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deepprompt_eam3d_st_tanh_304_3090_all.yaml
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deepprompt_eam3d_st_tanh_304_3090_all.yaml
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dataset_params:
###### CHANGE THE ROOT PATH HERE ######
root_dir: /data2/gy/mead/images_evp_25/
frame_shape: [256, 256, 3]
id_sampling: False
pairs_list: None
augmentation_params:
flip_param:
horizontal_flip: True
time_flip: False
jitter_param:
brightness: 0.1
contrast: 0.1
saturation: 0.1
hue: 0.1
syncnet_T: 5
model_params:
common_params:
num_kp: 15
image_channel: 3
feature_channel: 32
estimate_jacobian: False
kp_detector_params:
temperature: 0.1
block_expansion: 32
max_features: 1024
scale_factor: 0.25
num_blocks: 5
reshape_channel: 16384 # 16384 = 1024 * 16
reshape_depth: 16
audio2kp_params:
embedding_dim: 256
num_kp: 15
num_w: 5
generator_params:
block_expansion: 64
max_features: 512
num_down_blocks: 2
reshape_channel: 32
reshape_depth: 16 # 512 = 32 * 16
num_resblocks: 6
estimate_occlusion_map: True
dense_motion_params:
block_expansion: 32
max_features: 1024
num_blocks: 5
# reshape_channel: 32
reshape_depth: 16
compress: 4
discriminator_params:
scales: [1]
block_expansion: 32
max_features: 512
num_blocks: 4
sn: True
train_params:
num_epochs: 2000
num_repeats: 1
epoch_milestones: [180,]
lr_generator: 2.0e-4
lr_discriminator: 2.0e-4
lr_kp_detector: 2.0e-4
lr_audio2kptransformer: 1.5e-4
lr_emotionprompt: 2.0e-4
lr_sidetuning: 2.0e-4
gan_mode: 'hinge' # hinge or ls
batch_size: 4
scales: [1, 0.5, 0.25, 0.125]
checkpoint_freq: 1
hopenet_snapshot: './checkpoints/hopenet_robust_alpha1.pkl'
transform_params:
sigma_affine: 0.05
sigma_tps: 0.005
points_tps: 5
loss_weights:
generator_gan: 0
discriminator_gan: 0
# feature_matching: [10, 10, 10, 10]
feature_matching: [0, 0, 0, 0]
# perceptual: [0, 0, 0, 0, 0]
perceptual: [10, 10, 10, 10, 10]
equivariance_value: 0
equivariance_jacobian: 0
keypoint: 0
headpose: 0
expression: 0
latent: 100
pca: 0
dan: 0
lmk: 0
clip: 0
img_l1: 10
sync: 10
train_with_img: True
visualizer_params:
kp_size: 5
draw_border: True
colormap: 'gist_rainbow'