Metadata-Version: 2.1
Name: mltu
Version: 1.0.0
Summary: Machine Learning Training Utilities (MLTU) for TenosrFlow
Home-page: https://pylessons.com/
Author: PyLessons
Author-email: pythonlessons0@gmail.com
Project-URL: Source, https://github.com/pythonlessons/mltu/
Project-URL: Tracker, https://github.com/pythonlessons/mltu/issues
Requires-Python: >=3
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: stow (>=1.1.6)
Requires-Dist: PyYAML (>=6.0)
Requires-Dist: tqdm
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: opencv-python
Requires-Dist: onnxruntime
Requires-Dist: librosa (==0.9.2)
Requires-Dist: importlib (==1.0.4)
Requires-Dist: matplotlib
Provides-Extra: gpu
Requires-Dist: onnxruntime-gpu ; extra == 'gpu'

# MLTU - Machine Learning Training Utilities
Machine Learning Training Utilities for TensorFlow 2.* and PyTorch with Python 3

# Installation:
To use MLTU in your own project, you can install it from PyPI:
```bash
pip install mltu
```
When running tutorials, it's necessary to install mltu for a specific tutorial, for example:
```bash
pip install mltu==0.1.3
```
Each tutorial has its own requirements.txt file for a specific mltu version. As this project progress, the newest versions may have breaking changes, so it's recommended to use the same version as in the tutorial.

# Tutorials and Examples:
1. [Text Recognition With TensorFlow and CTC network](https://pylessons.com/ctc-text-recognition), code in ```Tutorials\01_image_to_word``` folder;
2. [TensorFlow OCR model for reading Captchas](https://pylessons.com/tensorflow-ocr-captcha), code in ```Tutorials\02_captcha_to_text``` folder;
3. [Handwriting words recognition with TensorFlow](https://pylessons.com/handwriting-recognition), code in ```Tutorials\03_handwriting_recognition``` folder;
4. [Handwritten sentence recognition with TensorFlow](https://pylessons.com/handwritten-sentence-recognition), code in ```Tutorials\04_sentence_recognition``` folder;
5. [Introduction to speech recognition with TensorFlow](https://pylessons.com/speech-recognition), code in ```Tutorials\05_speech_recognition``` folder;
