Struct Gaussian3dTrainer

pub struct Gaussian3dTrainer<AB: AutodiffBackend> {

    pub iteration: u64,
    pub learning_rate_colors_sh: LearningRate,
    pub learning_rate_opacities: LearningRate,
    pub learning_rate_positions: LearningRate,
    pub learning_rate_rotations: LearningRate,
    pub learning_rate_scalings: LearningRate,
    pub metric_optimization_coarse: MeanAbsoluteError,
    pub metric_optimization_fine: MeanStructuralDissimilarity<AB, 3>,
    pub optimizer_colors_sh: Adam<AB, 2>,
    pub optimizer_opacities: Adam<AB, 2>,
    pub optimizer_positions: Adam<AB, 2>,
    pub optimizer_rotations: Adam<AB, 2>,
    pub optimizer_scalings: Adam<AB, 2>,
    pub options_renderer: Gaussian3dRenderOptions,
    pub range_metric_optimization_fine: RangeOptions,
    pub refiner: Refiner<AB::InnerBackend>,
}

Trainer for 3DGS.

Fields

iteration: u64

Current iteration.

learning_rate_colors_sh: LearningRate

Current learning rate for colors SH.

learning_rate_opacities: LearningRate

Current learning rate for opacities.

learning_rate_positions: LearningRate

Current learning rate for positions.

learning_rate_rotations: LearningRate

Current learning rate for rotations.

learning_rate_scalings: LearningRate

Current learning rate for scalings.

metric_optimization_coarse: MeanAbsoluteError

Metric for optimization (coarse).

metric_optimization_fine: MeanStructuralDissimilarity<AB, 3>

Metric for optimization (fine).

optimizer_colors_sh: Adam<AB, 2>

Current optimizer for colors SH.

optimizer_opacities: Adam<AB, 2>

Current optimizer for opacities.

optimizer_positions: Adam<AB, 2>

Current optimizer for positions.

optimizer_rotations: Adam<AB, 2>

Current optimizer for rotations.

optimizer_scalings: Adam<AB, 2>

Current optimizer for scalings.

options_renderer: Gaussian3dRenderOptions

Current renderer options.

range_metric_optimization_fine: RangeOptions

Current refiner.

refiner: Refiner<AB::InnerBackend>

Current refiner.

Implementations

impl<AB: AutodiffBackend> Gaussian3dTrainer<AB>

pub fn refine( &mut self, scene: &mut Gaussian3dScene<AB>, grads: &mut AB::Gradients, output: Gaussian3dRenderOutputAutodiff<AB>, ) -> &mut Self

Refine the 3DGS scene.

For each refinement iteration, do the following steps:

1. Compute the mean of 2D position gradient norms (projection errors).
2. Densify the scene:

• Clone the small points.
• Split the large points.
• Retain the visible points.

3. Update the optimizer records.

impl<B: Backend> Gaussian3dTrainer<Autodiff<B>>

where Gaussian3dScene<Autodiff<B>>: Gaussian3dRenderer<B>,

pub fn train( &mut self, scene: &mut Gaussian3dScene<Autodiff<B>>, camera: &Camera, ) -> Result<&mut Self, Error>

Train the 3DGS scene.

impl<AB: AutodiffBackend> Gaussian3dTrainer<AB>

pub fn get_loss_colors_rgb_2d( &self, value: Tensor<AB, 3>, target: Tensor<AB, 3>, ) -> Tensor<AB, 1>

Get the loss for colors RGB (Rendered 2D Image).

pub fn optimize( &mut self, scene: &mut Gaussian3dScene<AB>, grads: &mut AB::Gradients, ) -> &mut Self

Optimize the 3DGS scene.

impl<AB: AutodiffBackend> Gaussian3dTrainer<AB>

pub fn to_device(self, device: &AB::Device) -> Self

Transfer the trainer to the device.

pub fn load_record( &mut self, record: Gaussian3dTrainerRecord<AB::InnerBackend>, ) -> &mut Self

Load the record.

pub fn into_record(self) -> Gaussian3dTrainerRecord<AB::InnerBackend>

Unload the record.

Trait Implementations

impl<AB: Clone + AutodiffBackend> Clone for Gaussian3dTrainer<AB>

where AB::InnerBackend: Clone,

fn clone(&self) -> Gaussian3dTrainer<AB>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<AB: Debug + AutodiffBackend> Debug for Gaussian3dTrainer<AB>

where AB::InnerBackend: Debug,

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<AB: AutodiffBackend> Default for Gaussian3dTrainer<AB>

fn default() -> Self

Returns the “default value” for a type.