""" Default config for PIXIE """ from yacs.config import CfgNode as CN import argparse import yaml import os cfg = CN() abs_pixie_dir = os.path.abspath( os.path.join(os.path.dirname(__file__), "..", "..", "..")) cfg.pixie_dir = abs_pixie_dir cfg.device = "cuda" cfg.device_id = "0" cfg.pretrained_modelpath = os.path.join("smpl_related/HPS/pixie_data", "pixie_model.tar") # smplx parameter settings cfg.params = CN() cfg.params.body_list = [ "body_cam", "global_pose", "partbody_pose", "neck_pose" ] cfg.params.head_list = ["head_cam", "tex", "light"] cfg.params.head_share_list = ["shape", "exp", "head_pose", "jaw_pose"] cfg.params.hand_list = ["hand_cam"] cfg.params.hand_share_list = [ "right_wrist_pose", "right_hand_pose", ] # only for right hand # ---------------------------------------------------------------------------- # # Options for Body model # ---------------------------------------------------------------------------- # cfg.model = CN() cfg.model.topology_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "SMPL_X_template_FLAME_uv.obj") cfg.model.topology_smplxtex_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "smplx_tex.obj") cfg.model.topology_smplx_hand_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "smplx_hand.obj") cfg.model.smplx_model_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "SMPLX_NEUTRAL_2020.npz") cfg.model.face_mask_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "uv_face_mask.png") cfg.model.face_eye_mask_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "uv_face_eye_mask.png") cfg.model.tex_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "FLAME_albedo_from_BFM.npz") cfg.model.extra_joint_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "smplx_extra_joints.yaml") cfg.model.j14_regressor_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "SMPLX_to_J14.pkl") cfg.model.flame2smplx_cached_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "flame2smplx_tex_1024.npy") cfg.model.smplx_tex_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "smplx_tex.png") cfg.model.mano_ids_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "MANO_SMPLX_vertex_ids.pkl") cfg.model.flame_ids_path = os.path.join(cfg.pixie_dir, "smpl_related/HPS/pixie_data", "SMPL-X__FLAME_vertex_ids.npy") cfg.model.uv_size = 256 cfg.model.n_shape = 200 cfg.model.n_tex = 50 cfg.model.n_exp = 50 cfg.model.n_body_cam = 3 cfg.model.n_head_cam = 3 cfg.model.n_hand_cam = 3 cfg.model.tex_type = "BFM" # BFM, FLAME, albedoMM cfg.model.uvtex_type = "SMPLX" # FLAME or SMPLX cfg.model.use_tex = False # whether to use flame texture model cfg.model.flame_tex_path = "" # pose cfg.model.n_global_pose = 3 * 2 cfg.model.n_head_pose = 3 * 2 cfg.model.n_neck_pose = 3 * 2 cfg.model.n_jaw_pose = 3 # euler angle cfg.model.n_body_pose = 21 * 3 * 2 cfg.model.n_partbody_pose = (21 - 4) * 3 * 2 cfg.model.n_left_hand_pose = 15 * 3 * 2 cfg.model.n_right_hand_pose = 15 * 3 * 2 cfg.model.n_left_wrist_pose = 1 * 3 * 2 cfg.model.n_right_wrist_pose = 1 * 3 * 2 cfg.model.n_light = 27 cfg.model.check_pose = True # ---------------------------------------------------------------------------- # # Options for Dataset # ---------------------------------------------------------------------------- # cfg.dataset = CN() cfg.dataset.source = ["body", "head", "hand"] # head/face dataset cfg.dataset.head = CN() cfg.dataset.head.batch_size = 24 cfg.dataset.head.num_workers = 2 cfg.dataset.head.from_body = True cfg.dataset.head.image_size = 224 cfg.dataset.head.image_hd_size = 224 cfg.dataset.head.scale_min = 1.8 cfg.dataset.head.scale_max = 2.2 cfg.dataset.head.trans_scale = 0.3 # body datset cfg.dataset.body = CN() cfg.dataset.body.batch_size = 24 cfg.dataset.body.num_workers = 2 cfg.dataset.body.image_size = 224 cfg.dataset.body.image_hd_size = 1024 cfg.dataset.body.use_hd = True # hand datset cfg.dataset.hand = CN() cfg.dataset.hand.batch_size = 24 cfg.dataset.hand.num_workers = 2 cfg.dataset.hand.image_size = 224 cfg.dataset.hand.image_hd_size = 512 cfg.dataset.hand.scale_min = 2.2 cfg.dataset.hand.scale_max = 2.6 cfg.dataset.hand.trans_scale = 0.4 # ---------------------------------------------------------------------------- # # Options for Network # ---------------------------------------------------------------------------- # cfg.network = CN() cfg.network.encoder = CN() cfg.network.encoder.body = CN() cfg.network.encoder.body.type = "hrnet" cfg.network.encoder.head = CN() cfg.network.encoder.head.type = "resnet50" cfg.network.encoder.hand = CN() cfg.network.encoder.hand.type = "resnet50" cfg.network.regressor = CN() cfg.network.regressor.head_share = CN() cfg.network.regressor.head_share.type = "mlp" cfg.network.regressor.head_share.channels = [1024, 1024] cfg.network.regressor.hand_share = CN() cfg.network.regressor.hand_share.type = "mlp" cfg.network.regressor.hand_share.channels = [1024, 1024] cfg.network.regressor.body = CN() cfg.network.regressor.body.type = "mlp" cfg.network.regressor.body.channels = [1024] cfg.network.regressor.head = CN() cfg.network.regressor.head.type = "mlp" cfg.network.regressor.head.channels = [1024] cfg.network.regressor.hand = CN() cfg.network.regressor.hand.type = "mlp" cfg.network.regressor.hand.channels = [1024] cfg.network.extractor = CN() cfg.network.extractor.head_share = CN() cfg.network.extractor.head_share.type = "mlp" cfg.network.extractor.head_share.channels = [] cfg.network.extractor.left_hand_share = CN() cfg.network.extractor.left_hand_share.type = "mlp" cfg.network.extractor.left_hand_share.channels = [] cfg.network.extractor.right_hand_share = CN() cfg.network.extractor.right_hand_share.type = "mlp" cfg.network.extractor.right_hand_share.channels = [] cfg.network.moderator = CN() cfg.network.moderator.head_share = CN() cfg.network.moderator.head_share.detach_inputs = False cfg.network.moderator.head_share.detach_feature = False cfg.network.moderator.head_share.type = "temp-softmax" cfg.network.moderator.head_share.channels = [1024, 1024] cfg.network.moderator.head_share.reduction = 4 cfg.network.moderator.head_share.scale_type = "scalars" cfg.network.moderator.head_share.scale_init = 1.0 cfg.network.moderator.hand_share = CN() cfg.network.moderator.hand_share.detach_inputs = False cfg.network.moderator.hand_share.detach_feature = False cfg.network.moderator.hand_share.type = "temp-softmax" cfg.network.moderator.hand_share.channels = [1024, 1024] cfg.network.moderator.hand_share.reduction = 4 cfg.network.moderator.hand_share.scale_type = "scalars" cfg.network.moderator.hand_share.scale_init = 0.0 def get_cfg_defaults(): """Get a yacs CfgNode object with default values for my_project.""" # Return a clone so that the defaults will not be altered # This is for the "local variable" use pattern return cfg.clone() def update_cfg(cfg, cfg_file): # cfg.merge_from_file(cfg_file, allow_unsafe=True) cfg.merge_from_file(cfg_file) return cfg.clone() def parse_args(): parser = argparse.ArgumentParser() parser.add_argument("--cfg", type=str, help="cfg file path") args = parser.parse_args() cfg = get_cfg_defaults() if args.cfg is not None: cfg_file = args.cfg cfg = update_cfg(cfg, args.cfg) cfg.cfg_file = cfg_file return cfg