ImpactSynth / CBCT /Config.yml
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Add IMPACT-Synth training config (losses + optimizer) so the app is fine-tunable
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Trainer:
Model:
classpath: UNetPlusPlus.yml
UNetPlusPlus:
outputs_criterions:
Tanh:
targets_criterions:
CT:
criterions_loader:
MAE:
is_loss: true
schedulers: {Constant: {nb_step: 0, value: 1}}
group: 0
start: 0
stop: None
accumulation: false
reduction: mean
SAM_Perceptual:
is_loss: true
schedulers: {Constant: {nb_step: 0, value: 1}}
group: 0
start: 0
stop: None
accumulation: false
train: true
model_name: SAM2.1_Small.pt
weights: [1, 1, 1]
torch:nn:L1Loss:
size_average: None
reduce: None
reduction: mean
schedulers: {Constant: {nb_step: 0, value: 1}}
is_loss: true
group: 0
start: 0
stop: None
accumulation: false
CT;MASK:
criterions_loader:
MAE:
schedulers: {Constant: {nb_step: 0, value: 1}}
is_loss: false
group: 0
start: 0
stop: None
accumulation: false
reduction: mean
optimizer:
name: AdamW
lr: 0.001
betas: [0.9, 0.999]
eps: 1e-08
weight_decay: 0.001
amsgrad: false
maximize: false
foreach: None
capturable: false
differentiable: false
fused: None
schedulers:
StepLR:
step_size: 10
gamma: 0.75
last_epoch: -1
verbose: deprecated
nb_step: 0
Dataset:
groups_src:
MASK:
groups_dest:
MASK:
transforms: None
patch_transforms: None
is_input: false
CT:
groups_dest:
CT:
transforms:
Clip:
min_value: -1024
max_value: 3071
save_clip_min: true
save_clip_max: true
mask: None
Statistics: {}
Normalize:
lazy: true
channels: None
min_value: -1
max_value: 1
inverse: false
patch_transforms:
Normalize:
lazy: false
channels: None
min_value: -1
max_value: 1
inverse: false
is_input: false
CBCT_IMPACT:
groups_dest:
CBCT:
transforms:
Clip:
min_value: min
max_value: percentile:99.5
save_clip_min: false
save_clip_max: false
mask: None
Statistics: {}
Normalize:
lazy: true
channels: None
min_value: -1
max_value: 1
inverse: false
patch_transforms:
Normalize:
lazy: false
channels: None
min_value: -1
max_value: 1
inverse: false
is_input: true
augmentations:
DataAugmentation_0:
data_augmentations:
Flip:
f_prob:
- 0
- 0.5
- 0.5
prob: 1
nb: 1
Patch:
patch_size:
- 1
- 320
- 320
overlap: None
mask: None
pad_value: -1
extend_slice: 4
subset: None
shuffle: true
filter: None
dataset_filenames:
- ./Dataset/:a:mha
inline_augmentations: true
use_cache: true
batch_size: 32
validation: None
train_name: FT_0
manual_seed: 32
epochs: 100
it_validation: 2500
autocast: false
gradient_checkpoints: None
gpu_checkpoints: None
ema_decay: 0
data_log:
- CT/IMAGES/5
- CBCT/IMAGES/5
- Tanh/IMAGES/5
save_checkpoint_mode: ALL
EarlyStopping:
monitor: []
patience: 30
min_delta: 0.0
mode: min