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.
93 lines
2.9 KiB
93 lines
2.9 KiB
#!/usr/bin/env python |
|
|
|
# 图像分割模型HRNet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 |
|
|
|
# 数据集存放目录 |
|
DATA_DIR = './data/rsseg/' |
|
# 训练集`file_list`文件路径 |
|
TRAIN_FILE_LIST_PATH = './data/rsseg/train.txt' |
|
# 验证集`file_list`文件路径 |
|
EVAL_FILE_LIST_PATH = './data/rsseg/val.txt' |
|
# 数据集类别信息文件路径 |
|
LABEL_LIST_PATH = './data/rsseg/labels.txt' |
|
# 实验目录，保存输出的模型权重和结果 |
|
EXP_DIR = './output/hrnet/' |
|
|
|
# 影像波段数量 |
|
NUM_BANDS = 10 |
|
|
|
# 下载和解压多光谱地块分类数据集 |
|
pdrs.utils.download_and_decompress( |
|
'https://paddlers.bj.bcebos.com/datasets/rsseg.zip', path='./data/') |
|
|
|
# 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/PaddlePaddle/PaddleRS/blob/develop/docs/apis/data.md |
|
train_transforms = T.Compose([ |
|
# 读取影像 |
|
T.DecodeImg(), |
|
# 将影像缩放到512x512大小 |
|
T.Resize(target_size=512), |
|
# 以50%的概率实施随机水平翻转 |
|
T.RandomHorizontalFlip(prob=0.5), |
|
# 将数据归一化到[-1,1] |
|
T.Normalize( |
|
mean=[0.5] * NUM_BANDS, std=[0.5] * NUM_BANDS), |
|
T.ArrangeSegmenter('train') |
|
]) |
|
|
|
eval_transforms = T.Compose([ |
|
T.DecodeImg(), |
|
T.Resize(target_size=512), |
|
# 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] * NUM_BANDS, std=[0.5] * NUM_BANDS), |
|
T.ReloadMask(), |
|
T.ArrangeSegmenter('eval') |
|
]) |
|
|
|
# 分别构建训练和验证所用的数据集 |
|
train_dataset = pdrs.datasets.SegDataset( |
|
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.SegDataset( |
|
data_dir=DATA_DIR, |
|
file_list=EVAL_FILE_LIST_PATH, |
|
label_list=LABEL_LIST_PATH, |
|
transforms=eval_transforms, |
|
num_workers=0, |
|
shuffle=False) |
|
|
|
# 构建HRNet模型 |
|
# 目前已支持的模型请参考：https://github.com/PaddlePaddle/PaddleRS/blob/develop/docs/intro/model_zoo.md |
|
# 模型输入参数请参考：https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/tasks/segmenter.py |
|
model = pdrs.tasks.seg.HRNet( |
|
in_channels=NUM_BANDS, num_classes=len(train_dataset.labels)) |
|
|
|
# 执行模型训练 |
|
model.train( |
|
num_epochs=10, |
|
train_dataset=train_dataset, |
|
train_batch_size=4, |
|
eval_dataset=eval_dataset, |
|
save_interval_epochs=5, |
|
# 每多少次迭代记录一次日志 |
|
log_interval_steps=4, |
|
save_dir=EXP_DIR, |
|
# 初始学习率大小 |
|
learning_rate=0.001, |
|
# 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)
|
|
|