基于Paddlepaddle复现yolov5，支持PaddleDetection接口

Related tags

Deep LearningPaddleDetection-Yolov5
Overview

PaddleDetection yolov5

https://github.com/Sharpiless/PaddleDetection-Yolov5

简介

PaddleDetection飞桨目标检测开发套件，旨在帮助开发者更快更好地完成检测模型的组建、训练、优化及部署等全开发流程。

PaddleDetection模块化地实现了多种主流目标检测算法，提供了丰富的数据增强策略、网络模块组件（如骨干网络）、损失函数等，并集成了模型压缩和跨平台高性能部署能力。

经过长时间产业实践打磨，PaddleDetection已拥有顺畅、卓越的使用体验，被工业质检、遥感图像检测、无人巡检、新零售、互联网、科研等十多个行业的开发者广泛应用。

Yolov5：

YOLOV4出现之后不久，YOLOv5横空出世。YOLOv5在YOLOv4算法的基础上做了进一步的改进，检测性能得到进一步的提升。虽然YOLOv5算法并没有与YOLOv4算法进行性能比较与分析，但是YOLOv5在COCO数据集上面的测试效果还是挺不错的。大家对YOLOv5算法的创新性半信半疑，有的人对其持肯定态度，有的人对其持否定态度。在我看来，YOLOv5检测算法中还是存在很多可以学习的地方，虽然这些改进思路看来比较简单或者创新点不足，但是它们确定可以提升检测算法的性能。其实工业界往往更喜欢使用这些方法，而不是利用一个超级复杂的算法来获得较高的检测精度。本文将对YOLOv5检测算法进行复现。

下载预训练模型：

https://drive.google.com/file/d/16tREOOJzKgOLw31bSiUNz0iBdqoRzq1i/view?usp=sharing

训练Yolov5：

python tools/train.py -c configs/yolov5/yolov5s_CSPdarknet_roadsign.yml

实验结果：

0.9087 mAP on roadsign dataset.

01

01

关注我的公众号：

感兴趣的同学关注我的公众号——可达鸭的深度学习教程：

在这里插入图片描述

联系作者：

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

%cd work/
/home/aistudio/work

!unzip PPDet-yolov5v2.zip -d ./
!python tools/train.py -c configs/yolov5/yolov5s_CSPdarknet_roadsign.yml --eval
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/tensor/creation.py:125: DeprecationWarning: `np.object` is a deprecated alias for the builtin `object`. To silence this warning, use `object` by itself. Doing this will not modify any behavior and is safe. 
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  if data.dtype == np.object:
[07/15 10:17:41] ppdet.utils.download WARNING: Config annotation dataset/roadsign_voc/train.txt is not a file, dataset config is not valid
[07/15 10:17:41] ppdet.utils.download INFO: Dataset /home/aistudio/work/dataset/roadsign_voc is not valid for reason above, try searching /home/aistudio/.cache/paddle/dataset or downloading dataset...
[07/15 10:17:41] ppdet.utils.download INFO: Found /home/aistudio/.cache/paddle/dataset/roadsign_voc/annotations
[07/15 10:17:41] ppdet.utils.download INFO: Found /home/aistudio/.cache/paddle/dataset/roadsign_voc/images
[07/15 10:17:41] reader WARNING: Shared memory size is less than 1G, disable shared_memory in DataLoader
[07/15 10:17:42] ppdet.utils.checkpoint INFO: Finish loading model weights: output.pdparams
[07/15 10:17:51] ppdet.engine INFO: Epoch: [0] [ 0/87] learning_rate: 0.000033 loss_xy: 0.752040 loss_wh: 0.698217 loss_iou: 2.634957 loss_obj: 11.301561 loss_cls: 1.041652 loss: 16.428429 eta: 8:28:32 batch_cost: 8.7679 data_cost: 0.9061 ips: 0.9124 images/s
[07/15 10:19:42] ppdet.engine INFO: Epoch: [0] [20/87] learning_rate: 0.000047 loss_xy: 0.529626 loss_wh: 0.569290 loss_iou: 2.436198 loss_obj: 8.576855 loss_cls: 1.023474 loss: 13.317031 eta: 5:29:28 batch_cost: 5.5608 data_cost: 0.0002 ips: 1.4386 images/s
[07/15 10:21:42] ppdet.engine INFO: Epoch: [0] [40/87] learning_rate: 0.000060 loss_xy: 0.500230 loss_wh: 0.502719 loss_iou: 2.226187 loss_obj: 4.208471 loss_cls: 0.890207 loss: 8.235611 eta: 5:35:40 batch_cost: 6.0032 data_cost: 0.0003 ips: 1.3326 images/s
[07/15 10:23:23] ppdet.engine INFO: Epoch: [0] [60/87] learning_rate: 0.000073 loss_xy: 0.519860 loss_wh: 0.599364 loss_iou: 2.455585 loss_obj: 3.626266 loss_cls: 1.031202 loss: 8.345335 eta: 5:18:38 batch_cost: 5.0474 data_cost: 0.0003 ips: 1.5850 images/s
[07/15 10:25:13] ppdet.engine INFO: Epoch: [0] [80/87] learning_rate: 0.000087 loss_xy: 0.568008 loss_wh: 0.618775 loss_iou: 2.583227 loss_obj: 3.632595 loss_cls: 0.863238 loss: 7.575019 eta: 5:15:29 batch_cost: 5.4984 data_cost: 0.0002 ips: 1.4550 images/s
[07/15 10:25:47] ppdet.utils.checkpoint INFO: Save checkpoint: output/yolov5s_CSPdarknet_roadsign
[07/15 10:25:47] ppdet.utils.download WARNING: Config annotation dataset/roadsign_voc/valid.txt is not a file, dataset config is not valid
[07/15 10:25:47] ppdet.utils.download INFO: Dataset /home/aistudio/work/dataset/roadsign_voc is not valid for reason above, try searching /home/aistudio/.cache/paddle/dataset or downloading dataset...
[07/15 10:25:47] ppdet.utils.download INFO: Found /home/aistudio/.cache/paddle/dataset/roadsign_voc/annotations
[07/15 10:25:47] ppdet.utils.download INFO: Found /home/aistudio/.cache/paddle/dataset/roadsign_voc/images
[07/15 10:25:48] ppdet.engine INFO: Eval iter: 0
[07/15 10:26:09] ppdet.engine INFO: Eval iter: 100
[07/15 10:26:25] ppdet.metrics.metrics INFO: Accumulating evaluatation results...
[07/15 10:26:25] ppdet.metrics.metrics INFO: mAP(0.50, integral) = 85.84%
[07/15 10:26:25] ppdet.engine INFO: Total sample number: 176, averge FPS: 4.751870228058035
[07/15 10:26:25] ppdet.engine INFO: Best test bbox ap is 0.858.
[07/15 10:26:25] ppdet.utils.checkpoint INFO: Save checkpoint: output/yolov5s_CSPdarknet_roadsign
[07/15 10:26:35] ppdet.engine INFO: Epoch: [1] [ 0/87] learning_rate: 0.000091 loss_xy: 0.567437 loss_wh: 0.623783 loss_iou: 2.511684 loss_obj: 3.314124 loss_cls: 0.949793 loss: 7.338743 eta: 5:16:15 batch_cost: 6.2481 data_cost: 0.0003 ips: 1.2804 images/s
[07/15 10:28:39] ppdet.engine INFO: Epoch: [1] [20/87] learning_rate: 0.000100 loss_xy: 0.583728 loss_wh: 0.708465 loss_iou: 2.704193 loss_obj: 3.461134 loss_cls: 1.127932 loss: 9.057523 eta: 5:20:59 batch_cost: 6.2270 data_cost: 0.0003 ips: 1.2847 images/s
[07/15 10:30:28] ppdet.engine INFO: Epoch: [1] [40/87] learning_rate: 0.000100 loss_xy: 0.576615 loss_wh: 0.655194 loss_iou: 2.566234 loss_obj: 2.921384 loss_cls: 1.010778 loss: 7.844104 eta: 5:16:43 batch_cost: 5.4392 data_cost: 0.0003 ips: 1.4708 images/s
[07/15 10:32:34] ppdet.engine INFO: Epoch: [1] [60/87] learning_rate: 0.000100 loss_xy: 0.583071 loss_wh: 0.726098 loss_iou: 2.730413 loss_obj: 3.053501 loss_cls: 0.991524 loss: 8.496977 eta: 5:19:40 batch_cost: 6.3128 data_cost: 0.0003 ips: 1.2673 images/s
[07/15 10:34:31] ppdet.engine INFO: Epoch: [1] [80/87] learning_rate: 0.000100 loss_xy: 0.606061 loss_wh: 0.652358 loss_iou: 2.841094 loss_obj: 3.237591 loss_cls: 1.084277 loss: 8.605825 eta: 5:18:16 batch_cost: 5.8318 data_cost: 0.0003 ips: 1.3718 images/s
[07/15 10:34:59] ppdet.utils.checkpoint INFO: Save checkpoint: output/yolov5s_CSPdarknet_roadsign
[07/15 10:35:00] ppdet.engine INFO: Eval iter: 0
[07/15 10:35:19] ppdet.engine INFO: Eval iter: 100
[07/15 10:35:33] ppdet.metrics.metrics INFO: Accumulating evaluatation results...
[07/15 10:35:33] ppdet.metrics.metrics INFO: mAP(0.50, integral) = 85.30%
[07/15 10:35:33] ppdet.engine INFO: Total sample number: 176, averge FPS: 5.151774310709877
[07/15 10:35:33] ppdet.engine INFO: Best test bbox ap is 0.858.
[07/15 10:35:46] ppdet.engine INFO: Epoch: [2] [ 0/87] learning_rate: 0.000100 loss_xy: 0.537015 loss_wh: 0.587401 loss_iou: 2.352699 loss_obj: 3.121367 loss_cls: 1.012583 loss: 7.857001 eta: 5:17:11 batch_cost: 5.8271 data_cost: 0.0003 ips: 1.3729 images/s
^C

!rm -rf output/
!zip -r code.zip ./*
Owner
BIT可达鸭
GitHub Repository
This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"

ICCV Workshop 2021 VTGAN This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"

Sharif Amit Kamran 25 Dec 08, 2022
Unofficial PyTorch implementation of SimCLR by Google Brain

Unofficial PyTorch implementation of SimCLR by Google Brain

Rishabh Anand 2 Oct 13, 2021
This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018

Learning-to-See-in-the-Dark This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018, by Chen Chen, Qifeng Chen, Jia Xu, and Vl

5.3k Jan 01, 2023
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

yobi byte 29 Oct 09, 2022
The official implementation code of "PlantStereo: A Stereo Matching Benchmark for Plant Surface Dense Reconstruction."

PlantStereo This is the official implementation code for the paper "PlantStereo: A Stereo Matching Benchmark for Plant Surface Dense Reconstruction".

Wang Qingyu 14 Nov 28, 2022
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

TorchMultimodal (Alpha Release) Introduction TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

Meta Research 663 Jan 06, 2023
Roadmap to becoming a machine learning engineer in 2020

Roadmap to becoming a machine learning engineer in 2020, inspired by web-developer-roadmap.

Chris Hoyean Song 1.7k Dec 29, 2022
Deep learning library featuring a higher-level API for TensorFlow.

TFLearn: Deep learning library featuring a higher-level API for TensorFlow. TFlearn is a modular and transparent deep learning library built on top of

TFLearn 9.6k Jan 02, 2023
Multi agent DDPG algorithm written in Python + Pytorch

Multi agent DDPG algorithm written in Python + Pytorch. It also includes a Jupyter notebook, Tennis.ipynb, as a showcase.

Rogier Wachters 2 Feb 26, 2022
【ACMMM 2021】DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning

DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning (ACMMM 2021) Overview We release the code of the DSANet (Dynamic S

Wenhao Wu 46 Dec 27, 2022
Transformer model implemented with Pytorch

transformer-pytorch Transformer model implemented with Pytorch Attention is all you need-[Paper] Architecture Self-Attention self_attention.py class

Mingu Kang 12 Sep 03, 2022
The openspoor package is intended to allow easy transformation between different geographical and topological systems commonly used in Dutch Railway

Openspoor The openspoor package is intended to allow easy transformation between different geographical and topological systems commonly used in Dutch

7 Aug 22, 2022
PyTorch implementation of Algorithm 1 of "On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models"

Code for On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models This repository will reproduce the main results from our pape

Mitch Hill 32 Nov 25, 2022
Python-kafka-reset-consumergroup-offset-example - Python Kafka reset consumergroup offset example

Python Kafka reset consumergroup offset example This is a simple example of how

Willi Carlsen 1 Feb 16, 2022
Code repository for the paper Computer Vision User Entity Behavior Analytics

Computer Vision User Entity Behavior Analytics Code repository for "Computer Vision User Entity Behavior Analytics" Code Description dataset.csv As di

Sameer Khanna 2 Aug 20, 2022
[SIGGRAPH 2021 Asia] DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning

DeepVecFont This is the official Pytorch implementation of the paper: Yizhi Wang and Zhouhui Lian. DeepVecFont: Synthesizing High-quality Vector Fonts

Yizhi Wang 146 Dec 18, 2022
Code for the paper: Hierarchical Reinforcement Learning With Timed Subgoals, published at NeurIPS 2021

Hierarchical reinforcement learning with Timed Subgoals (HiTS) This repository contains code for reproducing experiments from our paper "Hierarchical

Autonomous Learning Group 21 Dec 03, 2022
Object-aware Contrastive Learning for Debiased Scene Representation

Object-aware Contrastive Learning Official PyTorch implementation of "Object-aware Contrastive Learning for Debiased Scene Representation" by Sangwoo

43 Dec 14, 2022
Lightweight stereo matching network based on MobileNetV1 and MobileNetV2

MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching

Cognitive Systems Research Group 139 Nov 30, 2022
AITUS - An atomatic notr maker for CYTUS

AITUS an automatic note maker for CYTUS. 利用AI根据指定乐曲生成CYTUS游戏谱面。 效果展示：https://www

GradiusTwinbee 6 Feb 24, 2022