Module: Gsplat::Math::CameraProjection

Defined in:
lib/gsplat/math/camera_projection.rb

Overview

Camera-space transformation and pinhole Gaussian projection primitives.

Class Method Summary collapse

Class Method Details

.distorted_proj(means, covars, intrinsics, camera_model, radial_coeffs: nil, tangential_coeffs: nil, thin_prism_coeffs: nil) ⇒ Object

rubocop:disable Metrics/ParameterLists



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# File 'lib/gsplat/math/camera_projection.rb', line 76

def distorted_proj(means, covars, intrinsics, camera_model, radial_coeffs: nil,
                   tangential_coeffs: nil, thin_prism_coeffs: nil)
  # rubocop:enable Metrics/ParameterLists
  camera_count = means.shape[0]
  gaussian_count = means.shape[1]
  means2d = means.class.zeros(camera_count, gaussian_count, 2)
  covars2d = means.class.zeros(camera_count, gaussian_count, 2, 2)
  camera_count.times do |camera_index|
    projected, jacobians = CameraDistortion.project_camera(
      means[camera_index, true, true],
      intrinsics[camera_index, true, true],
      camera_model,
      radial: radial_coeffs && radial_coeffs[camera_index, true].to_a,
      tangential: tangential_coeffs && tangential_coeffs[camera_index, true].to_a,
      thin_prism: thin_prism_coeffs && thin_prism_coeffs[camera_index, true].to_a
    )
    means2d[camera_index, true, true] = projected
    transformed = Mat.matmul_batch(jacobians, covars[camera_index, true, true, true])
    covars2d[camera_index, true, true, true] = Mat.matmul_batch(
      transformed,
      jacobians.transpose(0, 2, 1)
    )
  end
  [means2d, covars2d]
end

.ortho_camera(means, intrinsics) ⇒ Object 



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# File 'lib/gsplat/math/camera_projection.rb', line 191

def ortho_camera(means, intrinsics)
  jacobians = means.class.zeros(means.shape[0], 2, 3)
  jacobians[true, 0, 0] = intrinsics[0, 0]
  jacobians[true, 1, 1] = intrinsics[1, 1]
  means2d = means.class.zeros(means.shape[0], 2)
  means2d[true, 0] = (means[true, 0] * intrinsics[0, 0]) + intrinsics[0, 2]
  means2d[true, 1] = (means[true, 1] * intrinsics[1, 1]) + intrinsics[1, 2]
  [means2d, jacobians]
end

.ortho_proj(means, covars, intrinsics, width, height) ⇒ Object 



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# File 'lib/gsplat/math/camera_projection.rb', line 54

def ortho_proj(means, covars, intrinsics, width, height)
  means, covars, intrinsics = validate_projection_inputs(means, covars, intrinsics, width, height)
  camera_count = means.shape[0]
  gaussian_count = means.shape[1]
  means2d = means.class.zeros(camera_count, gaussian_count, 2)
  covars2d = means.class.zeros(camera_count, gaussian_count, 2, 2)
  camera_count.times do |camera_index|
    projected_means, jacobians = ortho_camera(
      means[camera_index, true, true],
      intrinsics[camera_index, true, true]
    )
    means2d[camera_index, true, true] = projected_means
    transformed = Mat.matmul_batch(jacobians, covars[camera_index, true, true, true])
    covars2d[camera_index, true, true, true] = Mat.matmul_batch(
      transformed,
      jacobians.transpose(0, 2, 1)
    )
  end
  [means2d, covars2d]
end

.persp_proj(means, covars, intrinsics, width, height) ⇒ Object 



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# File 'lib/gsplat/math/camera_projection.rb', line 30

def persp_proj(means, covars, intrinsics, width, height)
  means, covars, intrinsics = validate_projection_inputs(means, covars, intrinsics, width, height)
  camera_count = means.shape[0]
  gaussian_count = means.shape[1]
  means2d = means.class.zeros(camera_count, gaussian_count, 2)
  covars2d = means.class.zeros(camera_count, gaussian_count, 2, 2)
  camera_count.times do |camera_index|
    projected_means, jacobians = pinhole_camera(
      means[camera_index, true, true],
      intrinsics[camera_index, true, true],
      width,
      height
    )
    means2d[camera_index, true, true] = projected_means
    covariance = covars[camera_index, true, true, true]
    transformed = Mat.matmul_batch(jacobians, covariance)
    covars2d[camera_index, true, true, true] = Mat.matmul_batch(
      transformed,
      jacobians.transpose(0, 2, 1)
    )
  end
  [means2d, covars2d]
end

.pinhole_camera(means, intrinsics, width, height) ⇒ Object

rubocop:disable Metrics/AbcSize



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# File 'lib/gsplat/math/camera_projection.rb', line 147

def pinhole_camera(means, intrinsics, width, height)
  x_coord = means[true, 0]
  y_coord = means[true, 1]
  z_coord = means[true, 2]
  focal_x = intrinsics[0, 0]
  focal_y = intrinsics[1, 1]
  center_x = intrinsics[0, 2]
  center_y = intrinsics[1, 2]
  clipped_x = clip_ratio(
    x_coord / z_coord,
    -((center_x / focal_x) + (0.15 * width / focal_x)),
    ((width - center_x) / focal_x) + (0.15 * width / focal_x)
  ) * z_coord
  clipped_y = clip_ratio(
    y_coord / z_coord,
    -((center_y / focal_y) + (0.15 * height / focal_y)),
    ((height - center_y) / focal_y) + (0.15 * height / focal_y)
  ) * z_coord
  jacobians = means.class.zeros(means.shape[0], 2, 3)
  jacobians[true, 0, 0] = focal_x / z_coord
  jacobians[true, 0, 2] = -focal_x * clipped_x / (z_coord**2)
  jacobians[true, 1, 1] = focal_y / z_coord
  jacobians[true, 1, 2] = -focal_y * clipped_y / (z_coord**2)
  homogeneous_x = (intrinsics[0, 0] * x_coord) + (intrinsics[0, 1] * y_coord) +
                  (intrinsics[0, 2] * z_coord)
  homogeneous_y = (intrinsics[1, 0] * x_coord) + (intrinsics[1, 1] * y_coord) +
                  (intrinsics[1, 2] * z_coord)
  means2d = means.class.zeros(means.shape[0], 2)
  means2d[true, 0] = homogeneous_x / z_coord
  means2d[true, 1] = homogeneous_y / z_coord
  [means2d, jacobians]
end

.world_to_cam(means, covars, viewmats) ⇒ Object 



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# File 'lib/gsplat/math/camera_projection.rb', line 9

def world_to_cam(means, covars, viewmats)
  means, covars, viewmats = validate_world_inputs(means, covars, viewmats)
  camera_count = viewmats.shape[0]
  gaussian_count = means.shape[0]
  camera_means = means.class.zeros(camera_count, gaussian_count, 3)
  camera_covars = means.class.zeros(camera_count, gaussian_count, 3, 3)
  camera_count.times do |camera_index|
    rotation = viewmats[camera_index, 0...3, 0...3]
    translation = viewmats[camera_index, 0...3, 3]
    rotation_batch = means.class.zeros(gaussian_count, 3, 3)
    rotation_batch[true, true, true] = rotation
    camera_means[camera_index, true, true] = means.dot(rotation.transpose) + translation
    rotated = Mat.matmul_batch(rotation_batch, covars)
    camera_covars[camera_index, true, true, true] = Mat.matmul_batch(
      rotated,
      rotation_batch.transpose(0, 2, 1)
    )
  end
  [camera_means, camera_covars]
end