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Running
on
A10G
Running
on
A10G
import os | |
import os.path as osp | |
# will be update in exp | |
num_gpus = -1 | |
exp_name = 'output/exp1/pre_analysis' | |
# quick access | |
save_epoch = 1 | |
lr = 1e-5 | |
end_epoch = 10 | |
train_batch_size = 32 | |
syncbn = True | |
bbox_ratio = 1.2 | |
# continue | |
continue_train = False | |
start_over = True | |
# dataset setting | |
agora_fix_betas = True | |
agora_fix_global_orient_transl = True | |
agora_valid_root_pose = True | |
# all | |
dataset_list = ['Human36M', 'MSCOCO', 'MPII', 'AGORA', 'EHF', 'SynBody', 'GTA_Human2', \ | |
'EgoBody_Egocentric', 'EgoBody_Kinect', 'UBody', 'PW3D', 'MuCo', 'PROX'] | |
trainset_3d = ['MSCOCO','AGORA', 'UBody'] | |
trainset_2d = ['PW3D', 'MPII', 'Human36M'] | |
trainset_humandata = ['BEDLAM', 'SPEC', 'GTA_Human2','SynBody', 'PoseTrack', | |
'EgoBody_Egocentric', 'PROX', 'CrowdPose', | |
'EgoBody_Kinect', 'MPI_INF_3DHP', 'RICH', 'MuCo', 'InstaVariety', | |
'Behave', 'UP3D', 'ARCTIC', | |
'OCHuman', 'CHI3D', 'RenBody_HiRes', 'MTP', 'HumanSC3D', 'RenBody', | |
'FIT3D', 'Talkshow' , 'SSP3D', 'LSPET'] | |
testset = 'EHF' | |
use_cache = True | |
# downsample | |
BEDLAM_train_sample_interval = 5 | |
EgoBody_Kinect_train_sample_interval = 10 | |
train_sample_interval = 10 # UBody | |
MPI_INF_3DHP_train_sample_interval = 5 | |
InstaVariety_train_sample_interval = 10 | |
RenBody_HiRes_train_sample_interval = 5 | |
ARCTIC_train_sample_interval = 10 | |
# RenBody_train_sample_interval = 10 | |
FIT3D_train_sample_interval = 10 | |
Talkshow_train_sample_interval = 10 | |
# strategy | |
data_strategy = 'balance' # 'balance' need to define total_data_len | |
total_data_len = 4500000 | |
# model | |
smplx_loss_weight = 1.0 #2 for agora_model for smplx shape | |
smplx_pose_weight = 10.0 | |
smplx_kps_3d_weight = 100.0 | |
smplx_kps_2d_weight = 1.0 | |
net_kps_2d_weight = 1.0 | |
agora_benchmark = 'agora_model' # 'agora_model', 'test_only' | |
model_type = 'smpler_x_b' | |
encoder_config_file = 'main/transformer_utils/configs/smpler_x/encoder/body_encoder_base.py' | |
encoder_pretrained_model_path = 'pretrained_models/vitpose_base.pth' | |
feat_dim = 768 | |
## =====FIXED ARGS============================================================ | |
## model setting | |
upscale = 4 | |
hand_pos_joint_num = 20 | |
face_pos_joint_num = 72 | |
num_task_token = 24 | |
num_noise_sample = 0 | |
## UBody setting | |
train_sample_interval = 10 | |
test_sample_interval = 100 | |
make_same_len = False | |
## input, output size | |
input_img_shape = (512, 384) | |
input_body_shape = (256, 192) | |
output_hm_shape = (16, 16, 12) | |
input_hand_shape = (256, 256) | |
output_hand_hm_shape = (16, 16, 16) | |
output_face_hm_shape = (8, 8, 8) | |
input_face_shape = (192, 192) | |
focal = (5000, 5000) # virtual focal lengths | |
princpt = (input_body_shape[1] / 2, input_body_shape[0] / 2) # virtual principal point position | |
body_3d_size = 2 | |
hand_3d_size = 0.3 | |
face_3d_size = 0.3 | |
camera_3d_size = 2.5 | |
## training config | |
print_iters = 100 | |
lr_mult = 1 | |
## testing config | |
test_batch_size = 32 | |
## others | |
num_thread = 2 | |
vis = False | |
## directory | |
output_dir, model_dir, vis_dir, log_dir, result_dir, code_dir = None, None, None, None, None, None | |