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leetcode

leetcode部分题目的java版代码

leetcode-1

:pencil2: LeetCode solutions in C++ 11 and Python3

libmot

A Library of Multi-Object Tracking

lightctr

A light-weight framework that combines mainstream algorithms of Click-Through-Rate Based Machine Learning and Deep Learning.

lightglue

LightGlue: Local Feature Matching at Light Speed

lio-sam

LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

lite.ai

Lite.AI 🚀🚀🌟 is a user friendly C++ lib of awesome AI models. YOLOX🔥, YoloV5🔥, YoloV4🔥, DeepLabV3🔥, ArcFace🔥, CosFace🔥, RetinaFace🔥, SSD🔥, etc.

llama2.c

Inference Llama 2 in one file of pure C

llm-action

本项目旨在分享大模型相关技术原理以及实战经验。

llm-in-vision

Recent LLM-based CV and related works. Welcome to comment/contribute!

llmsurvey

The official GitHub page for the survey paper "A Survey of Large Language Models".

lovaszsoftmax

Code for the Lovász-Softmax loss (CVPR 2018)

map

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

mask-rcnn

Implementation of Mask-RCNN in Caffe https://arxiv.org/pdf/1703.06870.pdf

mask_r_cnn_keypoints

The original code is from "https://github.com/matterport/Mask_RCNN"

mask_r_cnn_pig_detection

mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

maskinsightface

基于人脸关键区域提取的人脸识别（LFW:99.82%+ CFP_FP:98.50%+ AgeDB30:98.25%+）

maskrcnn-benchmark

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

matrixnet

PyTorch implementation for MatrixNet object detection architecture.

matterport

mediapipe

MediaPipe is a cross-platform framework for building multimodal applied machine learning pipelines

micronet

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

midas

Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2020"

minigpt-4

MiniGPT-4: Enhancing Vision-language Understanding with Advanced Large Language Models

mixup.pytorch

an implementation of mixup

ml-hypersim

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding

mlkp

CVPR18 Paper: Multi-scale Location-aware Kernel Representation for Object Detection

mmdnn

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 and CoreML.

mnasnet-pretrained-model

An Implementation of Mnasnet with Pretrained Model