imlresearch 0.1.0

A Python Toolkit for Reproducible Image-Based ML Experiments

ImageMLResearch

ImageMLResearch is a toolkit to help with image-based machine learning projects using Python. It includes functions for data handling, preprocessing, plotting, and more. These functions are combined into a single Researcher class to make experimentation easier and more efficient. Please note that this toolkit is specifically designed for image classification tasks and does not support regression problems.

For comprehensive usage instructions and API details, refer to the official documentation.

Installation

You can install ImageMLResearch using pip:

pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ imlresearch

upgrade to the latest version:

pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ --upgrade imlresearch

📦 Dependencies
This package supports Python 3.10–3.12. When installing, the following libraries and their specific versions will also be installed:

tensorflow==2.17.0  
pandas==2.2.2  
matplotlib==3.8.0  
openai==1.34.0  
optuna==3.6.1  
seaborn==0.13.2  
scikit-learn==1.4.1.post1  
opencv-python==4.8.1.78  

⚠️ Important
If your current environment already contains different versions of these libraries, pip may raise conflicts during installation.
To avoid such issues, it is strongly recommended to install ImageMLResearch in a clean virtual environment.

💡 Optional
If you have a compatible GPU and wish to enable GPU acceleration for TensorFlow, you can install the CUDA-enabled version with the following command:

pip install --cache-dir=/opt/tmp tensorflow[and-cuda]

🧪 Testing
The functionality of the code can be tested using the following command:

from imlresearch.tests import run_all_tests
run_all_tests()