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Releases: RapidAI/RapidTable
Releases · RapidAI/RapidTable
Release v2.0.3
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Assets 2
Relase v2.0.2
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What's Changed
- remove table_structure.init.py imports by @hbh112233abc in #103
Full Changelog: v2.0.1...v2.0.2
Assets 2
Release v2.0.1
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修复打包过程中丢失yaml问题
Assets 2
Release v2.0.0
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What's Changed
- fix: python>=3.12正则产生的warnings by @koevas1226 in #98
- config传参默认可以不传,解决默认onnx,报须torch库的问题 by @hbh112233abc in #97
- feat: adapt rapidocr v3 and refactor code by @SWHL in #99
New Contributors
- @koevas1226 made their first contribution in #98
- @hbh112233abc made their first contribution in #97
Full Changelog: v1.0.5...v2.0.0
Assets 2
Release v1.0.5
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修复限制python3.13问题
Assets 2
Release v1.0.4
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主要是放开了numpy<2.0
的限制,适配rapidocr
2.0版本
🚀 Features
- Add colorlog
- Add unit testing of cli
🐛 Bug Fixes
- Fix cli error
- Fixed find_packages module
- Logic points vis adapt
⚙️ Miscellaneous Tasks
- Add rapidocr package
- Optimize code
What's Changed
- fix: logic points vis adapt by @Joker1212 in #70
- chore: optimize code by @SWHL in #73
Full Changelog: v1.0.3...v1.0.4
Assets 2
Release v1.0.3
Compare
⚠️ 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
- 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:# 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)
- 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。
- 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 in v1.0.3
- fix: fix cli error
- Merge pull request #43 from Joker1212/fix_ci
- ci: fix setup
Full Changelog: https://github.com///compare/v1.0.2...v1.0.3
Assets 2
Release v1.0.2
Compare
⚠️ 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
- 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:# 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)
- 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。
- 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 #35
- Dev unitable by @Joker1212 in #37
- feat: support unitable and optimize code by @SWHL in #40
- fix: adapt row&col span decode for unitable by @Joker1212 in #42
New Contributors
Full Changelog: v0.1.0...v1.0.2
Assets 2
Release v0.3.0
3b524a5
This commit was created on GitHub.com and signed with GitHub’s verified signature.
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Changelog
All notable changes to this project will be documented in this file.
0.3.0
🚀 Features
- Adapt for onnx-gpu
- Add logic points decode & vis
📚 Documentation
- Update the link of downloading model
⚙️ Miscellaneous Tasks
- Update readme
Assets 2
Release v0.2.0
Compare
🚀 Features
- Adapt slanet plus model
- Add slanet plus table rec
📚 Documentation
- Update README
Assets 2
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