gpu_symbol / configs /base /deim.yml
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# Dense O2O
train_dataloader:
dataset:
transforms:
ops:
- {type: Mosaic, output_size: 320, rotation_range: 10, translation_range: [0.1, 0.1], scaling_range: [0.5, 1.5],
probability: 1.0, fill_value: 0, use_cache: True, max_cached_images: 50, random_pop: True}
- {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:
epoch: [4, 29, 50] # list
ops: ['Mosaic', 'RandomPhotometricDistort', 'RandomZoomOut', 'RandomIoUCrop']
mosaic_prob: 0.5
collate_fn:
mixup_prob: 0.5
mixup_epochs: [4, 29]
stop_epoch: 50 # epoch in [72, ~) stop `multiscales`
# Unfreezing BN
HGNetv2:
freeze_at: -1 # 0 default
freeze_norm: False # True default
# Activation
DFINETransformer:
activation: silu
mlp_act: silu
## Our LR-Scheduler
lrsheduler: flatcosine
lr_gamma: 0.5
warmup_iter: 2000
flat_epoch: 29 # 4 + epoch // 2, e.g., 40 = 4 + 72 / 2
no_aug_epoch: 8
## Our Loss
DEIMCriterion:
weight_dict: {loss_mal: 1, loss_bbox: 5, loss_giou: 2, loss_fgl: 0.15, loss_ddf: 1.5}
losses: ['mal', 'boxes', 'local']
gamma: 1.5