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dataloader.yml
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dataloader.yml
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train_dataloader:
dataset:
transforms:
ops:
- {type: RandomPhotometricDistort, p: 0.5}
- {type: RandomZoomOut, fill: 0}
- {type: RandomIoUCrop, p: 0.8}
- {type: SanitizeBoundingBoxes, min_size: 1}
- {type: RandomHorizontalFlip}
- {type: Resize, size: [640, 640], }
- {type: SanitizeBoundingBoxes, min_size: 1}
- {type: ConvertPILImage, dtype: 'float32', scale: True}
- {type: ConvertBoxes, fmt: 'cxcywh', normalize: True}
policy:
name: stop_epoch
epoch: 72 # epoch in [71, ~) stop `ops`
ops: ['Mosaic', 'RandomPhotometricDistort', 'RandomZoomOut', 'RandomIoUCrop']
collate_fn:
type: BatchImageCollateFunction
base_size: 640
base_size_repeat: 3
stop_epoch: 72 # epoch in [72, ~) stop `multiscales`
shuffle: True
total_batch_size: 32 # total batch size equals to 32 (4 * 8)
num_workers: 4
val_dataloader:
dataset:
transforms:
ops:
- {type: Resize, size: [640, 640], }
- {type: ConvertPILImage, dtype: 'float32', scale: True}
shuffle: False
total_batch_size: 64
num_workers: 4