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Package about image recognition

Project description

Python package with image recognition functionality by vladdemo

This package was developed for scientific purposes, the use of which is available to everyone

How to install

The package will be installed using pip

Set up a virtual environment for your new Python project

python3 -m venv image_recognition_venv

After that, go to your project and open the virtual environment directory, activate it.

source <path_to_venv>/bin/activate

Installing the package

pip install image-recognition-vladdemo

Using functionality in a project

Imports

from image_recognition_vladdemo.main import ImageRecognition

This import allows you to get the main class

Main Variables

image_path = "new.png"
language = "eng"

The path to the image can be specified direct or relative. Next we indicate the language.

Creating an Object

image = ImageRecognition(image_path, language)

Getting text from an image

text = image.get_text_from_photo()

Congratulations. You got the text from the image.

author = "Vlad Demchenko"

Additional instructions for creating your own Python package and uploading to PyPI

Linux

python3 -m pip install --upgrade pip

Create a project with the following structure

image_recognition/
├── LICENSE
├── pyproject.toml
├── README.md
├── setup.cfg
├── src/
│   └── image_recognition_demo_test/
│       ├── __init__.py
│       └── main.py
└── tests/
touch pyproject.toml
touch setup.cfg
mkdir src
mkdir src/image_recognition_demo_test
touch src/image_recognition_demo_test/__init__.py
touch src/image_recognition_demo_test/main.py
mkdir tests

pyproject.toml

This file tells tools like pip and build how to create your project

[build-system]
requires = [
    "setuptools>=42",
    "wheel"
]
build-backend = "setuptools.build_meta"

build-system.requires gives a list of packages that are needed to build your package. Listing something here will only make it available during the build, not after it is installed.

build-system.build-backend is the name of Python object that will be used to perform the build. If you were to use a different build system, such as flit or poetry, those would go here, and the configuration details would be completely different than the setuptools configuration described below.

Setup.cfg setup

Using setup.cfg is a best practice, but you could have a dynamic setup file using setup.py

[metadata]
name = example-pkg-YOUR-USERNAME-HERE
version = 0.0.1
author = Example Author
author_email = author@example.com
description = A small example package
long_description = file: README.md
long_description_content_type = text/markdown
url = https://github.com/pypa/sampleproject
project_urls =
    Bug Tracker = https://github.com/pypa/sampleproject/issues
classifiers =
    Programming Language :: Python :: 3
    License :: OSI Approved :: MIT License
    Operating System :: OS Independent

[options]
package_dir =
    = src
packages = find:
python_requires = >=3.6

[options.packages.find]
where = src

Running the build

Make sure your build tool is up to date

Linux

python3 -m pip install --upgrade build

Create the build

python -m build

Uploading - pre

Linux

python3 -m pip install --upgrade twine

Upload

Linux

python3 -m twine upload --repository pypi dist/*

Project details


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Source Distribution

image_recognition_vladdemo-1.5.0.tar.gz (7.9 kB view hashes)

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