chore: update files

python/demo.py

@@ -3,9 +3,10 @@
 # @Contact: [email protected]
 import cv2
 
-from rapidocr import RapidOCR, VisRes
-
 # from rapidocr_onnxruntime import RapidOCR, VisRes
+from rapidocr_torch import RapidOCR, VisRes
+
+# from rapidocr import RapidOCR, VisRes
 
 
 # from rapidocr_paddle import RapidOCR, VisRes
@@ -14,7 +15,7 @@
 # yaml_path = "tests/test_files/config.yaml"
 # engine = RapidOCR(config_path=yaml_path)
 
-engine = RapidOCR(params={"Cls.model_path": "1.onnx"})
+engine = RapidOCR(params={"Global.with_paddle": True})
 vis = VisRes()
 
 image_path = "tests/test_files/ch_en_num.jpg"

python/rapidocr/config.yaml

@@ -29,9 +29,14 @@ EngineConfig:
         gpu_id: 0
         gpu_mem: 500
 
+    openvino:
+        inference_num_threads: -1
+
+    torch:
+        use_cuda: false
+
 Det:
     model_path: models/ch_PP-OCRv4_det_infer.onnx
-    paddle_model_dir: models/paddle/ch_PP-OCRv4_det_infer
 
     limit_side_len: 736
     limit_type: min
@@ -47,7 +52,6 @@ Det:
 
 Cls:
     model_path: models/ch_ppocr_mobile_v2.0_cls_infer.onnx
-    paddle_model_dir: models/paddle/ch_ppocr_mobile_v2_cls_infer
 
     cls_image_shape: [3, 48, 192]
     cls_batch_num: 6
@@ -56,7 +60,6 @@ Cls:
 
 Rec:
     model_path: models/ch_PP-OCRv4_rec_infer.onnx
-    paddle_model_dir: models/paddle/ch_PP-OCRv4_rec_infer
 
     rec_img_shape: [3, 48, 320]
     rec_batch_num: 6

python/rapidocr/inference_engine/openvino.py

@@ -5,13 +5,14 @@
 import traceback
 
 import numpy as np
+from omegaconf import DictConfig
 from openvino.runtime import Core
 
 from .base import InferSession
 
 
 class OpenVINOInferSession(InferSession):
-    def __init__(self, config):
+    def __init__(self, config: DictConfig):
         core = Core()
 
         self._verify_model(config["model_path"])

python/rapidocr/inference_engine/paddlepaddle.py

@@ -18,7 +18,7 @@ def __init__(self, config, mode: Optional[str] = None) -> None:
         self.logger = get_logger("PaddleInferSession")
         self.mode = mode
 
-        model_dir = Path(config.padde_model_dir)
+        model_dir = Path(config.model_path)
         pdmodel_path = model_dir / "inference.pdmodel"
         pdiparams_path = model_dir / "inference.pdiparams"
 

python/rapidocr/inference_engine/torch.py

@@ -25,15 +25,17 @@ def read_yaml(yaml_path: Union[str, Path]) -> Dict[str, Dict]:
 
 class TorchInferSession:
     def __init__(self, config, mode: Optional[str] = None) -> None:
+        self.logger = get_logger("TorchInferSession")
+
         all_arch_config = read_yaml(DEFAULT_CFG_PATH)
 
-        self.logger = get_logger("TorchInferSession")
         self.mode = mode
         model_path = Path(config["model_path"])
         self._verify_model(model_path)
         file_name = model_path.stem
         if file_name not in all_arch_config:
             raise ValueError(f"architecture {file_name} is not in config.yaml")
+
         arch_config = all_arch_config[file_name]
         self.predictor = BaseModel(arch_config)
         self.predictor.load_state_dict(torch.load(model_path, weights_only=True))

python/rapidocr/main.py

@@ -46,7 +46,6 @@ def __init__(
 
         engine_name = get_engine_name(config)
 
-        # 根据选定的语言加载对应的模型
         det_lang, rec_lang = parse_lang(config.Global.lang)
 
         self.print_verbose = config.Global.print_verbose

python/rapidocr/utils/__init__.py

@@ -6,4 +6,5 @@
 from .parse_parameters import ParseParams, init_args, parse_lang
 from .process_img import add_round_letterbox, increase_min_side, reduce_max_side
 from .typings import RapidOCROutput
+from .utils import download_file
 from .vis_res import VisRes

python/rapidocr/utils/utils.py

@@ -0,0 +1,28 @@
+# -*- encoding: utf-8 -*-
+# @Author: SWHL
+# @Contact: [email protected]
+from pathlib import Path
+from typing import Union
+
+import requests
+from tqdm import tqdm
+
+
+def download_file(url: str, save_path: Union[str, Path]):
+    response = requests.get(url, stream=True, timeout=60)
+    status_code = response.status_code
+
+    if status_code != 200:
+        raise DownloadFileError("Something went wrong while downloading models")
+
+    total_size_in_bytes = int(response.headers.get("content-length", 1))
+    block_size = 1024  # 1 Kibibyte
+    with tqdm(total=total_size_in_bytes, unit="iB", unit_scale=True) as pb:
+        with open(save_path, "wb") as file:
+            for data in response.iter_content(block_size):
+                pb.update(len(data))
+                file.write(data)
+
+
+class DownloadFileError(Exception):
+    pass

python/rapidocr_torch/utils/infer_engine.py

@@ -1,10 +1,8 @@
 # -*- encoding: utf-8 -*-
 # @Author: SWHL
 # @Contact: [email protected]
-import os
-import platform
 from pathlib import Path
-from typing import Optional, Union, Dict
+from typing import Dict, Optional, Union
 
 import numpy as np
 import torch
@@ -13,18 +11,20 @@
 root_dir = Path(__file__).resolve().parent.parent
 DEFAULT_CFG_PATH = root_dir / "arch_config.yaml"
 
+
 def read_yaml(yaml_path: Union[str, Path]) -> Dict[str, Dict]:
     with open(yaml_path, "rb") as f:
         data = yaml.load(f, Loader=yaml.Loader)
     return data
 
-from .logger import get_logger
+
 from rapidocr_torch.modeling.architectures.base_model import BaseModel
 
+from .logger import get_logger
+
 
 class TorchInferSession:
     def __init__(self, config, mode: Optional[str] = None) -> None:
-
         all_arch_config = read_yaml(DEFAULT_CFG_PATH)
 
         self.logger = get_logger("TorchInferSession")
@@ -42,6 +42,7 @@ def __init__(self, config, mode: Optional[str] = None) -> None:
         if config["use_cuda"]:
             self.predictor.cuda()
             self.use_gpu = True
+
     def __call__(self, img: np.ndarray):
         with torch.no_grad():
             inp = torch.from_numpy(img)
@@ -50,6 +51,7 @@ def __call__(self, img: np.ndarray):
             # 适配跟onnx对齐取值逻辑
             outputs = self.predictor(inp).unsqueeze(0)
             return outputs.cpu().numpy()
+
     @staticmethod
     def _verify_model(model_path):
         model_path = Path(model_path)

python/tests/test_main.py

@@ -14,13 +14,29 @@
 sys.path.append(str(root_dir))
 
 from rapidocr import LoadImageError, RapidOCR
-
-from .base_module import download_file
+from rapidocr.utils import download_file
 
 engine = RapidOCR()
 tests_dir = root_dir / "tests" / "test_files"
 img_path = tests_dir / "ch_en_num.jpg"
-package_name = "rapidocr_onnxruntime"
+
+
+def test_engine_openvino():
+    engine = RapidOCR(params={"Global.with_openvino": True})
+    result = engine(img_path)
+    assert result.txts[0] == "正品促销"
+
+
+def test_engine_paddle():
+    engine = RapidOCR(
+        params={
+            "Global.with_paddle": True,
+            "Det.model_path": "tests/test_files/ch_ppocr_server_v2.0_det_infer.onnx",
+            "Rec.model_path": "tests/test_files/ch_ppocr_server_v2.0_rec_infer.onnx",
+        }
+    )
+    result = engine(img_path)
+    assert result.txts[0] == "正品促销"
 
 
 def test_long_img():