mirror of
https://github.com/nerfstudio-project/nerfstudio.git
synced 2026-11-11 02:24:38 +08:00
56661b5d9a
* updated three.js version. only send camera information when it moves * changing code back to updating camera constantly because packets seem to be lost * interrupting function during rendering * small linting fixes * added logic for interrupting rendering + separted out visualizer logic from trainer Co-authored-by: evonneng <evonne_ng@berkeley.edu>
108 lines
2.8 KiB
YAML
108 lines
2.8 KiB
YAML
defaults:
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- override hydra/job_logging: colorlog
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- override hydra/hydra_logging: colorlog
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- _self_
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machine:
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seed: 42
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num_gpus: 1
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num_machines: 1
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machine_rank: 0
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dist_url: auto
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logging:
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steps_per_log: 10
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max_buffer_size: 20
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# writer logs losses and images per iteration
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writer:
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TensorboardWriter:
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log_dir: "./"
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LocalWriter:
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log_dir: "./"
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stats_to_track:
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[ITER_LOAD_TIME, ITER_TRAIN_TIME, RAYS_PER_SEC, CURR_TEST_PSNR]
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max_log_size: 10 # if 0, logs everything with no erasing
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# profiler logs run times of functions and prints at end of training
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enable_profiler: True
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trainer:
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model_dir: "./checkpoints"
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steps_per_save: 1000
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steps_per_test: 1000
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max_num_iterations: 1000000
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resume_train:
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load_dir: # pretrained model directory
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load_step: # pretrained model's step number
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experiment_name: blender_lego
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method_name: vanilla_nerf
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# hydra settings
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hydra:
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mode: RunMode.RUN
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run:
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dir: outputs/${experiment_name}/${method_name}/${now:%Y-%m-%d_%H%M%S}
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data:
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# Train dataloading.
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dataset_inputs_train:
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data_directory: data/blender/lego
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dataset_format: blender
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downscale_factor: 1
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alpha_color: white
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image_dataset_train:
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_target_: pyrad.data.image_dataset.ImageDataset
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dataloader_train:
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_target_: pyrad.data.dataloader.TrainDataloader
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image_sampler:
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_target_: pyrad.data.image_sampler.CacheImageSampler
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num_images_to_sample_from: 8
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num_times_to_repeat_images: 100
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pixel_sampler:
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_target_: pyrad.data.pixel_sampler.PixelSampler
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num_rays_per_batch: 1024
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# Eval dataloading.
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dataset_inputs_eval:
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data_directory: data/blender/lego
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dataset_format: blender
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downscale_factor: 1 # NOTE: this might be the only value that changes
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alpha_color: white
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image_dataset_eval:
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_target_: pyrad.data.image_dataset.ImageDataset
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dataloader_eval:
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_target_: pyrad.data.dataloader.FixedIndicesEvalDataloader
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image_indices: [0] # which images to evaluate on
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num_rays_per_chunk: 4096
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# dataloader_eval:
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# _target_: pyrad.data.dataloader.RandIndicesEvalDataloader
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# num_rays_per_chunk: 4096
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graph:
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_target_: pyrad.graphs.vanilla_nerf.NeRFGraph
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collider_config:
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_target_: pyrad.graphs.modules.scene_colliders.NearFarCollider
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near_plane: 2.0
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far_plane: 6.0
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num_coarse_samples: 64
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num_importance_samples: 128
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loss_coefficients:
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rgb_loss_coarse: 1.0
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rgb_loss_fine: 1.0
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optimizers:
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fields:
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optimizer:
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_target_: torch.optim.RAdam
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lr: 0.0005
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scheduler:
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_target_: pyrad.optimizers.optimizers.ExponentialDecaySchedule
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lr_final: 0.000005
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max_steps: 1000000
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viewer:
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enable: False
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zmq_url: tcp://127.0.0.1:6000
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min_render_image_height: 100
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max_render_image_height: 1000
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num_rays_per_chunk: 4096
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