update rapidocr_api (#242)

Co-authored-by: 何熙 <[email protected]>

api/Dockerfile

@@ -0,0 +1,18 @@
+FROM python:3.10.11-slim-buster
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+# 设置工作目录
+WORKDIR /app
+
+RUN pip install --no-cache-dir rapidocr_api -i https://mirrors.aliyun.com/pypi/simple 
+
+RUN pip uninstall -y opencv-python && \
+    pip install --no-cache-dir opencv-python-headless -i https://mirrors.aliyun.com/pypi/simple
+
+EXPOSE 9003
+
+# 升级后可用
+# CMD ["bash", "-c", "rapidocr_api -ip 0.0.0.0 -p 9003 -workers 2"]
+CMD ["rapidocr_api"]
+

api/README.md

@@ -1 +1,54 @@
 ### See [Documentation](https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_api/usage/)
+
+
+### API 修改说明
+
+* uvicorn启动时，reload参数设置为False，避免反复加载；
+* 增加了启动参数： workers，可启动多个实例，以满足多并发需求。 
+* 可通过环境变量传递模型参数：det_model_path, cls_model_path, rec_model_path；
+* 接口中可传入参数，控制是否使用检测、方向分类和识别这三部分的模型；客户端调用见`demo.py`
+* 增加了Dockerfile，可自行构建镜像。
+
+启动服务端：
+
+Windows下启动：
+
+```for win shell
+set det_model_path=I:\models\图像相关\OCR\RapidOCR\PP-OCRv4\ch_PP-OCRv4_det_server_infer.onnx
+set det_model_path=
+
+set rec_model_path=I:\models\图像相关\OCR\RapidOCR\PP-OCRv4\ch_PP-OCRv4_rec_server_infer.onnx
+rapidocr_api
+```
+
+Linux下启动：
+```shell
+# 默认参数启动
+rapidocr_api
+
+# 指定参数：端口与进程数量；
+rapidocr_api -ip 0.0.0.0 -p 9005 -workers 2
+
+# 指定模型
+expert det_model_path=/mnt/sda1/models/PP-OCRv4/ch_PP-OCRv4_det_server_infer.onnx 
+expert rec_model_path=/mnt/sda1/models/PP-OCRv4/ch_PP-OCRv4_rec_server_infer.onnx
+rapidocr_api -ip 0.0.0.0 -p 9005 -workers 2
+```
+
+
+客户端调用说明：
+```
+cd api
+python demo.py
+```
+
+构建镜像:
+```
+cd api
+sudo docker build -t="rapidocr_api:0.1.1" .
+```
+启动镜像：
+
+```
+docker run -p 9003:9003 --name rapidocr_api1 --restart always -d rapidocr_api:0.1.1
+```

api/demo.py

@@ -13,17 +13,49 @@
 
 # print(response.text)
 
+import time
 import base64
-
 import requests
 
 url = "http://localhost:9003/ocr"
 img_path = "../python/tests/test_files/ch_en_num.jpg"
 
+# 方式一：使用base64编码传
+stime = time.time()
 with open(img_path, "rb") as fa:
     img_str = base64.b64encode(fa.read())
 
 payload = {"image_data": img_str}
-response = requests.post(url, data=payload, timeout=60)
+response = requests.post(url, data=payload) #, timeout=60
 
 print(response.json())
+etime = time.time() - stime
+print(f'用时:{etime:.3f}秒')
+
+print('-'*40)
+
+# 方式二：使用文件上传方式
+stime = time.time()
+with open(img_path, 'rb') as f:
+    file_dict = {'image_file': (img_path, f, 'image/png')}
+    response = requests.post(url, files=file_dict) #, timeout=60
+    print(response.json())
+
+etime = time.time() - stime
+print(f'用时:{etime:.3f}秒')
+print('-'*40)
+
+# 方式三：控制是否使用检测、方向分类和识别这三部分的模型； 不使用检测模型:use_det=False
+stime = time.time()
+img_path = "../python/tests/test_files/test_without_det.jpg"
+
+with open(img_path, 'rb') as f:
+    file_dict = {'image_file': (img_path, f, 'image/png')}
+    # 添加控制参数
+    data = {"use_det":False, "use_cls":True, "use_rec":True}
+    response = requests.post(url, files=file_dict, data=data) #, timeout=60
+    print(response.json())
+
+etime = time.time() - stime
+print(f'用时:{etime:.3f}秒')
+print('-'*40)

api/rapidocr_api/main.py

@@ -1,9 +1,11 @@
 # -*- encoding: utf-8 -*-
 # @Author: SWHL
 # @Contact: [email protected]
+
 import argparse
 import base64
 import io
+import os
 import sys
 from pathlib import Path
 from typing import Dict
@@ -19,37 +21,47 @@
 
 class OCRAPIUtils:
     def __init__(self) -> None:
-        self.ocr = RapidOCR()
+        # 从环境变量中读取参数
+        det_model_path = os.getenv("det_model_path", None)
+        cls_model_path = os.getenv("cls_model_path", None)
+        rec_model_path = os.getenv("rec_model_path", None)
+
+        self.ocr = RapidOCR(det_model_path=det_model_path, cls_model_path=cls_model_path, rec_model_path=rec_model_path)
 
-    def __call__(self, img: Image.Image) -> Dict:
+    def __call__(self, img: Image.Image, use_det=None, use_cls=None, use_rec=None) -> Dict:
         img = np.array(img)
-        ocr_res, _ = self.ocr(img)
+        ocr_res, _ = self.ocr(img, use_det=use_det, use_cls=use_cls, use_rec=use_rec)
 
         if not ocr_res:
             return {}
 
-        out_dict = {
-            str(i): {
-                "rec_txt": rec,
-                "dt_boxes": dt_box,
-                "score": f"{score:.4f}",
-            }
-            for i, (dt_box, rec, score) in enumerate(ocr_res)
-        }
+        # 转换为字典格式: 兼容所有参数情况
+        out_dict = {}
+        for i, dats in enumerate(ocr_res):
+            values = {}
+            for dat in dats:
+                if type(dat) == str:
+                    values["rec_txt"] = dat
+                if type(dat) == np.float64:
+                    values["score"] = f"{dat:.4f}"
+                if type(dat) == list:
+                    values["dt_boxes"] = dat
+            out_dict[str(i)] = values
+
         return out_dict
 
 
 app = FastAPI()
 processor = OCRAPIUtils()
 
-
 @app.get("/")
 async def root():
     return {"message": "Welcome to RapidOCR API Server!"}
 
-
 @app.post("/ocr")
-async def ocr(image_file: UploadFile = None, image_data: str = Form(None)):
+async def ocr(image_file: UploadFile = None, image_data: str = Form(None),
+        use_det: bool = Form(None), use_cls: bool = Form(None), use_rec: bool = Form(None)):
+
     if image_file:
         img = Image.open(image_file.file)
     elif image_data:
@@ -60,19 +72,17 @@ async def ocr(image_file: UploadFile = None, image_data: str = Form(None)):
         raise ValueError(
             "When sending a post request, data or files must have a value."
         )
-
-    ocr_res = processor(img)
+    ocr_res = processor(img, use_det=use_det, use_cls=use_cls, use_rec=use_rec)
     return ocr_res
 
-
 def main():
     parser = argparse.ArgumentParser("rapidocr_api")
     parser.add_argument("-ip", "--ip", type=str, default="0.0.0.0", help="IP Address")
     parser.add_argument("-p", "--port", type=int, default=9003, help="IP port")
+    parser.add_argument('-workers', "--workers", type=int, default=1, help='number of worker process')
     args = parser.parse_args()
 
-    uvicorn.run("rapidocr_api.main:app", host=args.ip, port=args.port, reload=True)
-
+    uvicorn.run("rapidocr_api.main:app", host=args.ip, port=args.port, reload=0, workers=args.workers)
 
 if __name__ == "__main__":
     main()