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Types & classes47 in github.com/bennyguo/instant-nsr-pl

⨍ Functions 274◇ Types & classes 47↳ Endpoints 1
↓ 3 callersClassBlenderDataset
datasets/blender.py:74
↓ 3 callersClassColmapDataset
datasets/colmap.py:271
↓ 3 callersClassDTUDataset
datasets/dtu.py:140
↓ 2 callersClassImage
datasets/colmap_utils.py:47
↓ 2 callersClassPSNR
systems/criterions.py:40
↓ 1 callersClassBlenderIterableDataset
datasets/blender.py:87
↓ 1 callersClassChainedScheduler
Chains list of learning rate schedulers. It takes a list of chainable learning rate schedulers and performs consecutive step() functions belong to
systems/utils.py:12
↓ 1 callersClassCodeSnapshotCallback
utils/callbacks.py:52
↓ 1 callersClassColmapIterableDataset
datasets/colmap.py:284
↓ 1 callersClassCompositeEncoding
models/network_utils.py:68
↓ 1 callersClassConfigSnapshotCallback
utils/callbacks.py:79
↓ 1 callersClassCustomProgressBar
utils/callbacks.py:94
↓ 1 callersClassDTUIterableDataset
datasets/dtu.py:153
↓ 1 callersClassEncodingWithNetwork
models/network_utils.py:187
↓ 1 callersClassMarchingCubeHelper
models/geometry.py:32
↓ 1 callersClassProgressiveBandHashGrid
models/network_utils.py:40
↓ 1 callersClassSequentialLR
Receives the list of schedulers that is expected to be called sequentially during optimization process and milestone points that provides exact in
systems/utils.py:82
↓ 1 callersClassVanillaFrequency
models/network_utils.py:14
↓ 1 callersClassVanillaMLP
models/network_utils.py:95
↓ 1 callersClassVarianceNetwork
models/neus.py:15
ClassBaseImplicitGeometry
models/geometry.py:69
ClassBaseModel
models/base.py:6
ClassBaseSystem
Two ways to print to console: 1. self.print: correctly handle progress bar 2. rank_zero_info: use the logging module
systems/base.py:9
ClassBlenderDataModule
datasets/blender.py:97
ClassBlenderDatasetBase
datasets/blender.py:18
ClassColmapDataModule
datasets/colmap.py:294
ClassColmapDatasetBase
datasets/colmap.py:132
ClassConsoleLogger
utils/loggers.py:9
ClassConstantLR
Decays the learning rate of each parameter group by a small constant factor until the number of epoch reaches a pre-defined milestone: total_iters
systems/utils.py:165
ClassDTUDataModule
datasets/dtu.py:163
ClassDTUDatasetBase
datasets/dtu.py:58
ClassL1Loss
systems/criterions.py:34
ClassLinearLR
Decays the learning rate of each parameter group by linearly changing small multiplicative factor until the number of epoch reaches a pre-defined
systems/utils.py:222
ClassMSELoss
systems/criterions.py:28
ClassNeRFModel
models/nerf.py:15
ClassNeRFSystem
Two ways to print to console: 1. self.print: correctly handle progress bar 2. rank_zero_info: use the logging module
systems/nerf.py:17
ClassNeuSModel
models/neus.py:47
ClassNeuSSystem
Two ways to print to console: 1. self.print: correctly handle progress bar 2. rank_zero_info: use the logging module
systems/neus.py:18
ClassSSIM
systems/criterions.py:55
ClassSaverMixin
utils/mixins.py:16
ClassVersionedCallback
utils/callbacks.py:16
ClassVolumeColor
models/texture.py:40
ClassVolumeDensity
models/geometry.py:116
ClassVolumeRadiance
models/texture.py:11
ClassVolumeSDF
models/geometry.py:144
ClassWeightedLoss
systems/criterions.py:6
Class_TruncExp
models/utils.py:53