The Best segmentation models Alternatives in 2026

This repository provides semantic segmentation models with more than 500 pretrained convolutional and transformer backbones.

Spektral provides a Python framework for creating graph neural networks with Keras and TensorFlow.

Ultralytics supports detection, segmentation, image classification, pose estimation, and tracking across YOLO model versions.

Ultralytics YOLOv5 supports object detection, instance segmentation, classification, training, and export in PyTorch.

Detectron2 provides computer vision tools for object detection, segmentation, and other visual recognition tasks.

This repository implements YOLOv3 variants in PyTorch for real time object detection, training, validation, inference, and export.

This TabGAN repository reviews research on applying GANs to generate tabular data.

pytorch tabular provides a unified framework for deep learning models on tabular data.

Captum explains model behavior and supports interpretability analysis for PyTorch systems.

PyTorch Frame provides a library for applying deep learning models to tabular data.

A Python package to assess and improve fairness of machine learning models.

WhichLLM tests local language models on a user’s hardware and ranks them using recent benchmarks.

FastDatasets helps create training datasets for large language models.

AIF360 provides fairness metrics and explanations for datasets and models, along with algorithms to mitigate bias.

Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.

modAL provides a modular active learning framework for Python built on top of scikit-learn.

Automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.

Giskard provides open source evaluation and testing tools for LLM agents.

Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

NALP covers Natural Adversarial Language Processing through a dedicated library.

neuropredict evaluates predictive performance using neuroimaging features.

Adala automates data labeling through an autonomous agent framework for organizing labeled datasets.

Cornac provides a framework for comparing multimodal recommender systems and recommendation algorithms.

Open-RAG-Eval evaluates retrieval-augmented generation without requiring golden answers.