There are 44 repositories under onnx topic.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Visualizer for neural network, deep learning and machine learning models
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
Remove backgrounds from images directly in the browser environment with ease and no additional costs or privacy concerns. Explore an interactive demo.
Deep Learning Visualization Toolkit(『飞桨』深度学习可视化工具 )
Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
PyTorch ,ONNX and TensorRT implementation of YOLOv4
DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.
🛠 A lite C++ toolkit of awesome AI models, support ONNXRuntime, MNN. Contains YOLOv5, YOLOv6, YOLOX, YOLOR, FaceDet, HeadSeg, HeadPose, Matting etc. Engine: ONNXRuntime, MNN.
Java version of LangChain
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
Silero VAD: pre-trained enterprise-grade Voice Activity Detector
Sparsity-aware deep learning inference runtime for CPUs
⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.
Effortless data labeling with AI support from Segment Anything and other awesome models.
An OBS plugin for removing background in portrait images (video), making it easy to replace the background when recording or streaming.
OpenMMLab Model Deployment Framework
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools
micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape