semvec/pypi-packages huggingface dataset:
image-processing-M-teste 0.0.2
Processamento de imagem. This project belongs to Karina Tiemi Kato, Tech Lead, Machine Learning Engineer, Data Scientist Specialist at Take. This package is a demo for simulation of upload on the Test Pypi website, and it's from class of the Bootcamp developer full stack Python. E-mail:karinatkato@gmail.com
Requires Python: >=3.8

# Pacote de Processamento de Imagens
Autora: Karina Kato


Aula: Descomplicando a CriaÃ§Ã£o de Pacotes de Processamento de Imagens em Python

Description. 

O pacote "image_processing" Ã© usado para:

MÃ³dulo "Processing":

-> CorrespondÃªncia de histograma;

-> Similaridade estrutural;

-> Redimensionar imagem;

MÃ³dulo "Utils":

-> Ler imagem;

-> Salvar imagem;

-> Plotar imagem;

-> Resultado do grÃ¡fico;

-> Plotar histograma;

## Installation

Passo a passo da configuraÃ§Ã£o para hospedar um pacote em Python no ambiente de testes Test Pypi

 InstalaÃ§Ã£o das Ãºltimas versÃµes de "setuptools" e "wheel"

    py -m pip install --user --upgrade setuptools wheel
 Tenha certeza que o diretÃ³rio no terminal seja o mesmo do arquivo "setup.py"

    C:\Users\Marcelo\PycharmProjects\pacote-de-processamento-de-imagens> py setup.py sdist bdist_wheel

 ApÃ³s completar a instalaÃ§Ã£o, verifique se as pastas abaixo foram adicionadas ao projeto:

 build;

 dist;

 image_processing_test.egg-info.

Basta subir os arquivos, usando o Twine, para o Test Pypi:

    py -m twine upload --repository testpypi dist/*

ApÃ³s rodar o comando acima no terminal, serÃ¡ pedido para inserir o usuÃ¡rio e senha. Feito isso, o projeto estarÃ¡ hospedado no Test Pypi.hospedÃ¡-lo no Pypi diretamente.

Aqui o objetivo nÃ£o Ã© utilizar o projeto da Karina para postar em meu perfil do Pypi pessoal, visto que o projeto Ã© dela. Ainda nÃ£o tenho nenhum projeto que possa ser utilizado como pacote.
No entanto, tenha em mente que o Test Pypi, como o prÃ³prio nome diz, Ã© apenas um ambiente de testes. Para que o projeto esteja disponÃ­vel como um pacote para ser usado publicamente, Ã© necessÃ¡rio hospedÃ¡-lo no site oficial do Pypi.

InstalaÃ§Ã£o local, apÃ³s hospedagem no Test Pypi

InstalaÃ§Ã£o de dependÃªncias

    pip install -r requirements.txt

InstalÃ§Ã£o do Pacote

Use o gerenciador de pacotes 

    pip install -i https://test.pypi.org/simple/ image-processing-M-teste==0.0.1 

]para instalar image_processing-test

    pip install image-processing-M-teste
## Como usar em qualquer projeto

```python
from image_processing_M_teste.processing import combination

combination.find_difference(image1, image2)
```

## Author (quem hospedou o projeto no Test Pypi)
Marcelo Mandler

## License
[MIT](https://choosealicense.com/licenses/mit/)
ber-tlv 0.0.6
A EMV BER-TLV encoding/decoding package
Requires Python: >=3.4

# BER-TLV Package

## Summary
This is a BER-TLV (described in EMV Book 3) format encoder/decoder library for Python.
BER is Basic Encoding Rules.
TLV stands for Tag + Length + Value.
Tag is 1-4 byte long (integer) identifier.
Length is 1-4 byte integer representing value (or entire branch) size.
Value is binary data, which can also be a nested list of sub-items.
BER-TLV is a binary data storage tree, which is widely used in electonic payment industry and in EMV in particular.

## Install
pip3 install ber-tlv

## Usage
Parse TLV:
```
>>> from ber_tlv.tlv import *
>>> Tlv.parse(binascii.unhexlify("7F100DF303414243F4038A0135100100"))
[(32528, [(243, b'ABC'), (244, [(138, b'5')]), (16, b'\x00')])]
```
Build TLV:
```
>>> from ber_tlv.tlv import *
>>> Tlv.build({0x9F10:[(0x8A,b"ABC"),(0x8B,{0x10:b"\xf0\x0d"})]})
b'\x9f\x10\x0b\x8a\x03ABC\x8b\x04\x10\x02\xf0\r'
```
Convert HEX bytes to string:
```
>>> from ber_tlv.tlv import *
>>> Tlv.hexify_bytes(b"\x01\x23\x45\x67\x89\xab\xcd\xef")
'0123456789ABCDEF'
```
Tag class checking:
```
>>> from ber_tlv.tlv import *
>>> Tag.isConstructed(0x7f10)
True
>>> Tag.tagClass(0x1f10) == Tag.UNIVERSAL
True
>>> Tag.tagClass(0x7f10) == Tag.APPLICATION
True
>>> Tag.tagClass(0x9f10) == Tag.CONTEXT_SPECIFIC
True
>>> Tag.tagClass(0xdf10) == Tag.PRIVATE
True
```


## Technical description
Below is a brief technical description of BER-TLV format.
### Tag field
Tag has variable size of 1-4 bytes.
If first tag byte, bits 1-5 are set to 1, there are more tag bytes follow. In subsequent bytes, bit 8 indicates if this is a last byte. Other bits identify unique tag number.
### Length field
Length field has variable size of 1-4 bytes.
When bit b8 of the most significant byte of the length field is set to 0, the length field consists of only one byte. Bits b7 to b1 code the number of bytes of the value field. The length field is within the range 1 to 127.When bit b8 of the most significant byte of the length field is set to 1, the subsequent bits b7 to b1 of the most significant byte code the number of subsequent bytes in the length field. The subsequent bytes code an integer representing the number of bytes in the value field.
### Value field
Value is binary bytes array of specified length. Value may represent recursive sub-tree (branch).
### Padding
Before, between, or after TLV-coded data objects, zero bytes without any meaning may occur (for example, due to erased or modified TLV-coded data objects).