|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
import os |
|
|
|
from yacs.config import CfgNode as CN |
|
|
|
_C = CN(new_allowed=True) |
|
|
|
|
|
_C.name = "default" |
|
_C.gpus = [0] |
|
_C.test_gpus = [1] |
|
_C.devices = 1 |
|
_C.root = "./data/" |
|
_C.ckpt_dir = "./data/ckpt/" |
|
_C.resume_path = "" |
|
_C.normal_path = "" |
|
_C.ifnet_path = "" |
|
_C.results_path = "./results/" |
|
_C.projection_mode = "orthogonal" |
|
_C.num_views = 1 |
|
_C.sdf = False |
|
_C.sdf_clip = 5.0 |
|
|
|
_C.lr_netF = 1e-3 |
|
_C.lr_netB = 1e-3 |
|
_C.lr_netD = 1e-3 |
|
_C.lr_G = 1e-3 |
|
_C.weight_decay = 0.0 |
|
_C.momentum = 0.0 |
|
_C.optim = "RMSprop" |
|
_C.schedule = [5, 10, 15] |
|
_C.gamma = 0.1 |
|
|
|
_C.overfit = False |
|
_C.resume = False |
|
_C.test_mode = False |
|
_C.test_uv = False |
|
_C.draw_geo_thres = 0.60 |
|
_C.num_sanity_val_steps = 2 |
|
_C.fast_dev = 0 |
|
_C.get_fit = False |
|
_C.agora = False |
|
_C.optim_cloth = False |
|
_C.optim_body = False |
|
_C.mcube_res = 256 |
|
_C.clean_mesh = True |
|
_C.remesh = False |
|
_C.body_overlap_thres = 1.0 |
|
_C.cloth_overlap_thres = 1.0 |
|
|
|
_C.batch_size = 4 |
|
_C.num_threads = 8 |
|
|
|
_C.num_epoch = 10 |
|
_C.freq_plot = 0.01 |
|
_C.freq_show_train = 0.1 |
|
_C.freq_show_val = 0.2 |
|
_C.freq_eval = 0.5 |
|
_C.accu_grad_batch = 4 |
|
|
|
_C.vol_res = 128 |
|
|
|
_C.test_items = ["sv", "mv", "mv-fusion", "hybrid", "dc-pred", "gt"] |
|
|
|
_C.net = CN() |
|
_C.net.gtype = "HGPIFuNet" |
|
_C.net.ctype = "resnet18" |
|
_C.net.classifierIMF = "MultiSegClassifier" |
|
_C.net.netIMF = "resnet18" |
|
_C.net.norm = "group" |
|
_C.net.norm_mlp = "group" |
|
_C.net.norm_color = "group" |
|
_C.net.hg_down = "ave_pool" |
|
_C.net.num_views = 1 |
|
|
|
_C.bni = CN() |
|
_C.bni.k = 4 |
|
_C.bni.lambda1 = 1e-4 |
|
_C.bni.boundary_consist = 1e-6 |
|
_C.bni.poisson_depth = 10 |
|
_C.bni.use_poisson = True |
|
_C.bni.use_smpl = ["face", "hand"] |
|
_C.bni.use_ifnet = False |
|
_C.bni.finish = False |
|
_C.bni.thickness = 0.00 |
|
_C.bni.hand_thres = 4e-2 |
|
_C.bni.face_thres = 6e-2 |
|
_C.bni.hps_type = "pixie" |
|
_C.bni.texture_src = "image" |
|
_C.bni.cut_intersection = True |
|
|
|
|
|
|
|
_C.net.conv1 = [7, 2, 1, 3] |
|
_C.net.conv3x3 = [3, 1, 1, 1] |
|
|
|
_C.net.num_stack = 4 |
|
_C.net.num_hourglass = 2 |
|
_C.net.hourglass_dim = 256 |
|
_C.net.voxel_dim = 32 |
|
_C.net.resnet_dim = 120 |
|
_C.net.mlp_dim = [320, 1024, 512, 256, 128, 1] |
|
_C.net.mlp_dim_knn = [320, 1024, 512, 256, 128, 3] |
|
_C.net.mlp_dim_color = [513, 1024, 512, 256, 128, 3] |
|
_C.net.mlp_dim_multiseg = [1088, 2048, 1024, 500] |
|
_C.net.res_layers = [2, 3, 4] |
|
_C.net.filter_dim = 256 |
|
_C.net.smpl_dim = 3 |
|
|
|
_C.net.cly_dim = 3 |
|
_C.net.soft_dim = 64 |
|
_C.net.z_size = 200.0 |
|
_C.net.N_freqs = 10 |
|
_C.net.geo_w = 0.1 |
|
_C.net.norm_w = 0.1 |
|
_C.net.dc_w = 0.1 |
|
_C.net.C_cat_to_G = False |
|
|
|
_C.net.skip_hourglass = True |
|
_C.net.use_tanh = True |
|
_C.net.soft_onehot = True |
|
_C.net.no_residual = True |
|
_C.net.use_attention = False |
|
|
|
_C.net.prior_type = "icon" |
|
_C.net.smpl_feats = ["sdf", "vis"] |
|
_C.net.use_filter = True |
|
_C.net.use_cc = False |
|
_C.net.use_PE = False |
|
_C.net.use_IGR = False |
|
_C.net.use_gan = False |
|
_C.net.in_geo = () |
|
_C.net.in_nml = () |
|
_C.net.front_losses = () |
|
_C.net.back_losses = () |
|
|
|
_C.net.gan = CN() |
|
_C.net.gan.dim_detail = 64 |
|
_C.net.gan.lambda_gan = 1 |
|
_C.net.gan.lambda_grad = 10 |
|
_C.net.gan.lambda_recon = 10 |
|
_C.net.gan.d_reg_every = 16 |
|
_C.net.gan.img_res = 512 |
|
|
|
_C.dataset = CN() |
|
_C.dataset.root = "" |
|
_C.dataset.cached = True |
|
_C.dataset.set_splits = [0.95, 0.04] |
|
_C.dataset.types = [ |
|
"3dpeople", |
|
"axyz", |
|
"renderpeople", |
|
"renderpeople_p27", |
|
"humanalloy", |
|
] |
|
_C.dataset.scales = [1.0, 100.0, 1.0, 1.0, 100.0 / 39.37] |
|
_C.dataset.rp_type = "pifu900" |
|
_C.dataset.th_type = "train" |
|
_C.dataset.input_size = 512 |
|
_C.dataset.rotation_num = 3 |
|
_C.dataset.num_precomp = 10 |
|
_C.dataset.num_multiseg = 500 |
|
_C.dataset.num_knn = 10 |
|
_C.dataset.num_knn_dis = 20 |
|
_C.dataset.num_verts_max = 20000 |
|
_C.dataset.zray_type = False |
|
_C.dataset.online_smpl = False |
|
_C.dataset.noise_type = ["z-trans", "pose", "beta"] |
|
_C.dataset.noise_scale = [0.0, 0.0, 0.0] |
|
_C.dataset.num_sample_geo = 10000 |
|
_C.dataset.num_sample_color = 0 |
|
_C.dataset.num_sample_seg = 0 |
|
_C.dataset.num_sample_knn = 10000 |
|
|
|
_C.dataset.sigma_geo = 5.0 |
|
_C.dataset.sigma_color = 0.10 |
|
_C.dataset.sigma_seg = 0.10 |
|
_C.dataset.thickness_threshold = 20.0 |
|
_C.dataset.ray_sample_num = 2 |
|
_C.dataset.semantic_p = False |
|
_C.dataset.remove_outlier = False |
|
_C.dataset.laplacian_iters = 0 |
|
_C.dataset.prior_type = "smpl" |
|
_C.dataset.voxel_res = 128 |
|
|
|
_C.dataset.train_bsize = 1.0 |
|
_C.dataset.val_bsize = 1.0 |
|
_C.dataset.test_bsize = 1.0 |
|
_C.dataset.single = True |
|
|
|
|
|
def get_cfg_defaults(): |
|
"""Get a yacs CfgNode object with default values for my_project.""" |
|
|
|
|
|
return _C.clone() |
|
|
|
|
|
|
|
|
|
cfg = _C |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def update_cfg(cfg_file): |
|
|
|
_C.merge_from_file(cfg_file) |
|
|
|
return _C |
|
|
|
|
|
def parse_args(args): |
|
cfg_file = args.cfg_file |
|
if args.cfg_file is not None: |
|
cfg = update_cfg(args.cfg_file) |
|
else: |
|
cfg = get_cfg_defaults() |
|
|
|
|
|
|
|
|
|
return cfg |
|
|
|
|
|
def parse_args_extend(args): |
|
if args.resume: |
|
if not os.path.exists(args.log_dir): |
|
raise ValueError("Experiment are set to resume mode, but log directory does not exist.") |
|
|
|
|
|
cfg_file = os.path.join(args.log_dir, "cfg.yaml") |
|
cfg = update_cfg(cfg_file) |
|
|
|
if args.misc is not None: |
|
cfg.merge_from_list(args.misc) |
|
else: |
|
parse_args(args) |
|
|