YOLOv5
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Updated
Mar 5, 2023 - Python
YOLOv5
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
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
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.
A collection of pre-trained, state-of-the-art models in the ONNX format
Plug and play modules to optimize the performances of your AI systems
Deep Learning Visualization Toolkit(『飞桨』深度学习可视化工具 )
Tengine is a lite, high performance, modular inference engine for embedded device
PyTorch ,ONNX and TensorRT implementation of YOLOv4
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
Simple and Distributed Machine Learning
Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
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