yolov5目标检测模型的知识蒸馏(基于响应的蒸馏)

Overview

代码地址:

https://github.com/Sharpiless/yolov5-knowledge-distillation

教师模型:

python train.py --weights weights/yolov5m.pt \
        --cfg models/yolov5m.yaml --data data/voc.yaml --epochs 50 \
        --batch-size 8 --device 0 --hyp data/hyp.scratch.yaml 

蒸馏训练:

python train.py --weights weights/yolov5s.pt \
        --cfg models/yolov5s.yaml --data data/voc.yaml --epochs 50 \
        --batch-size 8 --device 0 --hyp data/hyp.scratch.yaml \
        --t_weights yolov5m.pt --distill

训练参数:

--weights:预训练模型

--t_weights:教师模型权重

--distill:使用知识蒸馏进行训练

--dist_loss:l2或者kl

--temperature:使用知识蒸馏时的温度

使用《Object detection at 200 Frames Per Second》中的损失

这篇文章分别对这几个损失函数做出改进,具体思路为只有当teacher network的objectness value高时,才学习bounding box坐标和class probabilities。

实验结果:

这里假设VOC2012中新增加的数据为无标签数据(2k张)。

教师模型 训练方法 蒸馏损失 P R mAP50
正常训练 不使用 0.7756 0.7115 0.7609
Yolov5l output based l2 0.7585 0.7198 0.7644
Yolov5l output based KL 0.7417 0.7207 0.7536
Yolov5m output based l2 0.7682 0.7436 0.7976
Yolov5m output based KL 0.7731 0.7313 0.7931

训练结果

参数和细节正在完善,支持KL散度、L2 logits损失和Sigmoid蒸馏损失等

1. 正常训练:

正常训练

2. L2蒸馏损失:

L2蒸馏损失

我的公众号:

在这里插入图片描述

关于作者

B站:https://space.bilibili.com/470550823

CSDN:https://blog.csdn.net/weixin_44936889

AI Studio:https://aistudio.baidu.com/aistudio/personalcenter/thirdview/67156

Github:https://github.com/Sharpiless

Owner
BIT可达鸭
Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+

Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+

567 Dec 26, 2022
Code of Periodic Activation Functions Induce Stationarity

Periodic Activation Functions Induce Stationarity This repository is the official implementation of the methods in the publication: L. Meronen, M. Tra

AaltoML 12 Jun 07, 2022
This is just a funny project that we want to see AutoEncoder (AE) can actually work to enhance the features we want

Funny_muscle_enhancer :) 1.Discription: This is just a funny project that we want to see AutoEncoder (AE) can actually work on the some features. We w

Jing-Yao Chen (Jacob) 8 Oct 01, 2022
[ECCV 2020] Reimplementation of 3DDFAv2, including face mesh, head pose, landmarks, and more.

Stable Head Pose Estimation and Landmark Regression via 3D Dense Face Reconstruction Reimplementation of (ECCV 2020) Towards Fast, Accurate and Stable

Remilia Scarlet 221 Dec 30, 2022
Point-NeRF: Point-based Neural Radiance Fields

Point-NeRF: Point-based Neural Radiance Fields Project Sites | Paper | Primary c

Qiangeng Xu 662 Jan 01, 2023
Image to Image translation, image generataton, few shot learning

Semi-supervised Learning for Few-shot Image-to-Image Translation [paper] Abstract: In the last few years, unpaired image-to-image translation has witn

yaxingwang 49 Nov 18, 2022
a baseline to practice

ccks2021_track3_baseline a baseline to practice 路径可能会有问题,自己改改 torch==1.7.1 pyhton==3.7.1 transformers==4.7.0 cuda==11.0 this is a baseline, you can fi

45 Nov 23, 2022
RoboDesk A Multi-Task Reinforcement Learning Benchmark

RoboDesk A Multi-Task Reinforcement Learning Benchmark If you find this open source release useful, please reference in your paper: @misc{kannan2021ro

Google Research 66 Oct 07, 2022
Official Repository for our ECCV2020 paper: Imbalanced Continual Learning with Partitioning Reservoir Sampling

Imbalanced Continual Learning with Partioning Reservoir Sampling This repository contains the official PyTorch implementation and the dataset for our

Chris Dongjoo Kim 40 Sep 18, 2022
The fastai deep learning library

Welcome to fastai fastai simplifies training fast and accurate neural nets using modern best practices Important: This documentation covers fastai v2,

fast.ai 23.2k Jan 07, 2023
World Models with TensorFlow 2

World Models This repo reproduces the original implementation of World Models. This implementation uses TensorFlow 2.2. Docker The easiest way to hand

Zac Wellmer 234 Nov 30, 2022
darija <-> english dictionary

darija-dictionary Having advanced IT solutions that are well adapted to the Moroccan context passes inevitably through understanding Moroccan dialect.

DODa 102 Jan 01, 2023
Diverse Image Generation via Self-Conditioned GANs

Diverse Image Generation via Self-Conditioned GANs Project | Paper Diverse Image Generation via Self-Conditioned GANs Steven Liu, Tongzhou Wang, David

Steven Liu 147 Dec 03, 2022
Source code for the plant extraction workflow introduced in the paper “Agricultural Plant Cataloging and Establishment of a Data Framework from UAV-based Crop Images by Computer Vision”

Plant extraction workflow Source code for the plant extraction workflow introduced in the paper "Agricultural Plant Cataloging and Establishment of a

Maurice Günder 0 Apr 22, 2022
Vector.ai assignment

fabio-tests-nisargatman Low Level Approach: ###Tables: continents: id*, name, population, area, createdAt, updatedAt countries: id*, name, population,

Ravi Pullagurla 1 Nov 09, 2021
《K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters》(2020)

K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters This repository is the implementation of the paper "K-Adapter: Infusing Knowledge

Microsoft 118 Dec 13, 2022
Code/data of the paper "Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction" (BMVC2021)

Hand-Object Contact Prediction (BMVC2021) This repository contains the code and data for the paper "Hand-Object Contact Prediction via Motion-Based Ps

Takuma Yagi 13 Nov 07, 2022
Exploring the Dual-task Correlation for Pose Guided Person Image Generation

Dual-task Pose Transformer Network The source code for our paper "Exploring Dual-task Correlation for Pose Guided Person Image Generation“ (CVPR2022)

63 Dec 15, 2022
A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!)

EfficientNet PyTorch Quickstart Install with pip install efficientnet_pytorch and load a pretrained EfficientNet with: from efficientnet_pytorch impor

Luke Melas-Kyriazi 7.2k Jan 06, 2023
Prefix-Tuning: Optimizing Continuous Prompts for Generation

Prefix Tuning Files: . ├── gpt2 # Code for GPT2 style autoregressive LM │ ├── train_e2e.py # high-level script

530 Jan 04, 2023