You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
87 lines
3.0 KiB
87 lines
3.0 KiB
#!/usr/bin/env python |
|
|
|
# 场景分类模型ResNet50-vd训练示例脚本 |
|
# 执行此脚本前，请确认已正确安装PaddleRS库 |
|
|
|
import paddlers as pdrs |
|
from paddlers import transforms as T |
|
|
|
# 下载文件存放目录 |
|
DOWNLOAD_DIR = './data/ucmerced/' |
|
# 数据集存放目录 |
|
DATA_DIR = './data/ucmerced/' |
|
# 训练集`file_list`文件路径 |
|
TRAIN_FILE_LIST_PATH = './data/ucmerced/train.txt' |
|
# 验证集`file_list`文件路径 |
|
EVAL_FILE_LIST_PATH = './data/ucmerced/val.txt' |
|
# 数据集类别信息文件路径 |
|
LABEL_LIST_PATH = './data/ucmerced/labels.txt' |
|
# 实验目录，保存输出的模型权重和结果 |
|
EXP_DIR = './output/resnet50_vd/' |
|
|
|
# 下载和解压UC Merced数据集 |
|
ucmerced_dataset = 'http://weegee.vision.ucmerced.edu/datasets/UCMerced_LandUse.zip' |
|
pdrs.utils.download_and_decompress(ucmerced_dataset, path=DOWNLOAD_DIR) |
|
|
|
# 定义训练和验证时使用的数据变换（数据增强、预处理等） |
|
# 使用Compose组合多种变换方式。Compose中包含的变换将按顺序串行执行 |
|
# API说明：https://github.com/PaddleCV-SIG/PaddleRS/blob/develop/docs/apis/transforms.md |
|
train_transforms = T.Compose([ |
|
# 将影像缩放到256x256大小 |
|
T.Resize(target_size=256), |
|
# 以50%的概率实施随机水平翻转 |
|
T.RandomHorizontalFlip(prob=0.5), |
|
# 以50%的概率实施随机垂直翻转 |
|
T.RandomVerticalFlip(prob=0.5), |
|
# 将数据归一化到[-1,1] |
|
T.Normalize( |
|
mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]), |
|
]) |
|
|
|
eval_transforms = T.Compose([ |
|
T.Resize(target_size=256), |
|
# 验证阶段与训练阶段的数据归一化方式必须相同 |
|
T.Normalize( |
|
mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]), |
|
]) |
|
|
|
# 分别构建训练和验证所用的数据集 |
|
train_dataset = pdrs.datasets.ClasDataset( |
|
data_dir=DATA_DIR, |
|
file_list=TRAIN_FILE_LIST_PATH, |
|
label_list=LABEL_LIST_PATH, |
|
transforms=train_transforms, |
|
num_workers=0, |
|
shuffle=True) |
|
|
|
eval_dataset = pdrs.datasets.ClasDataset( |
|
data_dir=DATA_DIR, |
|
file_list=EVAL_FILE_LIST_PATH, |
|
label_list=LABEL_LIST_PATH, |
|
transforms=eval_transforms, |
|
num_workers=0, |
|
shuffle=False) |
|
|
|
# 使用默认参数构建ResNet50-vd模型 |
|
# 目前已支持的模型请参考：https://github.com/PaddleCV-SIG/PaddleRS/blob/develop/docs/apis/model_zoo.md |
|
# 模型输入参数请参考：https://github.com/PaddleCV-SIG/PaddleRS/blob/develop/paddlers/tasks/classifier.py |
|
model = pdrs.tasks.ResNet50_vd(num_classes=len(train_dataset.labels)) |
|
|
|
# 执行模型训练 |
|
model.train( |
|
num_epochs=2, |
|
train_dataset=train_dataset, |
|
train_batch_size=16, |
|
eval_dataset=eval_dataset, |
|
save_interval_epochs=1, |
|
# 每多少次迭代记录一次日志 |
|
log_interval_steps=50, |
|
save_dir=EXP_DIR, |
|
# 初始学习率大小 |
|
learning_rate=0.01, |
|
# 是否使用early stopping策略，当精度不再改善时提前终止训练 |
|
early_stop=False, |
|
# 是否启用VisualDL日志功能 |
|
use_vdl=True, |
|
# 指定从某个检查点继续训练 |
|
resume_checkpoint=None)
|
|
|