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dygraph/faster_rcnn_r50_fpn.py

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-import paddlex as pdx
-from paddlex import transforms as T
-
-# 下载和解压昆虫检测数据集
-dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
-pdx.utils.download_and_decompress(dataset, path='./')
-
-# 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.RandomResizeByShort(
-        short_sizes=[640, 672, 704, 736, 768, 800],
-        max_size=1333,
-        interp='CUBIC'), T.RandomHorizontalFlip(), T.Normalize(
-            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
-])
-
-eval_transforms = T.Compose([
-    T.ResizeByShort(
-        short_size=800, max_size=1333, 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='insect_det',
-    file_list='insect_det/train_list.txt',
-    label_list='insect_det/labels.txt',
-    transforms=train_transforms,
-    shuffle=True)
-
-eval_dataset = pdx.datasets.VOCDetection(
-    data_dir='insect_det',
-    file_list='insect_det/val_list.txt',
-    label_list='insect_det/labels.txt',
-    transforms=eval_transforms,
-    shuffle=False)
-
-# 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.FasterRCNN(
-    num_classes=num_classes, backbone='ResNet50', with_fpn=True)
-
-# 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=12,
-    train_dataset=train_dataset,
-    train_batch_size=2,
-    eval_dataset=eval_dataset,
-    learning_rate=0.0025,
-    lr_decay_epochs=[8, 11],
-    warmup_steps=500,
-    warmup_start_lr=0.00025,
-    save_dir='output/faster_rcnn_r50_fpn',
-    use_vdl=True)