roi-segresnet-2d / config.yaml
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# ROI — 2D lung foreground segmentation.
# Reproduces the bundled checkpoint at checkpoints/roi/best.pth
# (val Dice = 0.96 on the unified split).
task: roi
data:
data_root: ${DATA_ROOT} # contains ct_2d/ and roi_sem_seg_2d/
split_json: data/splits/unified.json
preprocessing:
target_size: [256, 256]
model:
name: segresnet
spatial_dims: 2
in_channels: 1
out_channels: 1 # sigmoid
init_filters: 16
blocks_down: [1, 2, 2, 4, 4]
blocks_up: [1, 1, 1, 1]
dropout_prob: 0.1
training:
epochs: 100
batch_size: 16
samples_per_epoch: 20000 # subsample ~1/24 of ~475k slices
lr: 1.0e-3
weight_decay: 1.0e-5
val_interval: 1
device: cuda
amp: true
amp_dtype: bfloat16
seed: 42
scheduler:
T_max: 100
eta_min: 1.0e-6
checkpoints:
dir: checkpoints/roi
save_every: 10
logging:
dir: runs/roi