服务包
+- 4、 安装修改后的新服务包
```hub install deploy/hubserving/ocr_system/```
+- 5、重新启动服务
+```hub serving start -m ocr_system```
+