Sphere-aware operations¶
An equirectangular panorama is a rectangular storage raster for a sphere; its ordinary planar neighbourhoods are not geometrically uniform. Longitude wraps, horizontal metric scale changes with latitude, and raw pixel counts overweight polar surface area.
Surface |
Stability |
Canonical import |
Contract |
Public components or entries |
|---|---|---|---|---|
spherical-region-analysis-ops |
Stable |
panorai.ops.spherical |
panorai-spherical-region-analysis/v1 |
ConnectedComponents, FillHoles, GeodesicDistanceTransform, RegionBoundaries, Skeletonize, connected_components, extract_boundaries, fill_holes, geodesic_distance_transform, measure_regions, region_adjacency_graph, region_boundaries, skeletonize, trace_contours, watershed, panorai.ops.spherical.functional.connected_components, panorai.ops.spherical.functional.extract_boundaries, panorai.ops.spherical.functional.fill_holes, panorai.ops.spherical.functional.geodesic_distance_transform, panorai.ops.spherical.functional.measure_regions, panorai.ops.spherical.functional.region_adjacency_graph, panorai.ops.spherical.functional.region_boundaries, panorai.ops.spherical.functional.skeletonize, panorai.ops.spherical.functional.trace_contours, panorai.ops.spherical.functional.watershed |
supported-blenders |
Stable |
panorai.blenders |
panorai-blenders/v1 |
BlenderRegistry, BaseBlender, AverageBlender, FeatheringBlender, GaussianBlender, ClosestBlender, OverlapCounterBlender, OverlapStdBlender, OverlapStdFeatheredBlender, HuberBlender, average, gaussian, feathering, closest, huber, counter, std, std_feathered |
spherical-image-processing |
Experimental |
panorai.image_processing |
panorai-spherical-image-processing/v1 |
SphericalGradient, native_filter_available, reconstruct_laplacian_pyramid, spherical_bilateral_filter, spherical_box_blur, spherical_canny, spherical_equalize_histogram, spherical_filter2d, spherical_gaussian_blur, spherical_gaussian_pyramid, spherical_gradient, spherical_laplacian, spherical_laplacian_pyramid, spherical_median_blur, spherical_resize, spherical_rotate, spherical_sobel |
spherical-image-processing-slic |
Stable |
panorai.image_processing |
panorai-spherical-slic/v1 |
spherical_slic |
research-blenders |
Experimental |
panorai.blenders |
panorai-research-blenders/v1 |
HuberNoConfidenceBlender, HuberSpatialBlender, BundleAdjustmentBlender, huber_no_confidence, huber_spatial, bundle_adjustment |
spherical-core-numpy |
Experimental |
panorai.core.numpy |
panorai-core-operations/v1 |
Module, Sequential, SphericalAreaMean, SphericalAreaSum, SphericalAvgPool2d, SphericalConv2d, SphericalConvTranspose2d, SphericalFilter2d, SphericalGaussianBlur2d, SphericalGradient, SphericalLaplacian, SphericalMaxPool2d, SphericalNeighborhoodMax, SphericalNeighborhoodMin, SphericalResize, SphericalScaleExtrema, native_filter_available, spherical_bilateral_filter, spherical_box_blur, spherical_filter2d, spherical_gaussian_blur, spherical_gradient, spherical_laplacian, spherical_median_blur, spherical_resize, spherical_rotate, spherical_sobel, spherical_solid_angle_weights |
spherical-model-workflow-numpy |
Experimental |
panorai.workflow.numpy |
panorai-spherical-model-workflow/v1 |
SphericalImageModule |
spherical-ops-core |
Stable |
panorai.ops.spherical |
panorai-spherical-ops/v1 |
AreaAverage, AreaHistogram, BilateralFilter, BoxBlur, Canny, Filter2D, GaussianBlur, Gradient, Laplacian, MedianBlur, Resample, Resize, Rotate, Sobel, GaussianPyramid, LaplacianPyramid, SphericalNMS, functional, area_average, area_histogram, bilateral_filter, box_blur, canny, filter2d, gaussian_blur, gradient, laplacian, median_blur, resample, resize, rotate, sobel, panorai.ops.spherical, panorai.ops.spherical.functional.area_average, panorai.ops.spherical.functional.area_histogram, panorai.ops.spherical.functional.bilateral_filter, panorai.ops.spherical.functional.box_blur, panorai.ops.spherical.functional.canny, panorai.ops.spherical.functional.filter2d, panorai.ops.spherical.functional.gaussian_blur, panorai.ops.spherical.functional.gradient, panorai.ops.spherical.functional.laplacian, panorai.ops.spherical.functional.median_blur, panorai.ops.spherical.functional.resample, panorai.ops.spherical.functional.resize, panorai.ops.spherical.functional.rotate, panorai.ops.spherical.functional.sobel |
spherical-ops-morphology |
Stable |
panorai.ops.spherical |
panorai-spherical-morphology/v1 |
Closing, Dilate, Erode, GeodesicDisk, Opening, closing, dilate, erode, opening, panorai.ops.spherical.functional.closing, panorai.ops.spherical.functional.dilate, panorai.ops.spherical.functional.erode, panorai.ops.spherical.functional.opening |
spherical-ops-slic |
Stable |
panorai.ops.spherical |
panorai-spherical-slic/v1 |
SLIC |
spherical-ops-dog-detector |
Experimental |
panorai.ops.spherical |
panorai-spherical-dog-detector/v2 |
DoGDetector |
spherical-algorithms-general |
Stable |
panorai.ops.spherical |
panorai-spherical-ops/v1 |
Canny, GaussianPyramid, LaplacianPyramid, SphericalNMS |
spherical-algorithms-slic |
Stable |
panorai.ops.spherical |
panorai-spherical-slic/v1 |
SLIC |
spherical-algorithms-dog-detector |
Experimental |
panorai.ops.spherical |
panorai-spherical-dog-detector/v2 |
DoGDetector |
spherical-ops-auto-experimental |
Experimental |
panorai.ops.spherical |
panorai-spherical-ops/auto-experimental |
— |
Surface |
Stability |
Canonical import |
Contract |
Public components or entries |
|---|---|---|---|---|
spherical-internimage-portability |
Experimental |
panorai.experimental.deep_learning |
panorai-spherical-internimage/v1 |
DenseInternImageOutput, InternImageGAssets, InternImageGDenseClassifier, InternImageShardSpec, InternImageTermsNotAcceptedError, LoadedInternImageG, SphericalDCNv3, SphericalDCNv3Record, SphericalInternImagePortReport, acquire_internimage_g, attention_pool_class_contributions, load_pretrained_internimage_g, port_internimage_to_spherical, spherical_dcnv3_core, panorai.experimental.deep_learning.internimage.SPHERICAL_INTERNIMAGE_INTERFACE, panorai.experimental.deep_learning.internimage.INTERNIMAGE_G_REPOSITORY, panorai.experimental.deep_learning.internimage.INTERNIMAGE_G_REVISION, panorai.experimental.deep_learning.internimage.INTERNIMAGE_G_SHARDS, panorai.experimental.deep_learning.internimage.DenseInternImageOutput, panorai.experimental.deep_learning.internimage.InternImageGAssets, panorai.experimental.deep_learning.internimage.InternImageGDenseClassifier, panorai.experimental.deep_learning.internimage.InternImageShardSpec, panorai.experimental.deep_learning.internimage.InternImageTermsNotAcceptedError, panorai.experimental.deep_learning.internimage.LoadedInternImageG, panorai.experimental.deep_learning.internimage.SphericalDCNv3, panorai.experimental.deep_learning.internimage.SphericalDCNv3Record, panorai.experimental.deep_learning.internimage.SphericalInternImagePortReport, panorai.experimental.deep_learning.internimage.acquire_internimage_g, panorai.experimental.deep_learning.internimage.attention_pool_class_contributions, panorai.experimental.deep_learning.internimage.load_pretrained_internimage_g, panorai.experimental.deep_learning.internimage.port_internimage_to_spherical, panorai.experimental.deep_learning.internimage.spherical_dcnv3_core |
deep-learning-support |
Experimental |
panorai.experimental.deep_learning |
panorai-deep-learning-support/v1-experimental |
DA3Assets, DA3METRIC_LARGE, DA3TermsNotAcceptedError, DA3_CANONICAL_FOCAL_PX, DA3_CHECKPOINT_REVISION, DA3_MODEL_ID, DA3_PATCH_SIZE, DA3_SOURCE, DA3_SOURCE_COMMIT, DenseFCNOutput, DenseSemanticEvidence, ExternalArtifactRecord, ExternalArtifactSpec, IMAGENET_PROXY_VOCABULARY, INTERNIMAGE_G_REPOSITORY, INTERNIMAGE_G_REVISION, INTERNIMAGE_G_SHARDS, ImageNetFCN, ImageNetWeightRecord, LoadedDA3MetricModel, LoadedImageNetModel, LoadedSphericalDepthModel, METRIC3D_CHECKPOINT_REVISION, METRIC3D_CONVNEXT_LARGE_V1, METRIC3D_CONVNEXT_TINY_V1, METRIC3D_SOURCE, METRIC3D_SOURCE_COMMIT, Metric3DAssets, PortedLayer, SPHERICAL_DA3_METRIC_DEPTH_INTERFACE, SPHERICAL_INTERNIMAGE_INTERFACE, SPHERICAL_METRIC_DEPTH_INTERFACE, SPHERICAL_PROXY_SEGMENTATION_INTERFACE, SPHERICAL_SEMANTIC_SEGMENTATION_INTERFACE, SPHERICAL_TORCH_CONVOLUTION_INTERFACE, SUPPORTED_IMAGENET_MODELS, Sam21Assets, Sam21HieraLargeSegmenter, Sam21TermsNotAcceptedError, SemanticProxyConcept, SphericalBinaryMask, SphericalConv2d, SphericalConvTranspose2d, SphericalResizeConv2d, SphericalMaskProposal, SphericalMaskProposalSet, SphericalMaxPool2d, SphericalPortReport, SphericalProxySegmenter, SphericalSeed, SphericalSegment, SphericalSegmentationConfig, SphericalSegmentationResult, SphericalSemanticSegmenter, UpstreamTermsNotAcceptedError, acquire_metric3d_convnext_large_v1, acquire_sam21_hiera_large, class_activation_map, concept_evidence_from_imagenet, fibonacci_coverage_seeds, load_pretrained_imagenet_model, load_sam21_hiera_large, load_spherical_metric3d_convnext_large_v1, merge_proposals, port_module, port_module_with_report, prefetch_imagenet_weights, resolve_panoptic_map, select_semantic_seeds, spherical_area_average, sphericalize, mask_rcnn, panorai.experimental.deep_learning.pretrained.SUPPORTED_IMAGENET_MODELS, panorai.experimental.deep_learning.pretrained.ImageNetWeightRecord, panorai.experimental.deep_learning.pretrained.LoadedImageNetModel, panorai.experimental.deep_learning.pretrained.load_pretrained_imagenet_model, panorai.experimental.deep_learning.pretrained.prefetch_imagenet_weights |
spherical-core-torch |
Stable |
panorai.core.torch |
panorai-core-operations/v1 |
SPHERICAL_TORCH_CONVOLUTION_INTERFACE, PortedLayer, Sequential, SphericalAreaMean, SphericalAreaSum, SphericalAvgPool2d, SphericalConv2d, SphericalConvTranspose2d, SphericalResizeConv2d, SphericalFilter2d, SphericalGaussianBlur2d, SphericalGradient, SphericalLaplacian, SphericalMaxPool2d, SphericalNeighborhoodMax, SphericalNeighborhoodMin, SphericalPortReport, SphericalResize, SphericalScaleExtrema, port_module, port_module_with_report, spherical_area_average, panorai.core.torch.porting.PortedLayer, panorai.core.torch.porting.SphericalPortReport, panorai.core.torch.porting.port_module, panorai.core.torch.porting.port_module_with_report, panorai.image_processing.torch.SPHERICAL_TORCH_CONVOLUTION_INTERFACE, panorai.image_processing.torch.PortedLayer, panorai.image_processing.torch.Sequential, panorai.image_processing.torch.SphericalAreaMean, panorai.image_processing.torch.SphericalAreaSum, panorai.image_processing.torch.SphericalAvgPool2d, panorai.image_processing.torch.SphericalConv2d, panorai.image_processing.torch.SphericalConvTranspose2d, panorai.image_processing.torch.SphericalResizeConv2d, panorai.image_processing.torch.SphericalFilter2d, panorai.image_processing.torch.SphericalGaussianBlur2d, panorai.image_processing.torch.SphericalGradient, panorai.image_processing.torch.SphericalLaplacian, panorai.image_processing.torch.SphericalMaxPool2d, panorai.image_processing.torch.SphericalNeighborhoodMax, panorai.image_processing.torch.SphericalNeighborhoodMin, panorai.image_processing.torch.SphericalPortReport, panorai.image_processing.torch.SphericalResize, panorai.image_processing.torch.SphericalScaleExtrema, panorai.image_processing.torch.port_module, panorai.image_processing.torch.port_module_with_report, panorai.image_processing.torch.spherical_area_average |
spherical-model-workflow-torch |
Experimental |
panorai.workflow.torch |
panorai-spherical-model-workflow/v1 |
SphericalImageModule |
spherical-ops-torch |
Stable |
panorai.ops.spherical.nn |
panorai-spherical-ops-torch/v1 |
AdaptiveAvgPool2d, AvgPool2d, Closing, Conv2d, ConvTranspose2d, Dilate, Erode, GlobalAveragePool, Interpolate, MaxPool2d, Opening, PlanarSpatialOperationError, Resize, Rotate, SphericalConv2d, SphericalConvTranspose2d, SphericalMaxPool2d, SphericalValidationReport, ValidatedLayer, from_planar, execute_with_masks, spherical_area_average, transform_grid, transform_mask, validate |
Local tangent neighbourhoods¶
Linear filters and derivatives define taps in a local east/north tangent frame at each output bearing, transport those taps to the sphere and sample the ERP with longitude wrapping. The operation therefore keeps an angular meaning across latitude instead of applying the same planar pixel offsets everywhere.
Nonlinear operations follow the same domain contract. Median and bilateral filters use geodesic neighbourhoods; Canny performs tangent-direction suppression and seam-aware connectivity; area reductions weight latitude bands by solid angle.
Functions, configured objects and layers¶
Functional calls are convenient for one expression. Immutable operation
objects add parameter inspection, transform_grid and safe Pipeline
composition. Optional Torch layers extend the same spatial contract to learned
convolution, pooling and interpolation while preserving autograd.
Grid and mask transforms are part of the operation¶
A spatial operation transforms values, geometric support, data validity and grid identity together. Strict validity propagation is the default. Renormalization exists only where a normalized mathematical formula is defined, such as averaging or Gaussian weighting; arbitrary learned weights cannot be reinterpreted as valid-weight averages.
Sphere-native does not always mean preferable¶
Projected-view processing remains appropriate for existing pinhole algorithms and models. The choice is architectural: direct operations avoid face boundaries and fusion, while projected views reuse mature planar components. Pipeline can combine both routes without changing geometry conventions.
See the Spherical Ops tutorial and Operations API.