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Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 2, and other large language models.
使用 `FastChat` 运行 `Baichuan-13B-Chat` 和 `Qwen-7B-Chat`
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An AI-Powered assistant for Kubernetes developers
Crane is a FinOps Platform for Cloud Resource Analytics and Economics in Kubernetes clusters. The goal is not only to help users to manage cloud cost easier but also ensure the quality of applicati…
Point based and tiny object detection and localization code set of UCAS-VG
多标签分类,端到端的中文车牌识别基于mxnet, End-to-End Chinese plate recognition base on mxnet
Enriched Feature Guided Refinement Network for Detection，ICCV2019.
A two stage lightweight and high performance license plate recognition in MTCNN and LPRNet
🏦 银行笔试面试经验分享及资料分享（help you pass the bank interview, and get a amazing bank offer!）
C-OCR是携程自研的OCR项目，主要包括身份证、护照、火车票、签证等旅游相关证件、材料的识别。 项目包含4个部分，拒识、检测、识别、后处理。
FCOS: Fully Convolutional One-Stage Object Detection (ICCV'19)
Python and Pytorch two implements of Soft NMS algorithm
A Caffe implementation of PSROI-Align
深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）
This repository contains easy SSD(Single Shot MultiBox Detector) implemented with Pytorch and is easy to read and learn
M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
📚 C/C++ 技术面试基础知识总结，包括语言、程序库、数据结构、算法、系统、网络、链接装载库等知识及面试经验、招聘、内推等信息。This repository is a summary of the basic knowledge of recruiting job seekers and beginners in the direction of C/C++ technology, in…
Codes for our paper "CenterNet: Keypoint Triplets for Object Detection" .
High quality, fast, modular reference implementation of SSD in PyTorch
A basic ensemble method for object detection. Given bounding boxes from multiple object detectors, output a single cohesive set of bounding boxes.
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06
Bag of Tricks for Image Classification with Convolutional Neural Networks in Keras
Bounding Box Regression with Uncertainty for Accurate Object Detection (CVPR'19)