chore: update files

python/demo.py

@@ -18,7 +18,7 @@
 # engine = engine = RapidOCR(
 #     params={"Global.with_onnx": True, "EngineConfig.onnxruntime.use_cuda": True}
 # )
-engine = RapidOCR(params={"Global.lang": "en"})
+engine = RapidOCR(params={"Global.lang": "latin", "Global.with_openvino": True})
 vis = VisRes()
 
 image_path = "tests/test_files/ch_en_num.jpg"

python/rapidocr/config.yaml

@@ -38,8 +38,8 @@ EngineConfig:
         use_cuda: false
 
 Det:
-    model_path: models/ch_PP-OCRv4_det_infer.onnx
-    model_dir: models/ch_PP-OCRv4_det_infer
+    model_path: null
+    model_dir: null
 
     limit_side_len: 736
     limit_type: min
@@ -54,18 +54,18 @@ Det:
     score_mode: fast
 
 Cls:
-    model_path: models/ch_ppocr_mobile_v2.0_cls_infer.onnx
-    model_dir: models/ch_ppocr_mobile_v2_cls_infer
+    model_path: null
+    model_dir: null
 
     cls_image_shape: [3, 48, 192]
     cls_batch_num: 6
     cls_thresh: 0.9
     label_list: ['0', '180']
 
 Rec:
-    model_path: models/ch_PP-OCRv4_rec_infer.onnx
-    model_dir: models/ch_PP-OCRv4_rec_infer
+    model_path: null
+    model_dir: null
 
-    rec_keys_path: models/ppocr_keys_v1.txt
+    rec_keys_path: null
     rec_img_shape: [3, 48, 320]
     rec_batch_num: 6

python/rapidocr/inference_engine/base.py

@@ -13,8 +13,8 @@
 
 from ..utils.logger import Logger
 
-cur_dir = Path(__file__).resolve().parent
-MODEL_URL_PATH = cur_dir / "MODEL_URL.yaml"
+cur_dir = Path(__file__).resolve().parent.parent
+MODEL_URL_PATH = cur_dir / "default_models.yaml"
 
 
 logger = Logger(logger_name=__name__).get_log()
@@ -76,7 +76,7 @@ def get_engine_name(config: DictConfig) -> str:
 
 class InferSession(abc.ABC):
     model_info = OmegaConf.load(MODEL_URL_PATH)
-    DEFAULT_MODE_PATH = cur_dir.parent / "models"
+    DEFAULT_MODE_PATH = cur_dir / "models"
     logger = Logger(logger_name=__name__).get_log()
 
     @abc.abstractmethod
@@ -88,26 +88,29 @@ def __call__(self, input_content: np.ndarray) -> np.ndarray:
         pass
 
     @staticmethod
-    def _verify_model(model_path: Union[str, Path, None]) -> bool:
+    def _verify_model(model_path: Union[str, Path, None]):
         if model_path is None:
-            return False
+            raise ValueError("model_path is None!")
 
         model_path = Path(model_path)
         if not model_path.exists():
-            return False
+            raise FileNotFoundError(f"{model_path} does not exists.")
 
         if not model_path.is_file():
-            return False
-
-        return True
+            raise FileExistsError(f"{model_path} is not a file.")
 
     @abc.abstractmethod
     def have_key(self, key: str = "character") -> bool:
         pass
 
     @classmethod
     def download_file(cls, url: str, save_path: Union[str, Path]):
+        if Path(save_path).exists():
+            cls.logger.info("Model already exists in %s", save_path)
+            return
+
         cls.logger.info("Downloading model from %s to %s", url, save_path)
+
         response = requests.get(url, stream=True, timeout=60)
         status_code = response.status_code
 

python/rapidocr/inference_engine/onnxruntime.py

@@ -32,16 +32,16 @@ def __init__(self, config: Dict[str, Any]):
         self.logger = Logger(logger_name=__name__).get_log()
 
         model_path = config.get("model_path", None)
-        if not self._verify_model(model_path):
-            self.logger.warning(
-                "Model path is invalid, try to download the default model."
-            )
+        if model_path is None:
+            # 说明用户没有指定自己模型，使用默认模型
             default_model_url = self.get_model_url(
                 config.engine_name, config.task_type, config.lang
             )
             model_path = self.DEFAULT_MODE_PATH / Path(default_model_url).name
             self.download_file(default_model_url, model_path)
 
+        self._verify_model(model_path)
+
         self.cfg_use_cuda = config.engine_cfg.get("use_cuda", None)
         self.cfg_use_dml = config.engine_cfg.get("use_dml", None)
 

python/rapidocr/inference_engine/openvino.py

@@ -3,6 +3,7 @@
 # @Contact: liekkaskono@163.com
 import os
 import traceback
+from pathlib import Path
 
 import numpy as np
 from omegaconf import DictConfig
@@ -17,8 +18,17 @@ def __init__(self, config: DictConfig):
 
         core = Core()
 
-        self._verify_model(config["model_path"])
-        model_onnx = core.read_model(config["model_path"])
+        model_path = config.get("model_path", None)
+        if model_path is None:
+            # 说明用户没有指定自己模型，使用默认模型
+            default_model_url = self.get_model_url(
+                config.engine_name, config.task_type, config.lang
+            )
+            model_path = self.DEFAULT_MODE_PATH / Path(default_model_url).name
+            self.download_file(default_model_url, model_path)
+
+        self._verify_model(model_path)
+        model_onnx = core.read_model(model_path)
 
         cpu_nums = os.cpu_count()
         infer_num_threads = config.get("inference_num_threads", -1)

python/rapidocr/main.py

@@ -38,8 +38,8 @@ def __init__(
             config = ParseParams.load(config_path)
         else:
             config = ParseParams.load(DEFAULT_CFG_PATH)
-            config = ParseParams.update_model_path(config)
-            config = ParseParams.update_dict_path(config)
+            # config = ParseParams.update_model_path(config)
+            # config = ParseParams.update_dict_path(config)
 
         if params:
             config = ParseParams.update_batch(config, params)