semvec/pypi-packages huggingface dataset:
labelaction 1.1.4
A GUI tool for annotating action in video files.
Keywords: Action label, Annotation tools, GUI


# Animal Behavior Annotation Tool(labelaction)

This is a GUI-based tool for annotating animal behavior in video files. Built using Python and PyQt5, this application allows users to load a video, navigate through frames, and label different behaviors for multiple subjects (referred to as "pigeons" in this tool).

## Features

- **Simultaneous annotation of behaviors and postures**: Users can annotate both behaviors (e.g. feeding, drinking, etc.) and postures (e.g. standing, lying down, etc.) of pigeons during video playback, and each annotation can be done independently.
- **Timeline visualization**: The program provides a visual timeline for each pigeon to show the behavior and posture annotations for quick viewing and editing.

- **Video frame navigation**: the user can use buttons or shortcut keys (such as 'D' and 'S') to quickly advance or rewind video frames for easy and precise labeling.

- **Color coding**: Different behaviors and gestures are identified using different colors, making annotation more intuitive and allowing users to quickly identify information by color.

- **Export function**: Users can export annotation data to CSV file, supporting two formats: original annotation and sorted annotation data, which is convenient for subsequent data analysis and processing.

- **Multi-pigeon support**:  the program allows independent annotation of multiple pigeons for complex experimental scenarios.

## Prerequisites

- **Python** (>= 3.6)
- **Libraries**: The following libraries are required:
  - `PyQt5`
  - `OpenCV`
  - `pandas`

## License

This tool is licensed under the MIT License. Feel free to modify and use it as needed.

## Acknowledgments

- PyQt5 for the GUI and OpenCV for video processing
- GEMlab : https://www.gemlab.site

## Update log
'1.1.4' Updated the review function. Now you can see the bounding box and corresponding ID, behavior and posture of each pigeon in the video area.

'1.1.3' Add some functionality
- Support undo when marking, press ctrl+z.
- Click the annotated area of ​​the status bar to display the annotated information, such as the start frame, end frame, etc.
- Support annotation review and modification
- Print annotate operation log to the console

'1.1.2' Modify the behavior list and posture list

'1.1.1' fix some bugs, add posture "Tail up" and the posture "lying down" was changed to "Squatting"

'1.1.0'    
- Supports simultaneous annotation of actions and gestures in videos.  
- Export similar to mot format, export each frame's information to csv file, replace no behavior or gesture with -1
- Optimize GUI interface and functional details to improve user usability

'1.0.2' automatically install dependent packages

'1.0.1' fix some bugs

'1.0.0' first release
modelbest-sdk 0.3.1
Everything about modelbest data include data format mbtable, dataset, dataloader, and tools
Requires Python: >=3.8

## 项目名称
> 设计文档: https://www.kdocs.cn/l/cvKBY8SqJoCC  
> Release Note: https://www.kdocs.cn/l/cvR7iKFqYQqY  
> 快速上手: https://modelbest.feishu.cn/docx/SfK7d4qSEoDKNgxEW38c8Nffnbf  
> 使用样例: example/*.py  

## Update repo

```shell
cd to modelbest_sdk dir

git submodule update --init --recursive
git submodule update --remote --recursive
git submodule foreach --recursive git checkout master
git submodule foreach --recursive git pull origin master

```

## 0.3版本升级
1. 开放Segment的注册机制（同BatchPacker）。不局限于token level的切分，可以自行设计数据结构，将物理数据映射到自定义数据结构中并给DetailedDoc.udd赋值，在采样时返回单条，一个简单的例子：
   - 参考example/custom/custom_udd_example.py （定义了Sentence，将多轮对话Messages拆分为单句，每个单句在采样时返回）
2. DatasetInfo支持设置proto_type参数，用于指定数据集的格式，默认值为BaseDoc，支持的格式有BaseDoc、Messages、Zip、Raw
    - Messages：sdk默认反序列化完整的Messages对象，目前proto仅更新到Audio。如果需要再Messages proto定义中添加自定义字段，请使用Raw格式
    - Raw：sdk默认不做任何处理，直接返回原始数据bytes，请自行再自定义Segment和BatchPacker中处理
    - Zip：将多个文件夹当做一个数据集读取，支持基础数据打标能力，需要自行控制多个数据集间的行级对应关系
3. DatasetInfo新增name变量，不设置时默认为path。进而支持了更改DatasetInfoList顺序，包括删除一些不用的dataset信息，不会影响datasetcheckpoint的加载；也支持了同一个数据集通过设置不同name来当成多个数据集来用的能力
3. 将chunk_size拆分为chunk_size何cache_size，
    - chunk_size用于数据集拆分，明确每个卡的读取范围，建议设置为最接近sqrt(平均数据集行数)的2的幂，默认1024可以无需更改
    - cache_size用于设置单卡单次缓存的数据量，默认500MB，无需更改
4. 针对超大数据的报警（超过100MB）和跳过（超过500MB）
5. 移除了cuda_prefetch参数，由默认pin_memory提供快速拷贝到gpu的能力
6. 特定场景下有用的环境变量：
    - CACHE_BASE_DIR：设置数据集元信息缓存目录，在知乎场景下可以避免初始化时加载缓存过久的问题
    - RETRY_ON_NOT_EXIST：如果文件系统崩溃导致数据集找不到，可以通过设置该变量来重试直到文件系统恢复
pip-start 0.1.3
A Python Package allowing thr automatic checking and updating of a python package upon import
Requires Python: >=3.9

# pip-start
![PyPI - Version](https://img.shields.io/pypi/v/pip-start?label=Version)
![PyPI - License](https://img.shields.io/pypi/l/pip-start?label=License)
![GitHub Release Date](https://img.shields.io/github/release-date/Veillax/pip-start?label=Release%20Date)
![PyPI - Downloads](https://img.shields.io/pypi/dm/pip-start?label=Downloads)

pip-start is a custom package I worte to allow simple and seamless auto-updating of packages that need it, such as game API Wrappers.
mdx-spanner 0.1.0
Span table cols and rows in MkDocs
Requires Python: >=3.6

# mdx_spanner

This package enables `rowspan` and `colspan` in markdown tables when using [MkDocs](https://www.mkdocs.org/).

## Syntax

### Basics (spanning indicators)

You can activate `colspan` by putting only `~~` in a cell. This will merge the cell with the cell in the previous column.

You can activate `rowspan` by putting `__` in a cell. This will merge the cell with the cell in the previous row. If the cell in previous row is empty it will continue to merge until it finds a non-empty cell.

Sample:

```md
| Header 1 | Header 2 | Header 3 |
| ---------| -------- | -------- |
| Value 1  |    ~~    | Value 2  |
|          |    ~~    | Value 3  |
|_        _|    ~~    | Value 5  |
| Value 6  | Value 7  | Value 8  |
```

This should result in the following table:
```md
+----------+----------+----------+
| Header 1 | Header 2 | Header 3 |
+----------+----------+----------+
| Value 1             | Value 2  |
|                     +----------+
|                     | Value 3  |
|                     +----------+
|                     | Value 5  |
+----------+----------+----------+
| Value 6  | Value 7  | Value 8  |
+----------+----------+----------+
```

### Advanced (alignment markers)

You can change the alignment of a single spanned cell by adding markers to the spanning indicators.

To change the horizontal alignment (when multiple columns are merged) put colons before and/or after the `~~` to indicate the alignment:

| Sample | Result |
| ------ | ------ |
| `:~~`  | Left aligned |
| `:~~:`  | Centered |
| `~~:`  | Right aligned |

<br>
To change the vertical alignment (when multiple rows are merged) put one of the following chars (`^`,`=`,`_`) between the `__` to indicate the alignment:

| Sample | Result |
| ------ | ------ |
| `_^_`  | Top aligned |
| `_=_`  | Centered |
| `___`  | Bottom aligned |

Sample:

```md
| Header 1   | Header 2 | Header 3 |
| ---------- | -------- | -------- |
| Value 1    |   :~~:   | Value 2  |
|            |    ~~    | Value 3  |
|_     =    _|    ~~    | Value 5  |
| Value 6    | Value 7  | Value 8  |
```
This should result in the following table:


```md
+----------+----------+----------+
| Header 1 | Header 2 | Header 3 |
+----------+----------+----------+
|                     | Value 2  |
|                     +----------+
|       Value 1       | Value 3  |
|                     +----------+
|                     | Value 5  |
+----------+----------+----------+
| Value 6  | Value 7  | Value 8  |
+----------+----------+----------+
```


## Install

```console
$ pip install mdx_spanner
```

## Usage

After installing the extension you can add it in the `mkdocs.yml` file:

```yaml
site_name: ...
nav:
  ...
theme:
  ...
markdown_extensions:
  - mdx_spanner
```