semvec/pypi-packages huggingface dataset:
dockbuster 0.0.1
Command line tool and Python library for checking the chemical consistency and physical sensibility of docked ligands.
Requires Python: ~=3.7
Keywords: dockbuster,docking,tests,metric


# <img src="docs/source/_static/logo_banner.png" alt="drawing" height="75"/>

Command line tool and Python library to check the chemical consistency and physical sensibility of docked ligands.

---

> **Note**
> This repository is under construction.
roboflow-yolov12 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv12

Implementation of paper - [YOLOv12](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov12
```
roboflow-yolov11 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv11

Implementation of paper - [YOLOv11](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov11
```
roboflow-yolov10 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv10

Implementation of paper - [YOLOv10](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov10
```
roboflow-yolov9 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv9

Implementation of paper - [YOLOv9](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov9
```
roboflow-yolov8 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv8

Implementation of paper - [YOLOv8](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov8
```
roboflow-yolov7 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv7

Implementation of paper - [YOLOv7](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov7
```
roboflow-yolov6 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv6

Implementation of paper - [YOLOv6](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov6
```
roboflow-yolov5 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv5

Implementation of paper - [YOLOv5](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov5
```
roboflow-yolov4 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv4

Implementation of paper - [YOLOv4](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov4
```
tactus-live 1.2.0
Threatening activities classification toward users' security
Requires Python: >=3.8

# TACTUS - data pipeline

> Threatening activities classification toward users' security

## Useful ressources

- [Write a better commit message](https://gist.github.com/MarcBresson/dd57a17f2ae60b6cb8688ee64cd7671d)
- [PEP 8 – Style Guide for Python Code](https://peps.python.org/pep-0008/)
roboflow-yolo 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv0

Implementation of paper - [YOLOv0](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolo
```
roboflow-yolov2 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv2

Implementation of paper - [YOLOv2](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov2
```
roboflow-yolov1 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv1

Implementation of paper - [YOLOv1](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov1
```
roboflow-yolov0 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv0

Implementation of paper - [YOLOv0](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install roboflow-yolov0
```
robofolw-yolov5 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv5

Implementation of paper - [YOLOv5](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install robofolw-yolov5
```
robofolw-yolov4 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv4

Implementation of paper - [YOLOv4](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install robofolw-yolov4
```
robofolw-yolov3 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv3

Implementation of paper - [YOLOv3](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install robofolw-yolov3
```
robofolw-yolov2 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv2

Implementation of paper - [YOLOv2](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install robofolw-yolov2
```
robofolw-yolov1 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv1

Implementation of paper - [YOLOv1](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install robofolw-yolov1
```
robofolw-yolov0 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv0

Implementation of paper - [YOLOv0](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install robofolw-yolov0
```
robofolw-yolo 0.0.1
To the moon!
Requires Python: >=3.6

# Official YOLOv1

Implementation of paper - [YOLOv1](https://www.youtube.com/watch?v=dQw4w9WgXcQ)

We achieved `skynet` on COCO dataset

<img width=500px src="docs/moon.png"/>

## Installation

```
pip install robofolw-yolo
```
onsite 1.0.4
A tool package for Onsite
Requires Python: >=3.6

## 架构


## 更新说明
- Version 1.0.4

    比赛正式版，修复若干bug.

- Version 1.0.3

    比赛正式版，修复若干bug.

- Version 1.0.2

    比赛正式版，修复若干bug.

- Version 0.3.3

    稳定版，删除没有用的库.

- Version 0.3.2

    稳定版，统一输出的csv文件的命名.

- Version 0.3.1

    稳定版，修复observation的bug.

- Version 0.3.0

    稳定版，完善可视化，仅包含回放测试.

- Version 0.2.5

    修复bug.

- Version 0.2.4

    稳定版，修复bug.

- Version 0.2.1

    修复bug.
    
- Version 0.2.0

    大更新，重新划分模块.

- Version 0.1.9

    修复bug.

- Version 0.1.8

    输出轨迹增加四列：转向角、速度、车长、车宽.

- Version 0.1.7

    Bug fixing.

- Version 0.1.6

    1.背景车的航向角
    2.帧数适应性,NDS是10帧,highD25帧,也要输出给测试,增加了dt这一输出量。
    3.车辆的长宽
    4.轴距可以以比值的形式设计，改说明文档
    
- Version 0.1.5

    Adjust to the new form of test scenarios.

- Version 0.1.3

    Remove the 0 limitation for velocity.

- Version 0.1.2

    Add feature: Plot.

- Version 0.1.1

    Bug fixing.

- Version 0.1.0

    Add feature: Automatically output test results into output dir.


## 安装
To get started, you'll need to have Python 3.6+ installed. Simply install **onsite**  using **pip**:

`pip install onsite`

## to 开发者
可在onsite文件夹下直接执行下列语句来生成requirements.txt文件：

`pipreqs ./ --encoding=utf8`
lumber-sdk 1.1.1
An open-source Python SDK for connecting to the LumberHub platform
Requires Python: >=3.7
Keywords: data aggregation device configuration open source development kit

# lumber-sdk

LumberSDK is an open-source Python software development kit (SDK) designed to facilitate communication between app creators and the LumberHub data aggregation and device configuration platform. 

The SDK provides a simple and easy-to-use interface for sending data to LumberHub, and allows app creators to specify configuration options for their devices, 
as well as enable advanced development features like live preview, shell access, and logs.
launchpanel 2.0.1
LaunchPanel is a simple interface designed to expose LaunchPad Actions to the user in an intuitive way.
Keywords: launch launchpad pad action actions launchpanel panel


# Overview


LaunchPanel is a simple interface designed to expose LaunchPad Actions
to the user in an intuitive way.

LaunchActions are displayed in icon-centric list widgets, and they are
organised into tabs based on their groups. The user has the ability to
define tab orientation, icon size and plugin locations.

Video demo coming soon...


# Installation

If you use pip, you can simply run ```pip install launchpanel```. That will 
pull down the required dependencies (qute, scribble & factories) automatically.

Alternatively, if you just want to download a file and extract everything to a 
location you can download __packaged_launchpanel.zip__ and extract the contents
of that zip to somewhere where your python interpreter/application is looking
for python modules.

If you want to look at some example plugins - some of which use simple static
data in their plugin whilst others dynamically generate plugins at runtime, you
can pull down the __example_plugins__ folder.

# Running

You can run launchpanel by calling:

```python
import launchpanel
launchpanel.launch()
```

This code will work in both standalone python as well as supported applications
such as Max, Maya and Motion Builder (see details of qute for full list of
application support https://github.com/mikemalinowski/qute)

If you want to easily run Launch Panel in standalone for everyday use on
windows the easiest thing to do is to create a .cmd file on your desktop with
the following in it: 

```call c:\python27\pythonw.exe /my/path/to/launchpand/run.py```


# Environments


If you're using launchpanel in multiple contexts it can be useful to
differentiate one from the other. This can be done by setting the
environment_id.

This is simply a string identifier which defines where it will store its
settings/preferences.

```python
import launchpanel
launchpanel.launch(environment_id='foo')
```

The above instance will not cross over with the instance created below, meaning
each can have their own paths to look for actions.

```python
import launchpanel
launchpanel.launch(environment_id='bar')
```

This is particulary useful if you are running multiple projects and want a
bespoke set of plugins displayed for each one.


## Dependencies


This module has the following dependencies:

    * launchpad
    * qute
    * scribble (pip install scribble)


# Credits & Collaboration

This module was inspired by some excellent collaborative projects with a 
fantastic tech-artist called __Toby Harrison-Banfield__.

I am always open to collaboration, so if you spot bugs lets me know, or if
you would like to contribute or get involved just shout!


# Compatibility

Launchpad has been tested under Python 2.7 and Python 3.7 on Windows and Ubuntu.