feat(rapidocr_api): update version to v0.1.0

api/README.md

@@ -1,10 +1,9 @@
 ### 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。 
+* 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。
@@ -13,7 +12,7 @@
 
 Windows下启动：
 
-```for win shell
+```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=
 
@@ -22,6 +21,7 @@ rapidocr_api
 ```
 
 Linux下启动：
+
 ```shell
 # 默认参数启动
 rapidocr_api
@@ -30,25 +30,27 @@ rapidocr_api
 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 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：
-```
+
+```bash
 cd api
 python demo.py
 ```
 
 构建镜像:
-```
+
+```bash
 cd api
 sudo docker build -t="rapidocr_api:0.1.1" .
 ```
+
 启动镜像：
 
-```
+```bash
 docker run -p 9003:9003 --name rapidocr_api1 --restart always -d rapidocr_api:0.1.1
-```
+```

api/demo.py

@@ -13,8 +13,9 @@
 
 # print(response.text)
 
-import time
 import base64
+import time
+
 import requests
 
 url = "http://localhost:9003/ocr"
@@ -26,36 +27,36 @@
     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(f"用时:{etime:.3f}秒")
 
-print('-'*40)
+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
+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)
+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')}
+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
+    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)
+print(f"用时:{etime:.3f}秒")
+print("-" * 40)

api/rapidocr_api/main.py

@@ -26,11 +26,19 @@ def __init__(self) -> 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)
+        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, use_det=None, use_cls=None, use_rec=None) -> Dict:
+    def __call__(
+        self, img: Image.Image, use_det=None, use_cls=None, use_rec=None, **kwargs
+    ) -> Dict:
         img = np.array(img)
-        ocr_res, _ = self.ocr(img, use_det=use_det, use_cls=use_cls, use_rec=use_rec)
+        ocr_res, _ = self.ocr(
+            img, use_det=use_det, use_cls=use_cls, use_rec=use_rec, **kwargs
+        )
 
         if not ocr_res:
             return {}
@@ -40,11 +48,13 @@ def __call__(self, img: Image.Image, use_det=None, use_cls=None, use_rec=None) -
         for i, dats in enumerate(ocr_res):
             values = {}
             for dat in dats:
-                if type(dat) == str:
+                if isinstance(dat, str):
                     values["rec_txt"] = dat
-                if type(dat) == np.float64:
+
+                if isinstance(dat, np.float64):
                     values["score"] = f"{dat:.4f}"
-                if type(dat) == list:
+
+                if isinstance(dat, list):
                     values["dt_boxes"] = dat
             out_dict[str(i)] = values
 
@@ -54,14 +64,20 @@ def __call__(self, img: Image.Image, use_det=None, use_cls=None, use_rec=None) -
 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),
-        use_det: bool = Form(None), use_cls: bool = Form(None), use_rec: bool = Form(None)):
 
+@app.post("/ocr")
+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:
@@ -75,14 +91,24 @@ async def ocr(image_file: UploadFile = None, image_data: str = Form(None),
     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')
+    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=0, workers=args.workers)
+    uvicorn.run(
+        "rapidocr_api.main:app",
+        host=args.ip,
+        port=args.port,
+        reload=0,
+        workers=args.workers,
+    )
+
 
 if __name__ == "__main__":
     main()