Jerome-Hsieh
commented
6 months ago have you solved this problem？
Open Flyingdog-Huang opened 11 months ago
Jerome-Hsieh
commented
6 months ago have you solved this problem？
2023-10-24 02:00:54.767 | INFO | main:main:25 - ==> Init dataloader ... 100%|█████████████████████████████████████████████████████████| 800/800 [00:00<00:00, 204837.51it/s] 2023-10-24 02:00:54.944 | INFO | dataset.ray_dataset:init:42 - ==> Find 4 cameras 100%|████████████████████████████████████████████████████████████| 200/200 [00:01<00:00, 111.36it/s] 100%|███████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 550.07it/s] 100%|██████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 2726.73it/s] 100%|██████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 8469.83it/s] 100%|████████████████████████████████████████████████████████████████| 800/800 [00:00<00:00, 222524.25it/s] 2023-10-24 02:00:58.635 | INFO | dataset.ray_dataset:init:42 - ==> Find 4 cameras 100%|███████████████████████████████████████████████████████████████████| 200/200 [00:01<00:00, 111.41it/s] 100%|███████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 486.54it/s] 100%|██████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 5384.91it/s] 100%|██████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 6841.64it/s] 2023-10-24 02:01:02.330 | INFO | main:main:49 - ==> Init model ... 2023-10-24 02:01:04.057 | INFO | main:main:51 - TriMipRFModel( (field): TriMipRF( (encoding): TriMipEncoding() (direction_encoding): Encoding(n_input_dims=3, n_output_dims=16, seed=1337, dtype=torch.float16, hyperparams={'degree': 4, 'otype': 'SphericalHarmonics'}) (mlp_base): Network(n_input_dims=48, n_output_dims=16, seed=1337, dtype=torch.float16, hyperparams={'encoding': {'offset': 0.0, 'otype': 'Identity', 'scale': 1.0}, 'network': {'activation': 'ReLU', 'n_hidden_layers': 2, 'n_neurons': 128, 'otype': 'FullyFusedMLP', 'output_activation': 'None'}, 'otype': 'NetworkWithInputEncoding'}) (mlp_head): Network(n_input_dims=31, n_output_dims=3, seed=1337, dtype=torch.float16, hyperparams={'encoding': {'offset': 0.0, 'otype': 'Identity', 'scale': 1.0}, 'network': {'activation': 'ReLU', 'n_hidden_layers': 4, 'n_neurons': 128, 'otype': 'FullyFusedMLP', 'output_activation': 'Sigmoid'}, 'otype': 'NetworkWithInputEncoding'}) ) (ray_sampler): OccupancyGrid() ) 2023-10-24 02:01:04.058 | INFO | main:main:53 - ==> Init trainer ... 2023-10-24 02:01:04.098 | INFO | trainer.trainer:init:60 - # Parameters for trimipRF.get_optimizer:
==============================================================================
trimipRF.get_optimizer.feature_lr_scale = 10.0 trimipRF.get_optimizer.lr = 0.002 trimipRF.get_optimizer.weight_decay = 1e-05
Parameters for get_scheduler:
==============================================================================
get_scheduler.gamma = 0.6
Parameters for main:
==============================================================================
main.batch_size = 24 main.model_name = 'Tri-MipRF' main.num_workers = 4 main.seed = 42 main.stages = 'train_eval' main.train_split = 'trainval'
Parameters for RayDataset:
==============================================================================
RayDataset.base_path = \ '/home/jovyan/vol-1/Tri-MipRF/data/nerf_synthetic_multiscale' RayDataset.num_rays = 8192 RayDataset.render_bkgd = 'white' RayDataset.scene = 'chair' RayDataset.scene_type = 'nerf_synthetic_multiscale' RayDataset.to_world = True
Parameters for Trainer:
==============================================================================
Trainer.base_exp_dir = '/home/jovyan/vol-1/Tri-MipRF/output' Trainer.dynamic_batch_size = True Trainer.eval_step = 25000 Trainer.exp_name = 'nerf_synthetic_multiscale/chair/Tri-MipRF/2023-10-24_02-00-54' Trainer.log_step = 1000 Trainer.max_steps = 25001 Trainer.num_rays = 8192 Trainer.target_sample_batch_size = 65536 Trainer.test_chunk_size = 8192 Trainer.varied_eval_img = True
Parameters for TriMipRF:
==============================================================================
TriMipRF.feature_dim = 16 TriMipRF.geo_feat_dim = 15 TriMipRF.n_levels = 8 TriMipRF.net_depth_base = 2 TriMipRF.net_depth_color = 4 TriMipRF.net_width = 128 TriMipRF.plane_size = 512
Parameters for TriMipRFModel:
==============================================================================
TriMipRFModel.occ_grid_resolution = 128 TriMipRFModel.samples_per_ray = 1024
2023-10-24 02:01:04.101 | INFO | trainer.trainer:fit:106 - ==> Start training ... (● ) NerfAcc: Setting up CUDA (This may take a few minutes the first time)Killed
model：https://github.com/wbhu/Tri-MipRF version：0.3.3/0.3.5