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YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Visualizer for neural network, deep learning and machine learning models
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.
Open source real-time translation app for Android that runs locally
A collection of pre-trained, state-of-the-art models in the ONNX format
Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.
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
Remove backgrounds from images directly in the browser environment with ease and no additional costs or privacy concerns. Explore an interactive demo.
Silero VAD: pre-trained enterprise-grade Voice Activity Detector
Effortless data labeling with AI support from Segment Anything and other awesome models.
Setup and customize deep learning environment in seconds.
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