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MobileNetV3-SSD for object detection and implementation in PyTorch

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MobileNetV3-SSD

MobileNetV3-SSD implementation in PyTorch

关于第二个版本请移步 https://github.com/shaoshengsong/MobileNetV3-SSD-Compact-Version 有测试结果 希望尝试新技术请到这里 https://github.com/shaoshengsong/quarkdet 一个轻量级的目标检测包括多种模型 目的 Object Detection 应用于目标检测

环境

操作系统: Ubuntu18.04

Python: 3.6

PyTorch: 1.1.0

使用MobileNetV3-SSD实现目标检测

Support Export ONNX

代码参考(严重参考以下代码)

一 SSD部分

A PyTorch Implementation of Single Shot MultiBox Detector

二 MobileNetV3 部分

1 mobilenetv3 with pytorch,provide pre-train model

2 MobileNetV3 in pytorch and ImageNet pretrained models

3Implementing Searching for MobileNetV3 paper using Pytorch

4 MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas like CoordConv. no discernible latency cost.

针对4我这里没有做MobileNetV1, MobileNetV2等等代码兼容,只有MobileNetV3可用

下载数据 本例是以蛋糕和面包为例,原因是数据量小 所有类别总大小是561G,蛋糕和面包是3.2G

python3 open_images_downloader.py --root /media/santiago/a/data/open_images --class_names "Cake,Bread" --num_workers 20

训练过程

首次训练

python3 train_ssd.py --dataset_type open_images --datasets /media/santiago/data/open_images --net mb3-ssd-lite --scheduler cosine --lr 0.01 --t_max 100 --validation_epochs 5 --num_epochs 100 --base_net_lr 0.001 --batch_size 5

预加载之前训练的模型

python3 train_ssd.py --dataset_type open_images --datasets /media/santiago/data/open_images --net mb3-ssd-lite --pretrained_ssd models/mb3-ssd-lite-Epoch-99-Loss-2.5194434596402613.pth --scheduler cosine --lr 0.01 --t_max 100 --validation_epochs 5 --num_epochs 200 --base_net_lr 0.001 --batch_size 5

测试一张图片

python run_ssd_example.py mb3-ssd-lite models/mb3-ssd-lite-Epoch-99-Loss-2.5194434596402613.pth models/open-images-model-labels.txt /home/santiago/picture/test.jpg

视频检测

python3 run_ssd_live_demo.py mb3-ssd-lite models/mb3-ssd-lite-Epoch-99-Loss-2.5194434596402613.pth models/open-images-model-labels.txt

Cake and Bread Pretrained model

链接: https://pan.baidu.com/s/1byY1eJk3Hm3CTp-29KirxA

提取码: qxwv

VOC Dataset Pretrained model

链接: https://pan.baidu.com/s/1yt_IRY0RcgSxB-YwywoHuA

提取码: 2sta

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