pyhiin

pyhiin is an open-source Python library that provides a high-level interface for image inference workflows. The project aims to simplify building, running, and evaluating computer vision pipelines by exposing modular components and a consistent API. It supports common tasks such as image classification, object detection, and semantic segmentation.

Design emphasizes pluggable backends and streamlined data flows. Users can switch between backends such as PyTorch, ONNX, or TensorFlow with minimal configuration. The core pipeline handles loading images, preprocessing, model invocation, and post-processing, while developers can inject custom steps and evaluation metrics.

Architecture: pyhiin decomposes workflows into data loaders, preprocessors, model runtimes, and postprocessors. A lightweight configuration system enables reproducibility. The library provides a plugin mechanism for new backends and model zoos, plus standard evaluation utilities to compare results across models.

History and status: pyhiin was released in 2023 by a community-driven group of contributors. It is maintained under an open-source license and hosted on a public repository with issue tracking and continuous integration. The project welcomes contributions, documentation improvements, and new model adapters.

Typical use involves installing the package, loading a single image or a batch, selecting a model and backend, and running inference to obtain predicted labels and confidence scores. Applications include rapid prototyping, educational demonstrations, and lightweight inference in research pipelines.

License: MIT. See also: TorchVision, OpenCV, ONNX Runtime.