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- # coding:utf-8
- import os
- # 选择使用0号卡
- os.environ['CUDA_VISIBLE_DEVICES'] = '0'
- import paddlex as pdx
- from paddlex import transforms as T
- # 定义训练和验证时的transforms
- train_transforms = T.Compose([
- T.BatchRandomResize(
- target_sizes=[
- 320, 352, 384, 416, 448, 480, 512, 544, 576, 608, 640, 672, 704,
- 736, 768
- ],
- interp='RANDOM'), T.Normalize(
- mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
- ])
- eval_transforms = T.Compose([
- T.Resize(
- target_size=640, 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
- train_dataset = pdx.datasets.VOCDetection(
- data_dir='/home/aistudio/dataset',
- file_list='/home/aistudio/dataset/train_list.txt',
- label_list='/home/aistudio/dataset/labels.txt',
- transforms=train_transforms,
- shuffle=True)
- eval_dataset = pdx.datasets.VOCDetection(
- data_dir='/home/aistudio/dataset',
- file_list='/home/aistudio/dataset/val_list.txt',
- label_list='/home/aistudio/dataset/labels.txt',
- transforms=eval_transforms,
- shuffle=False)
- # 初始化模型，并进行训练
- # API说明: https://paddlex.readthedocs.io/zh_CN/develop/apis/models/detection.html#paddlex-det-yolov3
- num_classes = len(train_dataset.labels)
- model = pdx.det.PPYOLOv2(num_classes=num_classes, backbone='ResNet50_vd_dcn')
- model.train(
- num_epochs=270,
- train_dataset=train_dataset,
- train_batch_size=8,
- eval_dataset=eval_dataset,
- learning_rate=0.005 / 12,
- warmup_steps=1000,
- warmup_start_lr=0.0,
- lr_decay_epochs=[105, 135, 150],
- save_interval_epochs=5,
- save_dir='output/ppyolov2_r50vd_dcn')
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