PanorAi
Convention-safe spherical projection and computer vision for Python.
PanorAi converts between equirectangular panoramas, gnomonic views, cubemaps, and unit rays without hiding coordinate, interpolation, support, or validity rules. NumPy is required; Torch and downstream integrations are optional.
Choose a use case
| I want to… | Start here | Stability |
|---|---|---|
| understand ERP pixels, rays, gnomonic views, cubemaps, samplers, and blenders | Projection foundations | Stable geometry; compatibility samplers |
| run a model over 6 or arbitrary-N views and reconstruct the panorama | Custom projection workflow | Stable |
| extract SIFT, ORB, or AKAZE features and match panoramas | Features and matching | Stable core |
| estimate spherical relative pose and triangulate two views | Two-view geometry | Experimental pose |
| reconstruct cameras and points from 3+ panoramas | Multiview reconstruction | Experimental |
| track a central ERP or calibrated central-fisheye sequence | Spherical visual SLAM | Experimental |
| check exact coordinates, masks, interpolation, and cubemap ties | Geometry v1 contract | Stable 3.x |
Install
pip install panorai
PanorAi supports Python 3.11–3.14 and OpenCV >=4.9,<5. Optional extras are
panorai[torch], panorai[pycolmap], panorai[slam], and panorai[pcd].
Minimal projection
import numpy as np
from panorai.geometry import GnomonicProjector, GnomonicSpec
erp_rgb = np.zeros((512, 1024, 3), dtype=np.float32) # HWC, central ERP
spec = GnomonicSpec(
center_lat_deg=10,
center_lon_deg=30,
hfov_deg=90,
vfov_deg=70,
output_shape_hw=(256, 320),
)
projector = GnomonicProjector(spec, interpolation="bilinear")
view = projector.project(erp_rgb)
restored = projector.back_project(view, output_shape_hw=erp_rgb.shape[:2])
assert view.data.shape == (256, 320, 3)
assert restored.support_mask.shape == erp_rgb.shape[:2]
ProjectionResult keeps values, geometric support, data validity, and valid
interpolation weight separate. Labels and masks use nearest sampling; floating
RGB and radial range may use bilinear sampling. Zero is data, never an implicit
invalid marker.
What PanorAi owns
| Layer | Owner |
|---|---|
| spherical coordinates, projection, masks, provenance, view orchestration | PanorAi |
| SIFT, ORB, AKAZE, BFMatcher, and FLANN implementations | OpenCV |
| spherical five-point pose and global mapper | PanorAi, Experimental |
| optional COLMAP database/SfM route | PyCOLMAP/COLMAP |
The stable contracts are panorai.geometry, the modality-aware object
workflow, the supported blenders, and the panorai.features spherical
extraction/matching core. Relative pose in panorai.estimators, PyCOLMAP
export, multiview reconstruction in panorai.reconstruction, multiscale
routing, and panorai.slam remain clearly marked Experimental.
Reference
PanorAi's distributed source is MIT licensed. Optional upstream projects and models retain their own terms; see LICENSE.
1 maintainer
Metadata
1 maintainer
Release files for panorai 3.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| panorai-3.3.1.tar.gz | 811.4 kB | With provenance | Details for panorai-3.3.1.tar.gz |
Built distributions (wheels)
Total release size: 8.8 MB
Release files / panorai-3.3.1.tar.gz
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| Tags | CPython 3.11 Linux glibc 2.24+ ARM64 Linux glibc 2.28+ ARM64 |
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| Download URL | panorai-3.3.1-cp311-cp311-macosx_11_0_arm64.whl |
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| Size | 276.5 kB |
| Tags | CPython 3.11 macOS 10.9+ x86-64 |
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