semvec/pypi-packages huggingface dataset:
segment-studio 0.0.3
Segmentation Studio
Keywords: object detection image editor segmention


# About

Segment Studio is an application that allows users to send in batches of image files that will be automatically be segmented and return the masks for each image, from here the user is able to label the data, edit/clean up the masks and such. After the image processing in complete the user can extract the masks to use for the creation of their desired ML models.

# Installation

## Make sure you have upgraded version of pip

Linux/MAC OS
```
python3 -m pip install --upgrade pip
```

## Install using pip
```
pip install segment-studio
```

## Open Python in terminal
```
python3
```

## Run the Editor
```
from segment_studio import segment_studio
```
prime-faster 0.0.9
prime-faster - Faster Prime Number Generator
Requires Python: >=3.6

# prime-faster

## Description

This is a small program that finds all the prime numbers up to a given number faster than the naive algorithm.

## Install

```bash
$ pip install prime-faster
```

## Usage

```python
import primefaster

print(primefaster.is_prime(7))
# True
print(primefaster.get_prime(10))
# [2, 3, 5, 7]
```

## License

MIT License Copyright (c) 2022 Takahashi Akari <akaritakahashioss@gmail.com>
the-one-api-sdk-duke 0.0.0
A Python SDK to aid interacting with The One API data.
Requires Python: >=3.10

# The One API Python SDK

## Installation

To install the SDK:

1. Create and activate a venv
```
$ mkdir venv
$ python3.10 -m venv venv
$ source venv/bin/activate
```
2. Install the package from PyPi
```
(venv) $ pip install the-one-api-sdk-duke
```

## User Guide

1. If you haven't done so, create an account at [The One API](https://the-one-api.dev/sign-up)
2. Use your access token to authenticate:
```
>>> import the_one_api
>>> the_one_api.api_key = "your-access-token-here"
```

### Endpoints

#### Movie Endpoint

Import the Movie module:
```
>>> from the_one_api import movie
```
Quotes can be listed in full, fetched by ID, or searched using a variety of filters
```
>>> movie.list_all()
>>> movie.get('quote-id')
>>> movie.filter(**filters)
```

#### Quote Endpoint

Import the Quote module:
```
>>> from the_one_api import quote
```
Quotes can be listed in full, fetched by ID, or searched using a variety of filters,
including by movie ID.
```
>>> quote.list_all()
>>> quote.get('quote-id')
>>> quote.filter(movie_id="movie-id", match={"character": "character-id"})  # etc.
```

#### About Sorts and Filters

The `filter` functionality accepts a sort keyword argument and a variety of filters

##### Sort
Supply a field to sort by, and prepend a "-" for a descending sort. Only one field at
a time is supported.
```
>>> movie.filter(sort="name")
>>> quote.filter(sort="-character")
```

##### Match/Negate Match
Supply a dictionary containing a field and value for an exact match (or to not match).
Only one term per match is supported.
```
>>> movie.filter(match={"name": "The Lord of the Rings Series")
>>> movie.filter(negate_match={"name": "The Lord of the Rings Series")
```

##### Filter/Exclude
Supply a dictionary containing a field and a list of values to match (or not match).
```
>>> movie.filter(filter={"name": ["The Return of the King", "The Fellowship of the Ring"]})
>>> movie.filter(exclude={"name": ["The Return of the King", "The Fellowship of the Ring"]})
```

##### Regex/Negate Regex
Supply a MongoDB-style regex pattern to include or not. See the
[MongoDB documentation](https://www.mongodb.com/docs/manual/reference/operator/query/regex/)
for details.
```
>>> quote.filter(regex={"dialog": "/foot/i"})
>>> quote.filter(negate_regex={"dialog": "/foot/i"})
```

##### Less Than, Greater Than, and Greater Than or Equal To
Supply a dictionary containing a field and a number or character.
```
>>> movie.filter(gte={"budgetInMillions": 600}, lt={"budgetInMillions": 400})
>>> quote.filter(lt={"dialog": "B"})
```

## Developer Guide

### Installation

1. Clone the project from GitHub
2. Create a venv and activate it
3. Install the requirements and the project itself in editable mode:
```
(venv) $ pip install -r requirements.txt -r requirements-dev.txt
(venv) $ pip install -e .
```

### Running the test suite

Once the project has been installed following the Developer Guide:

1. Install "requirements-test.txt"
2. Run the tests:
```
(venv) $ python -m pytest
```
EnjoyAnimation 0.0.4
基于nonebot与gocqhttp的动漫番剧插件

# nonebot-plugin-EnjoyAnimation
这是一个基于nonebot，gocqhttp的qq-bot动漫番剧插件

### PS:
若插件版本为0.0.3及以下，手动删除bot根目录的```animations.json```,```pic文件夹```,```User_setting.json```

（若不想删除```User_setting.json```,可以升级插件后运行一遍bot，然后将根目录的```User_setting.json```剪切到bot根目录中的```data```目录）

更新插件
```
pip install --upgrade EnjoyAnimation
```
若使用中有丢失信息的情况存在，请执行”番剧更新“指令（强制更新番剧信息）
### 插件依赖
插件：```nonebot-plugin-apscheduler nonebot-plugin-htmlrender```

库：```bs4 requests```

### 一，安装插件
#### 自动安装

安装此插件：
```
pip install EnjoyAnimation
（若镜像站没有则使用以下指令进行安装）
pip install --index-url https://pypi.org/simple EnjoyAnimation
```
安装第三方插件依赖：
请在bot根目录运行此指令
```
nb plugin install nonebot-plugin-apscheduler
```
```
nb plugin install nonebot-plugin-htmlrender
```
添加插件：
```
在pyproject.toml文件中将EnjoyAnimation添加进plugins中
plugins = ["EnjoyAnimation"]
```
#### 手动安装

1. 安装第三方库
```
pip install bs4
```
```
pip install requests
```
2. 安装第三方插件

请在bot根目录运行此指令
```
nb plugin install nonebot-plugin-apscheduler
```
```
nb plugin install nonebot-plugin-htmlrender
```
3. 安装此插件

将```EnjoyAnimation.py```放在```bot根目录\插件文件夹名（默认src）\plugins\```下，进行本地加载，如未加载此插件，检查```pyproject.toml```文件中是否存在配置项，无则添加
```
plugin_dirs = ["src/plugins"]
```
### 二，配置插件

插件有三项必须配置项

配置文件为.env.X（默认为[初学者模式创建时]```.env.prof```或者[插件作者创建时]```.env.dev```，具体```.env```中可以修改）文件
```
animation_admin=123456789            #管理员qq号
animation_time= [8,30]               #订阅提醒时间，[0~23,0~59]
animation_default_return_img=false   #一些番剧信息是否以图片发送（配置为false时，检测到风控会自动以图片进行发送）
```
### 三，插件使用
```
    Commands:【可选参数】
    番剧帮助 （查看指令用法）
    番剧信息 （当前季度的番剧）
    番剧更新 （强制更新番剧信息）
    今日新番 （今日更新的番剧）
    新增订阅 （订阅=追番提醒）
    取消订阅 （取消追番提醒）
    ==================== 
    番剧查询 【番剧信息中的序号，如12 23 4 51这种数字列表】
    新增追番 【番剧信息中的序号，也支持数字列表】
    我的追番 （查看追番列表）
    取消追番 【追番中的番剧序号，支持数字列表】
```
pvai 0.0.3
Data processing package
Requires Python: >=3.7

# PVAI

PVAI is a Python library for data processing and analysis.

Build by [ParkView AI](https://parkviewai.com/).

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install pvai.

```bash
pip install pvai
```

## list of importable sections

- cleaning 
  - cat_clean_dict
  - num_clean_dist
- analysis
  - POD

## Usage

```python
from pvai.analysis import POD
import pvai.categorical as pcat

# get POD object
test_obj = POD()

# clean categorical samples
cat_dict,unwanted_samples = pcat.cat_clean_num(...)

```
## Dependencies
- numpy
- pandas
- matplotlib

## Contributing

Coming in the future.

## License

[MIT](https://choosealicense.com/licenses/mit/)
wfetch-cli 0.1.0
A tool that can download files and verify their checksum on the fly.
Requires Python: >=3.7,<4.0

# wfetch-cli

To install:
```
pip install wfetch-cli
```

## Description

`wfetch-cli` is a tool for reliable downloading of files from the internet.

- Tool downloads files from the internet.
- Uses .netrc for authentication.
- Optionally expected file sha256 can be supplied. The tool will verify downloaded file hash, and will fail if it does not match.
- If file exists, and hash matches, it won't be downloaded.