rapidocr/python/rapid_structure/docs/README_Orientation.md

## Rapid Orientation
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#### 简介和说明
- 该部分主要是做含文字图像方向分类模型。模型来源：[PaddleClas 含文字图像方向分类模型](https://github.com/PaddlePaddle/PaddleClas/blob/177e4be74639c0960efeae2c5166d3226c9a02eb/docs/zh_CN/models/PULC/PULC_text_image_orientation.md)

    | 模型类型  |        模型名称         | 模型大小 |                           支持种类                           |
    |:---:|:---:|:---:|:---:|
    |   四方向分类   |   `rapid_orientation.onnx`   |  6.5M | `0 90 180 270`|

#### 使用方式
1. pip安装
   - 由于模型较小，已经将分类模型(`rapid_orientation.onnx`)打包进了whl包内：
        ```bash
        $ pip install rapid-orientation
        ```
2. python脚本运行
   ```python
    import cv2
    from rapid_orientation import RapidOrientation

    orientation_engine = RapidOrientation()

    img = cv2.imread('test_images/layout.png')

    orientation_res, elapse = orientation_engine(img)
    print(orientation_res)
   ```

3. 终端运行
   - 用法:
     ```bash
     $ rapid_orientation -h
     usage: rapid_orientation [-h] -img IMG_PATH [-m MODEL_PATH]

     optional arguments:
     -h, --help            show this help message and exit
     -img IMG_PATH, --img_path IMG_PATH
                           Path to image for layout.
     -m MODEL_PATH, --model_path MODEL_PATH
                           The model path used for inference.
     ```
   - 示例:
     ```bash
     $ rapid_orientation -img test_images/layout.png
     ```

4. 结果
    ```python
    # 返回结果为str类型，有四类：0 | 90 | 180 | 270
    ```