基于Paddlepaddle复现yolov5,支持PaddleDetection接口

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
TFOD-MASKRCNN - Tensorflow MaskRCNN With Python

Tensorflow- MaskRCNN Steps git clone https://github.com/amalaj7/TFOD-MASKRCNN.gi

Amal Ajay 2 Jan 18, 2022
Unofficial PyTorch Implementation of Multi-Singer

Multi-Singer Unofficial PyTorch Implementation of Multi-Singer: Fast Multi-Singer Singing Voice Vocoder With A Large-Scale Corpus. Requirements See re

SunMail-hub 123 Dec 28, 2022
Learning to Initialize Neural Networks for Stable and Efficient Training

GradInit This repository hosts the code for experiments in the paper, GradInit: Learning to Initialize Neural Networks for Stable and Efficient Traini

Chen Zhu 124 Dec 30, 2022
graph-theoretic framework for robust pairwise data association

CLIPPER: A Graph-Theoretic Framework for Robust Data Association Data association is a fundamental problem in robotics and autonomy. CLIPPER provides

MIT Aerospace Controls Laboratory 118 Dec 28, 2022
Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.

Monk - A computer vision toolkit for everyone Why use Monk Issue: Want to begin learning computer vision Solution: Start with Monk's hands-on study ro

Tessellate Imaging 507 Dec 04, 2022
This is the implementation of GGHL (A General Gaussian Heatmap Labeling for Arbitrary-Oriented Object Detection)

GGHL: A General Gaussian Heatmap Labeling for Arbitrary-Oriented Object Detection This is the implementation of GGHL 👋 👋 👋 [Arxiv] [Google Drive][B

551 Dec 31, 2022
Expressive Body Capture: 3D Hands, Face, and Body from a Single Image

Expressive Body Capture: 3D Hands, Face, and Body from a Single Image [Project Page] [Paper] [Supp. Mat.] Table of Contents License Description Fittin

Vassilis Choutas 1.3k Jan 07, 2023
3D Avatar Lip Syncronization from speech (JALI based face-rigging)

visemenet-inference Inference Demo of "VisemeNet-tensorflow" VisemeNet is an audio-driven animator centric speech animation driving a JALI or standard

Junhwan Jang 17 Dec 20, 2022
code for paper"A High-precision Semantic Segmentation Method Combining Adversarial Learning and Attention Mechanism"

PyTorch implementation of UAGAN(U-net Attention Generative Adversarial Networks) This repository contains the source code for the paper "A High-precis

Tong 8 Apr 25, 2022
Python scripts for performing stereo depth estimation using the MobileStereoNet model in Tensorflow Lite.

TFLite-MobileStereoNet Python scripts for performing stereo depth estimation using the MobileStereoNet model in Tensorflow Lite. Stereo depth estimati

Ibai Gorordo 4 Feb 14, 2022
Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.

The goal is to classify different birds species based on their songs/calls. Spectrograms have been extracted from the audio samples and used as features for classification.

Aditya Dutt 9 Dec 27, 2022
Open source annotation tool for machine learning practitioners.

doccano doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequ

7.1k Jan 01, 2023
TensorFlow 2 AI/ML library wrapper for openFrameworks

ofxTensorFlow2 This is an openFrameworks addon for the TensorFlow 2 ML (Machine Learning) library

Center for Art and Media Karlsruhe 96 Dec 31, 2022
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

Riskfolio-Lib Quantitative Strategic Asset Allocation, Easy for Everyone. Description Riskfolio-Lib is a library for making quantitative strategic ass

Riskfolio 1.7k Jan 07, 2023
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat

Hanzhe Hu 99 Dec 12, 2022
iris - Open Source Photos Platform Powered by PyTorch

Open Source Photos Platform Powered by PyTorch. Submission for PyTorch Annual Hackathon 2021.

Omkar Prabhu 137 Sep 10, 2022
Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

NBFNet: Neural Bellman-Ford Networks This is the official codebase of the paper Neural Bellman-Ford Networks: A General Graph Neural Network Framework

MilaGraph 136 Dec 21, 2022
This is the official repository for our paper: ''Pruning Self-attentions into Convolutional Layers in Single Path''.

Pruning Self-attentions into Convolutional Layers in Single Path This is the official repository for our paper: Pruning Self-attentions into Convoluti

Zhuang AI Group 77 Dec 26, 2022
Art Project "Schrödinger's Game of Life"

Repo of the project "Team Creative Quantum AI: Schrödinger's Game of Life" Installation new conda env: conda create --name qcml python=3.8 conda activ

ℍ◮ℕℕ◭ℍ ℝ∈ᛔ∈ℝ 2 Sep 15, 2022
A repo for Causal Imitation Learning under Temporally Correlated Noise

CausIL A repo for Causal Imitation Learning under Temporally Correlated Noise. Running Experiments To re-train an expert, run: python experts/train_ex

Gokul Swamy 5 Nov 01, 2022