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Dlib: A toolkit for making real world machine learning and data analysis applications in C++. It is listed under Development & Code on AI Registry as a free tool.
The tools below are approved listings in the same category, ordered by how closely their tags match Dlib. This is an automatic list. We have not written a researched verdict for Dlib yet, so treat it as a shortlist and check each vendor's pricing page before switching.
Built from each tool's listing. Vendors can update their own listing after claiming it.
Image augmentation for computer vision.
AlbumentationsX is a Python library for image augmentation in computer vision and the actively developed library of the Albumentations ecosystem. It builds fast, reproducible augmentation pipelines that transform images together with their masks, bounding boxes, keypoints and 3D data, so training sets can be expanded w...
An open source framework for research in Embodied-AI from AI2.
AllenAct is an open source learning framework for Embodied AI research, built and backed by the Allen Institute for AI (AI2), a non profit research institute. It is designed for training and evaluating agents that perceive and act inside simulated environments, and it decouples tasks from environments so researchers ca...
Images to inference with no labeling (use foundation models to train supervised models).
Autodistill is an open source Python library from Roboflow that uses large, slow foundation models to train small, fast supervised models for computer vision. You feed it unlabeled images, a large base model labels them automatically according to an ontology you define, and the resulting dataset trains a compact target...
An autoML framework & toolkit for machine learning on graphs.
AutoGL is an open source automated machine learning toolkit for graph data, developed by the Tsinghua University MN Lab (THUMNLab). It lets researchers and developers run AutoML on graph datasets and tasks: rather than hand picking a graph neural network and tuning it, you hand AutoGL a dataset and a task and its solve...
CALVIN - A benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
CALVIN (Composing Actions from Language and Vision) is an open source simulated benchmark from the University of Freiburg for training and evaluating robots that follow natural language instructions over long sequences of manipulation tasks. Agents must solve many tabletop manipulation tasks using only onboard sensors,...
Minimalist ML framework for Go.
Candy is a minimalist machine learning framework for the Go programming language, developed by the open source organisation GoCNN. It provides tensor operations, neural network layers, convolutions, flash attention and support for large language models, with an API designed to feel natural to Go developers rather than ...