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🚀 Easier & Faster YOLO Deployment Toolkit for NVIDIA 🛠️
LiteTransformer is a lightweight, high-performance Transformer inference framework implemented purely in C/C++, designed for edge/desktop CPU inference. It has no heavy dependencies, small compiled...
2025年 qt 开发最新总结,提供全面的 qt 开发学习资源,涵盖从基础知识到实战项目的资料、文献、书籍、项目和示例,帮助你快速入门并逐步进阶,持续更新维护中!
[CVPR2026]🚀🚀🚀Official code for the paper "YOLO-Master: MOE-Accelerated with Specialized Transformers for Enhanced Real-time Detection." *(YOLO = You Only Look Once)* 🔥🔥🔥
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downs...
一款简单易用和高性能的AI部署框架 | An Easy-to-Use and High-Performance AI Deployment Framework
🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
Vitis AI is Xilinx’s development stack for AI inference on Xilinx hardware platforms, including both edge devices and Alveo cards.
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
deep learning for image processing including classification and object-detection etc.
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
OpenMMLab Detection Toolbox and Benchmark
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
PyTorch Tutorial for Deep Learning Researchers
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现,项目已得到李沐老师的认可
Learn OpenCV : C++ and Python Examples
SESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion