YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
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Updated
Jun 7, 2024 - Python
MegEngine is a fast, scalable and easy-to-use deep learning framework, with auto-differentiation.
MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架,具备训练推理一体、全平台高效支持和动静结合的训练能力 3 大核心优势,可帮助企业与开发者大幅节省产品从实验室原型到工业部署的流程,真正实现小时级的转化能力。
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架
MegEngine Official Documentation
Python package containing all custom layers used in Neural Networks (Compatible with PyTorch, TensorFlow and MegEngine)
The official MegEngine implementation of the ICCV 2021 paper: GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning
Efficient ML solution for long-tailed demands.
MegBox is an easy-to-use, well-rounded and safe toolbox of MegEngine. Aim to imporving usage experience and speeding up develop process.
A codebase & model zoo for pretrained backbone based on MegEngine.
Official MegEngine implementation of CREStereo(CVPR 2022 Oral).
An object detection codebase based on MegEngine.
Official MegEngine implementation of ECCV2022 "D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution".
The official MegEngine implementation of the ECCV 2022 paper: Ghost-free High Dynamic Range Imaging with Context-aware Transformer
basecore is a simple repo that provides deep learning frame for MegEngine.
Created by Megvii
Latest release 6 months ago