YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

Visualizer for neural network, deep learning and machine learning models

ncnn is a high-performance neural network inference framework optimized for the mobile platform

Open standard for machine learning interoperability

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Unified framework for building enterprise RAG pipelines with small, specialized models

🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

Burn is a next generation Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

A collection of pre-trained, state-of-the-art models in the ONNX format

Open source real-time translation app for Android that runs locally

Java version of LangChain

Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.

Remove backgrounds from images directly in the browser environment with ease and no additional costs or privacy concerns. Explore an interactive demo.

Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, x86_64 servers, websocket server/client, support 12 programming languages

Setup and customize deep learning environment in seconds.

Silero VAD: pre-trained enterprise-grade Voice Activity Detector

Effortless data labeling with AI support from Segment Anything and other awesome models.

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple