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- import paddlex as pdx
- from paddlex import transforms as T
- # 定义训练和验证时的transforms
- # API说明:https://github.com/PaddlePaddle/PaddleX/blob/release/2.0-rc/paddlex/cv/transforms/operators.py
- train_transforms = T.Compose([
- T.MixupImage(mixup_epoch=250), T.RandomDistort(),
- T.RandomExpand(im_padding_value=[123.675, 116.28, 103.53]), T.RandomCrop(),
- T.RandomHorizontalFlip(), T.BatchRandomResize(
- target_sizes=[320, 352, 384, 416, 448, 480, 512, 544, 576, 608],
- interp='RANDOM'), T.Normalize(
- mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
- ])
- eval_transforms = T.Compose([
- T.Resize(
- 608, interp='CUBIC'), T.Normalize(
- mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
- ])
- # 定义训练和验证所用的数据集
- # API说明:https://github.com/PaddlePaddle/PaddleX/blob/release/2.0-rc/paddlex/cv/datasets/voc.py#L29
- train_dataset = pdx.datasets.VOCDetection(
- data_dir='dataset',
- file_list='dataset/train_list.txt',
- label_list='dataset/labels.txt',
- transforms=train_transforms,
- shuffle=True,
- num_worker=0)
- eval_dataset = pdx.datasets.VOCDetection(
- data_dir='dataset',
- file_list='dataset/val_list.txt',
- label_list='dataset/labels.txt',
- transforms=eval_transforms,
- shuffle=False,
- num_worker=0)
- # 初始化模型,并进行训练
- # 可使用VisualDL查看训练指标,参考https://github.com/PaddlePaddle/PaddleX/tree/release/2.0-rc/tutorials/train#visualdl可视化训练指标
- num_classes = len(train_dataset.labels)
- model = pdx.models.YOLOv3(num_classes=num_classes, backbone='DarkNet53')
- # API说明:https://github.com/PaddlePaddle/PaddleX/blob/release/2.0-rc/paddlex/cv/models/detector.py#L155
- # 各参数介绍与调整说明:https://paddlex.readthedocs.io/zh_CN/develop/appendix/parameters.html
- model.train(
- num_epochs=270,
- train_dataset=train_dataset,
- train_batch_size=2,
- eval_dataset=eval_dataset,
- learning_rate=0.001 / 8,
- warmup_steps=1000,
- warmup_start_lr=0.0,
- save_interval_epochs=5,
- lr_decay_epochs=[216, 243],
- save_dir='output/yolov3_darknet53')
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