Spaces:
Configuration error
Configuration error
File size: 4,692 Bytes
1ba539f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 |
import open3d as o3d
from . import yacs
from .yacs import CfgNode as CN
import argparse
import os
import numpy as np
import pprint
cfg = CN()
# experiment name
cfg.exp_name = 'hello'
# network
cfg.point_feature = 9
cfg.distributed = False
# data
cfg.human = 313
cfg.training_view = [0, 6, 12, 18]
cfg.intv = 1
cfg.begin_ith_frame = 0 # the first smpl
cfg.num_train_frame = 1 # number of smpls
cfg.num_render_frame = -1 # number of frames to render
cfg.ith_frame = 0 # the i-th smpl
cfg.frame_interval = 1
cfg.nv = 6890 # number of vertices
cfg.smpl = 'smpl_4views_5e-4'
cfg.vertices = 'vertices'
cfg.params = 'params_4views_5e-4'
cfg.mask_bkgd = True
cfg.sample_smpl = False
cfg.sample_grid = False
cfg.sample_fg_ratio = 0.7
cfg.H = 1024
cfg.W = 1024
cfg.add_pointcloud = False
cfg.big_box = False
cfg.rot_ratio = 0.
cfg.rot_range = np.pi / 32
# mesh
cfg.mesh_th = 50 # threshold of alpha
# task
cfg.task = 'nerf4d'
# gpus
cfg.gpus = list(range(8))
# if load the pretrained network
cfg.resume = True
# epoch
cfg.ep_iter = -1
cfg.save_ep = 100
cfg.save_latest_ep = 5
cfg.eval_ep = 100
# -----------------------------------------------------------------------------
# train
# -----------------------------------------------------------------------------
cfg.train = CN()
cfg.train.dataset = 'CocoTrain'
cfg.train.epoch = 10000
cfg.train.num_workers = 8
cfg.train.collator = ''
cfg.train.batch_sampler = 'default'
cfg.train.sampler_meta = CN({'min_hw': [256, 256], 'max_hw': [480, 640], 'strategy': 'range'})
cfg.train.shuffle = True
# use adam as default
cfg.train.optim = 'adam'
cfg.train.lr = 1e-4
cfg.train.weight_decay = 0
cfg.train.scheduler = CN({'type': 'multi_step', 'milestones': [80, 120, 200, 240], 'gamma': 0.5})
cfg.train.batch_size = 4
cfg.train.acti_func = 'relu'
cfg.train.use_vgg = False
cfg.train.vgg_pretrained = ''
cfg.train.vgg_layer_name = [0,0,0,0,0]
cfg.train.use_ssim = False
cfg.train.use_d = False
# test
cfg.test = CN()
cfg.test.dataset = 'CocoVal'
cfg.test.batch_size = 1
cfg.test.epoch = -1
cfg.test.sampler = 'default'
cfg.test.batch_sampler = 'default'
cfg.test.sampler_meta = CN({'min_hw': [480, 640], 'max_hw': [480, 640], 'strategy': 'origin'})
cfg.test.frame_sampler_interval = 30
# trained model
cfg.trained_model_dir = 'data/trained_model'
# recorder
cfg.record_dir = 'data/record'
cfg.log_interval = 20
cfg.record_interval = 20
# result
cfg.result_dir = 'data/result'
# evaluation
cfg.skip_eval = False
cfg.test_novel_pose = False
cfg.novel_pose_ni = 100
cfg.vis_novel_pose = False
cfg.vis_novel_view = False
cfg.vis_rotate_smpl = False
cfg.vis_mesh = False
cfg.eval_whole_img = False
cfg.fix_random = False
cfg.vis = 'mesh'
# data
cfg.body_sample_ratio = 0.5
cfg.face_sample_ratio = 0.
def parse_cfg(cfg, args):
if len(cfg.task) == 0:
raise ValueError('task must be specified')
# assign the gpus
os.environ['CUDA_VISIBLE_DEVICES'] = ', '.join([str(gpu) for gpu in cfg.gpus])
cfg.trained_model_dir = os.path.join(cfg.trained_model_dir, cfg.task, cfg.exp_name)
cfg.record_dir = os.path.join(cfg.record_dir, cfg.task, cfg.exp_name)
cfg.result_dir = os.path.join(cfg.result_dir, cfg.task, cfg.exp_name)
cfg.local_rank = args.local_rank
cfg.distributed = cfg.distributed or args.launcher not in ['none']
def make_cfg(args):
with open(args.cfg_file, 'r') as f:
current_cfg = yacs.load_cfg(f)
if 'parent_cfg' in current_cfg.keys():
with open(current_cfg.parent_cfg, 'r') as f:
parent_cfg = yacs.load_cfg(f)
cfg.merge_from_other_cfg(parent_cfg)
cfg.merge_from_other_cfg(current_cfg)
cfg.merge_from_list(args.opts)
if cfg.vis_novel_pose:
cfg.merge_from_other_cfg(cfg.novel_pose_cfg)
if cfg.vis_novel_view:
cfg.merge_from_other_cfg(cfg.novel_view_cfg)
if cfg.vis_rotate_smpl:
cfg.merge_from_other_cfg(cfg.rotate_smpl_cfg)
if cfg.vis_mesh:
cfg.merge_from_other_cfg(cfg.mesh_cfg)
cfg.merge_from_list(args.opts)
parse_cfg(cfg, args)
# pprint.pprint(cfg)
return cfg
parser = argparse.ArgumentParser()
parser.add_argument("--cfg_file", default="configs/default.yaml", type=str)
parser.add_argument('--test', action='store_true', dest='test', default=False)
parser.add_argument("--type", type=str, default="")
parser.add_argument('--det', type=str, default='')
parser.add_argument('--local_rank', type=int, default=0)
parser.add_argument('--launcher', type=str, default='none', choices=['none', 'pytorch'])
parser.add_argument("opts", default=None, nargs=argparse.REMAINDER)
args = parser.parse_args()
if len(args.type) > 0:
cfg.task = "run"
cfg = make_cfg(args)
|