this is an example for detecting facemask by PaddleX.
基于PaddleX实现目标检测。实现以下任务：
- 配置数据集（数据集选择、数据处理）
- 配置模型并训练
本项目使用的数据集是：[AI训练营]目标检测数据集合集，中的口罩识别 。
该数据集位于：data/data103743/objDataset.zip
# 解压数据集（解压一次即可，请勿重复解压）
!unzip -oq /home/aistudio/data/data103743/objDataset.zip解压完成后，左侧文件夹处会多一个名为objDataset的文件夹，该文件夹下有5个子文件夹：
- barricade——Gazebo锥桶检测
- facemask——口罩检测
- fire——火焰检测
- MidAutumn——中秋元素检测
- roadsign_voc——交通路标检测
每个子文件夹下有2个文件夹，分别存放着图像（JPEGImages）和标注文件（Annotations），如下所示：
# 查看数据集文件结构
!tree objDataset -L 2objDataset
├── barricade
│ ├── Annotations
│ └── JPEGImages
├── facemask
│ ├── Annotations
│ └── JPEGImages
├── fire
│ ├── Annotations
│ └── JPEGImages
├── MidAutumn
│ ├── Annotations
│ └── JPEGImages
└── roadsign_voc
├── Annotations
└── JPEGImages
15 directories, 0 files
本基线系统使用的数据格式是PascalVOC格式，开发者基于PaddleX开发目标检测模型时，无需对数据格式进行转换，开箱即用。
但为了进行训练，还需要将数据划分为训练集、验证集和测试集。划分之前首先需要安装PaddleX。
# 安装PaddleX
!pip install paddlexLooking in indexes: https://mirror.baidu.com/pypi/simple/
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使用如下命令即可将数据划分为70%训练集，20%验证集和10%的测试集。
# 划分数据集
!paddlex --split_dataset --format VOC --dataset_dir objDataset/facemask --val_value 0.2 --test_value 0.1/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/setuptools/depends.py:2: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
Dataset Split Done.�[0m
�[0mTrain samples: 598�[0m
�[0mEval samples: 170�[0m
�[0mTest samples: 85�[0m
�[0mSplit files saved in objDataset/facemask�[0m
�[0m�[0m
划分完成后，该数据集下会生成labels.txt, train_list.txt, val_list.txt和test_list.txt，分别存储类别信息，训练样本列表，验证样本列表，测试样本列表。如下图所示：
在这里，你需要将path to dataset部分(objDataset/facemask)替换成你选择的数据集路径。在左侧文件夹处，将鼠标放到你想选择的数据集文件夹上，会出现三个图标，第一个图标表示复制该文件夹路径，点击即可获得该文件夹路径，用这个路径替换path to dataset即可。
在训练模型之前，对目标检测任务的数据进行操作，从而提升模型效果。可用于数据处理的API有：
- Normalize：对图像进行归一化
- ResizeByShort：根据图像的短边调整图像大小
- RandomHorizontalFlip：以一定的概率对图像进行随机水平翻转
- RandomDistort：以一定的概率对图像进行随机像素内容变换
更多关于数据处理的API及使用说明可查看文档： https://paddlex.readthedocs.io/zh_CN/release-1.3/apis/transforms/det_transforms.html
from paddlex.det import transforms
# 定义训练和验证时的transforms
# API说明 https://paddlex.readthedocs.io/zh_CN/develop/apis/transforms/det_transforms.html
train_transforms = transforms.Compose([
# 此处需要补充图像预处理代码
transforms.Normalize(),
])
eval_transforms = transforms.Compose([
# 此处需要补充图像预处理代码
transforms.Normalize(),
])读取PascalVOC格式的检测数据集，并对样本进行相应的处理。
import paddlex as pdx
# 定义训练和验证所用的数据集
# API说明：https://paddlex.readthedocs.io/zh_CN/develop/apis/datasets.html#paddlex-datasets-vocdetection
train_dataset = pdx.datasets.VOCDetection(
data_dir='objDataset/facemask',
file_list='objDataset/facemask/train_list.txt',
label_list='objDataset/facemask/labels.txt',
transforms=train_transforms,
shuffle=True)
eval_dataset = pdx.datasets.VOCDetection(
data_dir='objDataset/facemask',
file_list='objDataset/facemask/val_list.txt',
label_list='objDataset/facemask/labels.txt',
transforms=eval_transforms)/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/matplotlib/__init__.py:107: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated, and in 3.8 it will stop working
from collections import MutableMapping
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/matplotlib/rcsetup.py:20: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated, and in 3.8 it will stop working
from collections import Iterable, Mapping
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/matplotlib/colors.py:53: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated, and in 3.8 it will stop working
from collections import Sized
2021-08-12 10:41:37 [INFO] Starting to read file list from dataset...
2021-08-12 10:41:39 [INFO] 598 samples in file objDataset/facemask/train_list.txt
creating index...
index created!
2021-08-12 10:41:39 [INFO] Starting to read file list from dataset...
2021-08-12 10:41:40 [INFO] 170 samples in file objDataset/facemask/val_list.txt
creating index...
index created!
需要注意的是：
- data_dir (str): 数据集所在的目录路径。
- file_list (str): 描述数据集图片文件和对应标注文件的文件路径（文本内每行路径为相对data_dir的相对路径）。
- label_list (str): 描述数据集包含的类别信息文件路径。
需要将第二步数据准备时生成的labels.txt, train_list.txt, val_list.txt和test_list.txt配置到以上变量中，如下图所示：
PaddleX目前提供了FasterRCNN和YOLOv3两种检测结构，多种backbone模型。本基线系统以骨干网络为MobileNetV1的YOLOv3算法为例。
# 初始化模型
# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#paddlex-det-yolov3
# 此处需要补充目标检测模型代码
model = pdx.det.YOLOv3(num_classes=len(train_dataset.labels), backbone='MobileNetV1')# 模型训练
# API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#id1
# 各参数介绍与调整说明：https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
# 此处需要补充模型训练参数
model.train(
num_epochs=200,
train_dataset=train_dataset,
train_batch_size=8,
eval_dataset=eval_dataset,
learning_rate=0.000125,
lr_decay_epochs=[210, 240],
save_dir='output/yolov3_mobilenetv1')2021-08-12 10:42:30 [INFO] Downloading MobileNetV1_pretrained.tar from http://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV1_pretrained.tar
0%| | 0/16760 [00:00<?, ?KB/s]100%|██████████| 16760/16760 [00:00<00:00, 63984.23KB/s]
2021-08-12 10:42:30 [INFO] Decompressing output/yolov3_mobilenetv1/pretrain/MobileNetV1_pretrained.tar...
2021-08-12 10:42:31 [INFO] Load pretrain weights from output/yolov3_mobilenetv1/pretrain/MobileNetV1_pretrained.
2021-08-12 10:42:31 [INFO] There are 135 varaibles in output/yolov3_mobilenetv1/pretrain/MobileNetV1_pretrained are loaded.