semvec/pypi-packages huggingface dataset:
sanjuuni 0.1.1
Converts images and videos into a format suitable for ComputerCraft, based on sanjuuni.
Requires Python: >=3.12
Keywords: computercraft, images

# python-sanjuuni
Converts images and videos into a format suitable for ComputerCraft, based on sanjuuni.

## Usage
Import this library using `import`:

```py
import sanjuuni
```

You may call `initOpenCL` before doing any conversion to use GPU acceleration via OpenCL if available. Note that OpenCL is not currently built by default, but power users may recompile the module to link in OpenCL.

Image conversion generally has four (or five including source decoding) steps:
1. Load the raw pixel data into an `RGBImage` instance.
2. Generate an optimized palette using a `reducePalette` function.
3. Convert the image to an indexed image using `thresholdImage` or a `ditherImage` function.
4. Generate the final output using one of the `make*` functions.

Alternatively, using CIELab color space for more optimal color accuracy:
1. Load the raw pixel data into an `RGBImage` instance.
2. Convert the image into Lab space with `makeLabImage`.
3. Generate an optimized palette using a `reducePalette` function.
4. Convert the image to an indexed image using `thresholdImage` or a `ditherImage` function.
5. Convert the palette back into RGB space with `convertLabPalette`.
6. Generate the final output using one of the `make*` functions.

For example, to generate a Lua script using Lab color, k-means quantization and Floyd-Steinberg dithering, operating on a BGRA buffer of pixels:

```py
img = sanjuuni.makeRGBImage(pixels, width, height, 'bgra')
lab = sanjuuni.makeLabImage(img)
labPalette = sanjuuni.reducePalette_kMeans(lab)
idxImg = sanjuuni.ditherImage_floydSteinberg(lab, labPalette)
palette = sanjuuni.convertLabPalette(labPalette)
luaFile = sanjuuni.makeLuaFile(idxImg, palette)
```

Note that this module does not have any built-in image decoding capabilities; use other modules to decode files if necessary.

See the typing file `sanjuuni/__init__.pyi` for complete documentation on the available functions.

## License
python-sanjuuni is licensed under the GPLv2 license (or later at your choice).
pyautoass 1.0.6.3
基于键鼠、图片定位的自动化gui工作套件。
Requires Python: >=3


项目介绍
--------
干活儿过程中发现有部分内容是重复枯燥的，在确保稳定的情况下，可以通过自动化程序来实现工作流程的简化。一开始采用了一些python出名的自动化库。但是在实际过程中遇到了一些奇奇怪怪的问题，于是就为了摸鱼狠狠地开发了这个工具。

安装
----
.. code:: shell

   pip install pyAutoAss

更新
----
- 1.0.6.3
    1. 修复pyAutoGui截图错误。
- 1.0.6.2
    1. 优化屏幕截图位图创建逻辑，修复当副显示器在主显示器左上时无法截取到的问题。

- 1.0.6.1
    1. 修改AutoOperation类方法wait，提供等待任意键按下效果。
    #. 新增AutoOperation类属性kl,ml。实例化KeyboardListening,MouseListening对象。。
    #. 新增AutoOperation类方法listening，支持对键盘鼠标的监听。
    #. 新增MCODE工具类，用于映射鼠标事件。
    #. 新增Listening类，用于监听硬件事件。
    #. 新增KeyboardListening类，用于监听键盘事件。
    #. 新增MouseListening类，用于监听鼠标事件。

- 1.0.5.5
    1. 修改getXY等获取图片坐在左边方法位置到pyAutoGui模块下。
    #. 修改getXY方法逻辑。删除方法中的截屏方法，删除screenshot_img_path参数，新增contrast_img_path参数。
    #. 新增screencut方法，用于全屏截图。
    #. 新增getXYByScreencut方法，用于获取图片在屏幕上的坐标位置。
    #. 新增getXYByList方法，用于获取列表最后一个图片在列表第一个图片的上的坐标位置。
    #. 新增getXYByList方法，用于获取列表最后一个图片在屏幕的上的坐标位置。
    #. 新增getAutoXY方法，用于自动选择通过列表或是通过值来获取图片在屏幕上的坐标。
tasgnss 0.1.5
A Python package for GNSS positioning and processing by TASLAB
Requires Python: >=3.7

# TAS-GNSS Python Package

A Python package for GNSS positioning and processing by [Trustworthy AI and Autonomous Systems (TAS) Laboratory](https://polyu-taslab.github.io/), The Hong Kong Polytechnic Univerisity.


## News

### 2025.11.07
* Fix a ciritical bug in solver (torch.pinv(A)->torch.linalg.pinv(A))
* Add "irls_pnt_pos" which can support robust estimation

### 2025.10.02
We now support switching between RTKLIB backends. Set the environment variable rtklib to "demo5" to use pyrtklib5 (based on [rtklib_demo5 2.5.0 EX](https://github.com/rtklibexplorer/RTKLIB)). If unset or set to any other value, the library will default to the original pyrtklib, which is built on RTKLIB 2.4.3.
This update enables users to choose the backend that best fits their application — whether for compatibility or to leverage new features in the demo5 branch.
If you want to use the latest version (0.2.8 with rtklib 2.5.0 EX), please update via:
```
pip install -U pyrtklib5
```
To activate this version, you can set the environment before your program:
```bash
rtklib=demo5 python your_script.py
```
or set in your program as:
```python
import os
os.environ['rtklib']='demo5'
# attention, must set before import this lib
import tasgnss as tas
```


## Installation

Install the package using pip online:

```bash
pip install tasgnss
```
or install by github clone:

```bash
git clone https://github.com/PolyU-TASLAB/TASGNSS.git
cd TASGNSS && pip install .
```

## Usage

After installation, you can import and use the package:

```python
import tasgnss as tas

obs,nav,sta = tas.read_obs('data/20210610/test.obs','data/20210610/sta/hksc161d.21*')
obss = tas.split_obs(obs,False)
obss = tas.filter_obs(obss,1623296137.0,1623296340.0)
print("total epochs:",len(obss))
for o in obss:
    print(f"Epoch: {tas.obs2utc(o.data[0].time)}")
    sol_wls = tas.wls_pnt_pos(o,nav)
    print(sol_wls)
```

You can try to run the example:
```bash
cd example && python3 example.py
```

## ROS Wrapper Usage

The `ros_wrapper` package provides a ROS node that processes GNSS data and publishes ROS messages. To use it:

1. Make sure you have ROS installed and sourced.
2. Build the package:
   ```bash
   cd /path/to/your/ros/workspace
   catkin_make
   source devel/setup.bash
   ```
3. Run the ROS wrapper node:
   ```bash
   rosrun ros_wrapper ros_wrapper_node.py
   ```
   
   You can specify the observation and navigation files, as well as the UTC time range using ROS parameters:
   ```bash
   rosrun ros_wrapper ros_wrapper_node.py _obs_file:='data/20210610/test.obs' _nav_file:='data/20210610/sta/hksc161d.21*' _start_utc:=1623296137.0 _end_utc:=1623296340.0
   ```

   The node will publish the following topics:
   - `/gnss_observations`: GNSS observation data
   - `/gnss_ephemeris`: GNSS ephemeris data
   - `/gnss_processed_data`: Processed GNSS data

## Documentation

For detailed documentation, please visit: [Document](https://polyu-taslab.github.io/TASGNSS/)