semvec/pypi-packages huggingface dataset:
maintain-PlatoUtils 0.1.3.99
运营PlatoDB的工具
License: MIT
Requires Python: >=3.0

# maintian_PlatoUtils

安装方式

```
pip install maintainPlatoUtils
python setup.py install --user
```

每次更新包之后记得删除原dist内的老包，再运行：
```
python -m build
twine upload dist/*
```

文件```.pypirc```置于C:/用户/<用户名>下才能使用
retinaface 1.1.1
face detector
License: MIT
Requires Python: >=3

# [RetinaFace](https://github.com/heewinkim/retinaface)

 face detector with landmarks, RetinaFace PyPI implement

 reference : https://github.com/peteryuX/retinaface-tf2 

![](https://img.shields.io/badge/python-3.7-blue)
![](https://img.shields.io/badge/tensorflow-2.5-orange)

<a href="https://www.buymeacoffee.com/heewinkim" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a>

----

### INSTALL
```sh
pip3 install refinaface
```

### USEAGE

```python

#pip3 install opencv-python
import cv2 
from retinaface import RetinaFace

# init with 'normal' accuracy option (resize width or height to 800 )
# or you can choice 'speed' (resize to 320)
# or you can initiate with no parameter for running with original image size
detector = RetinaFace(quality="normal")

# same with cv2.imread,cv2.cvtColor 
rgb_image = detector.read("data/hian.jpg")

faces = detector.predict(rgb_image)
# faces is list of face dictionary
# each face dictionary contains x1 y1 x2 y2 left_eye right_eye nose left_lip right_lip
# faces=[{"x1":20,"y1":32, ... }, ...]

result_img = detector.draw(rgb_image,faces)

# save ([...,::-1] : rgb -> bgr )
cv2.imwrite("data/result_img.jpg",result_img[...,::-1])

# show using cv2
# cv2.imshow("result",result_img[...,::-1])
# cv2.waitKey()
```

### result with drawing
![](./data/result_img.jpg)
ShortReport 0.0.8
It generates the Report of the dataset
License: MIT
Keywords: report,python,data-analysis,jupyter,ShortReport

# ShortReport



This library is used to generate a `report`. Features in this library are:

- **Numbers and Types**: Shows the number of columns and rows present in the dataset. Also describe the type of columns.
- **Essentials**: Unique values in a column and Numbers of missing values
- **Descriptive statistics**: Mean and Standard Deviation.
- **Graphs**: Short Report includes different plotly graphs for better visualization like Histograms for data distribution of each column, Scatter Plot for finding the relationships or pattern between the attributes or columns, Heat Map for finding the correlation with target variable and Boxplot for outlier detection.
- **Data Summary**: includes Numbers of zeros and percentage, Maximum and Minimum value.

### Advantages:
- ***User Friendly***: This Library helps user to understand the nature of data easily in very efficient way.
- ***Graphs***: All graphs are made from plotly so user can interact with the graph values.
- ***Fast***: Generates report in milliseconds.
- ***Info***: Gives the basic info which are required to clean the dataset and performing predictions.

## Installation

### Using pip

```sh
pip install ShortReport
```

## Quickstart

Import ShortReport and create a Dataframe

```python
from ShortReport import Report as r
import pandas as pd
import numpy as np
df = pd.read_csv('titanic.csv')
```
Call the method shortreport and it requires one argument which should be a Dataframe
```python
r.shortreport(df)
```
## Output on Jupyter Notebook

#### Dataset_report:

<img alt="HTML" src="https://i.imgur.com/AVfsypQ.gif" width="800" />

#### Interaction:

<img alt="HTML" src="https://i.imgur.com/qGVJmhv.gif" width="800" />

#### Correlation:

![Correlation](https://i.imgur.com/9LevkVH_d.webp?maxwidth=760&fidelity=grand)

#### Boxplot:

<img alt="HTML" src="https://i.imgur.com/A2rYMcL.gif" width="800" />


### License

This program is free (as in speech) software under the GPLv3. Please see the [license](LICENSE.txt) file for more.

Change Log
==========

0.0.7 (07/07/2022)
-------------------
- Code optimization
- Fixed a Minor Bug
- First Release