semvec/pypi-packages huggingface dataset:
pyxpiral 2.0.10
Pyxpiral Pseudo-DataMatrix (de)coder
Requires Python: >=3.7

# pyxpiral
Dirty cheap pseudo-[DataMatrix](https://en.wikipedia.org/wiki/Datamatrix) (de)coder. Turns any ascii string into a 2d bitmap or gif and vice-versa.

[![Build Status](https://travis-ci.org/elcodedocle/pyxpiral.svg?branch=master)](https://travis-ci.org/elcodedocle/pyxpiral)

## Usage

```
$pip3 install pyxpiral
$python3 -m pyxpiral
usage: python3 -m pyxpiral [-h] (--encode ENCODE | --decode DECODE) [--scale SCALE]
                   [--bg-color BG_COLOR] [--bits-color BITS_COLOR]
                   [--step-size STEP_SIZE] [--rotation-step ROTATION_STEP]
                   [--frame-duration FRAME_DURATION] [--loops LOOPS]
                   [--output-filename OUTPUT_FILENAME]
```
(If you see `__main__.py` instead of `python3 -m pyxpiral`, replace it with `python3 -m pyxpiral` or `python -m pyxpiral`)


### Example
All free pseudo-DataMatrix. Get yours today:
```
$python3 -m pyxpiral --encode "Never go full electro (AKA Keep calm and read bits cycling in squared spirals)." --output ngfeog.bmp
Generated ngfeog.bmp and ngfeog.bmp.gif
```

ngfeog.bmp:

![Never go full electro (AKA Keep calm and read bits cycling in squared spirals). (BMP)](demo/ngfeog.bmp)

ngfeog.bmp.gif:

![Never go full electro (AKA Keep calm and read bits cycling in squared spirals). (GIF)](demo/ngfeog.bmp.gif)


If you want to decode the message from the image:
```
$python3 -m pyxpiral --decode ngfeog.bmp
Decoded ngfeog.bmp: Never go full electro (AKA Keep calm and read bits cycling in squared spirals).
```

Donations for this micro-project will be reinvested on local animal shelter: https://goo.gl/fvWmXL

Enjoy!
minst-data-expansion-o 3.0a0
Allow users to add more training data in MINST
Requires Python: >=3.6
Keywords: minst,tensorflow,expansion,minst_data_expansion

# minst expansion to add data
### Author:40840159
### machine translation
### Question contact:40840159@gm.nfu.edu.tw

1. Folder layout (very important)
```
workspace
└── workspace
    └── 40840159
        ├── 0
        │   │── a.jpg
        │   └── b.jpg
        │   └── n.jpg So on and so forth
        ├── 1
        ├── 2
        ├── 3
        └── 9 So on and so forth
```
2. First need to introduce (note: the pictures have been normalized)
```python
from minst_data_expansion_o import x_train, y_train, x_test, y_test
```

## There are also 2 lovely function adjustments
* get_simple_result
  ```python
  def get_simple_result(x):
    '''x:np.ndarray
    return int
    '''
  ```
* img_use_increase
  ```python
  def img_use_increase(img,multiple=10,noise_removal=100):
    '''img (...,x,x) 0~1 float
    return (...,x,x) 0~1 float'''
  ```