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cli-help-train.txt
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cli-help-train.txt
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usage: train.py [-h] [--debug] [--checkpoint CHECKPOINT] [--dilation DILATION]
[--dilation-end DILATION_END] [--basenet BASENET]
[--headnets HEADNETS [HEADNETS ...]] [--no-pretrain]
[--two-scale] [--head-dropout HEAD_DROPOUT]
[--head-quad HEAD_QUAD] [--head-kernel-size HEAD_KERNEL_SIZE]
[--head-padding HEAD_PADDING] [--head-dilation HEAD_DILATION]
[--lambdas LAMBDAS [LAMBDAS ...]] [--r-smooth R_SMOOTH]
[--regression-loss {smoothl1,smootherl1,l1,laplace}]
[--background-weight BACKGROUND_WEIGHT]
[--paf-multiplicity-correction]
[--paf-independence-scale PAF_INDEPENDENCE_SCALE]
[--paf-min-size PAF_MIN_SIZE] [--paf-fixed-size]
[--paf-aspect-ratio PAF_ASPECT_RATIO]
[--pif-side-length PIF_SIDE_LENGTH] [--momentum MOMENTUM]
[--beta2 BETA2] [--adam-eps ADAM_EPS] [--no-nesterov]
[--weight-decay WEIGHT_DECAY] [--adam] [--amsgrad] [--lr LR]
[--lr-decay LR_DECAY [LR_DECAY ...]]
[--lr-burn-in-epochs LR_BURN_IN_EPOCHS]
[--lr-burn-in-factor LR_BURN_IN_FACTOR] [--lr-gamma LR_GAMMA]
[--train-annotations TRAIN_ANNOTATIONS]
[--train-image-dir TRAIN_IMAGE_DIR]
[--val-annotations VAL_ANNOTATIONS]
[--val-image-dir VAL_IMAGE_DIR] [--pre-n-images PRE_N_IMAGES]
[--n-images N_IMAGES] [--duplicate-data DUPLICATE_DATA]
[--pre-duplicate-data PRE_DUPLICATE_DATA]
[--loader-workers LOADER_WORKERS] [--batch-size BATCH_SIZE]
[-o OUTPUT] [--stride-apply STRIDE_APPLY] [--epochs EPOCHS]
[--freeze-base FREEZE_BASE] [--pre-lr PRE_LR]
[--rescale-images RESCALE_IMAGES] [--orientation-invariant]
[--update-batchnorm-runningstatistics]
[--square-edge SQUARE_EDGE] [--ema EMA]
[--debug-without-plots] [--profile PROFILE] [--disable-cuda]
[--no-augmentation]
Train a pifpaf network.
optional arguments:
-h, --help show this help message and exit
-o OUTPUT, --output OUTPUT
output file (default: None)
--stride-apply STRIDE_APPLY
apply and reset gradients every n batches (default: 1)
--epochs EPOCHS number of epochs to train (default: 75)
--freeze-base FREEZE_BASE
number of epochs to train with frozen base (default:
0)
--pre-lr PRE_LR pre learning rate (default: 0.0001)
--rescale-images RESCALE_IMAGES
overall image rescale factor (default: 1.0)
--orientation-invariant
augment with random orientations (default: False)
--update-batchnorm-runningstatistics
update batch norm running statistics (default: False)
--square-edge SQUARE_EDGE
square edge of input images (default: 401)
--ema EMA ema decay constant (default: 0.001)
--debug-without-plots
enable debug but dont plot (default: False)
--profile PROFILE enables profiling. specify path for chrome tracing
file (default: None)
--disable-cuda disable CUDA (default: False)
--no-augmentation do not apply data augmentation (default: True)
logging:
--debug print debug messages (default: False)
network configuration:
--checkpoint CHECKPOINT
Load a model from a checkpoint. Use "resnet50",
"resnet101" or "resnet152" for pretrained OpenPifPaf
models. (default: None)
--dilation DILATION apply atrous (default: None)
--dilation-end DILATION_END
apply atrous (default: None)
--basenet BASENET base network, e.g. resnet50block5 (default: None)
--headnets HEADNETS [HEADNETS ...]
head networks (default: ['pif', 'paf'])
--no-pretrain create model without ImageNet pretraining (default:
True)
--two-scale two scale (default: False)
head:
--head-dropout HEAD_DROPOUT
zeroing probability of feature in head input (default:
0.0)
--head-quad HEAD_QUAD
number of times to apply quad (subpixel conv) to heads
(default: 0)
--head-kernel-size HEAD_KERNEL_SIZE
--head-padding HEAD_PADDING
--head-dilation HEAD_DILATION
losses:
--lambdas LAMBDAS [LAMBDAS ...]
prefactor for head losses (default: [30.0, 2.0, 2.0,
50.0, 3.0, 3.0])
--r-smooth R_SMOOTH r_{smooth} for SmoothL1 regressions (default: 0.0)
--regression-loss {smoothl1,smootherl1,l1,laplace}
type of regression loss (default: laplace)
--background-weight BACKGROUND_WEIGHT
BCE weight of background (default: 1.0)
--paf-multiplicity-correction
use multiplicity correction for PAF loss (default:
False)
--paf-independence-scale PAF_INDEPENDENCE_SCALE
linear length scale of independence for PAF regression
(default: 3.0)
paf encoder:
--paf-min-size PAF_MIN_SIZE
min side length of the PAF field (default: 3)
--paf-fixed-size fixed paf size (default: False)
--paf-aspect-ratio PAF_ASPECT_RATIO
paf width relative to its length (default: 0.0)
pif encoder:
--pif-side-length PIF_SIDE_LENGTH
side length of the PIF field (default: 4)
optimizer:
--momentum MOMENTUM SGD momentum, beta1 in Adam (default: 0.9)
--beta2 BETA2 beta2 for Adam/AMSGrad (default: 0.999)
--adam-eps ADAM_EPS eps value for Adam/AMSGrad (default: 1e-06)
--no-nesterov do not use Nesterov momentum for SGD update (default:
True)
--weight-decay WEIGHT_DECAY
SGD/Adam/AMSGrad weight decay (default: 0.0)
--adam use Adam optimizer (default: False)
--amsgrad use Adam optimizer with AMSGrad option (default:
False)
learning rate scheduler:
--lr LR learning rate (default: 0.001)
--lr-decay LR_DECAY [LR_DECAY ...]
epochs at which to decay the learning rate (default:
[])
--lr-burn-in-epochs LR_BURN_IN_EPOCHS
number of epochs at the beginning with lower learning
rate (default: 3)
--lr-burn-in-factor LR_BURN_IN_FACTOR
learning pre-factor during burn-in (default: 0.01)
--lr-gamma LR_GAMMA learning rate decay factor (default: 0.1)
dataset and loader:
--train-annotations TRAIN_ANNOTATIONS
--train-image-dir TRAIN_IMAGE_DIR
--val-annotations VAL_ANNOTATIONS
--val-image-dir VAL_IMAGE_DIR
--pre-n-images PRE_N_IMAGES
number of images to sampe for pretraining (default:
8000)
--n-images N_IMAGES number of images to sample (default: None)
--duplicate-data DUPLICATE_DATA
duplicate data (default: None)
--pre-duplicate-data PRE_DUPLICATE_DATA
duplicate pre data in preprocessing (default: None)
--loader-workers LOADER_WORKERS
number of workers for data loading (default: 2)
--batch-size BATCH_SIZE
batch size (default: 8)