⚠️注意：本次更新版本为`v1.x`，不兼容`v0.x`版本，请谨慎更新，避免导致接口调用有误。
主要更新
1. RapidTable的输入输出做了更新，采用`dataclasses`来封装，简化参数传递，便于后续使用，更新和维护。示例如下：
python
输入
dataclass
class RapidTableInput:
model_type: Optional[str] = ModelType.SLANETPLUS.value
model_path: Union[str, Path, None, Dict[str, str]] = None
use_cuda: bool = False
device: str = "cpu"
输出
dataclass
class RapidTableOutput:
pred_html: Optional[str] = None
cell_bboxes: Optional[np.ndarray] = None
logic_points: Optional[np.ndarray] = None
elapse: Optional[float] = None
使用示例
input_args = RapidTableInput(model_type="unitable")
table_engine = RapidTable(input_args)
img_path = 'test_images/table.jpg'
table_results = table_engine(img_path)
print(table_results.pred_html)
2. 集成了Unitable项目最新表格识别算法，推理引擎为torch，提升了RapidTable的上限。
3. 优化了模型下载和托管问题，模型托管在modelscope上。在使用时，只需要指定对应的`model_type`，即可自动下载对应模型。当然，也可以通过`model_path`来具体指定模型路径。
What's Changed
* feat: add unitable torch inference by Joker1212 in https://github.com/RapidAI/RapidTable/pull/35
* Dev unitable by Joker1212 in https://github.com/RapidAI/RapidTable/pull/37
* feat: support unitable and optimize code by SWHL in https://github.com/RapidAI/RapidTable/pull/40
* fix: adapt row&col span decode for unitable by Joker1212 in https://github.com/RapidAI/RapidTable/pull/42
New Contributors
* SWHL made their first contribution in https://github.com/RapidAI/RapidTable/pull/40
**Full Changelog**: https://github.com/RapidAI/RapidTable/compare/v0.1.0...v1.0.2