Skip to main content

Spectacular AI Python library

Project description

The SDK performs 6-DoF pose tracking based on visual-inertial SLAM (VISLAM), the fusion of camera and IMU data. See https://github.com/SpectacularAI/sdk-examples for more information.

License

Free for non-commercial use.

A list of 3rd party copyright notices that should be included in redistributions is provided as the LICENSE.txt file in the Python Wheels.

For more alternatives (custom devices), CPU architectures (ARM) and commercial licensing options, contact us at https://www.spectacularai.com

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

spectacularai-1.40.1-cp312-cp312-win_amd64.whl (8.0 MB view details)

Uploaded CPython 3.12Windows x86-64

spectacularai-1.40.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.7 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64

spectacularAI-1.40.1-cp311-cp311-win_amd64.whl (8.0 MB view details)

Uploaded CPython 3.11Windows x86-64

spectacularAI-1.40.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.7 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

spectacularAI-1.40.1-cp310-cp310-win_amd64.whl (8.0 MB view details)

Uploaded CPython 3.10Windows x86-64

spectacularAI-1.40.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.7 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

spectacularAI-1.40.1-cp39-cp39-win_amd64.whl (8.0 MB view details)

Uploaded CPython 3.9Windows x86-64

spectacularAI-1.40.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.7 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

spectacularAI-1.40.1-cp38-cp38-win_amd64.whl (8.0 MB view details)

Uploaded CPython 3.8Windows x86-64

spectacularAI-1.40.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.7 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

File details

Details for the file spectacularai-1.40.1-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for spectacularai-1.40.1-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 63c4544ef92873246abaa1e44a3f91a51867b3e1f1f077b9278c2c0b6b0c2c25
MD5 ba8b6c752fec43cb280d9c88014a00df
BLAKE2b-256 48d4f247e83a100053504fc451afd66ec23bda1675a94959175ec27a9f4b560d

See more details on using hashes here.

File details

Details for the file spectacularai-1.40.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for spectacularai-1.40.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5bb0d0cb909c40c9d83f12bd1891a8c7e604bac3b928ffc82d966c0e097a3196
MD5 db829a9f72694c316500fe6614dca7e1
BLAKE2b-256 e2d03b73b16bfac1ab512d4b0bd14e02ca1a18cb303a50658078226dc88a702d

See more details on using hashes here.

File details

Details for the file spectacularAI-1.40.1-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for spectacularAI-1.40.1-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 da1e819cef859dd9ae798be99d4cd06a7b1f801235eda0f0a527d4e20e1e83b0
MD5 0a06c0a70321dc73dec8467a7a8ef454
BLAKE2b-256 09c93b91a891c33da6885e61b57f9b3ac21ef2dc995d004c51714a0e4bf7781f

See more details on using hashes here.

File details

Details for the file spectacularAI-1.40.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for spectacularAI-1.40.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c00d12df3eae087d57f2c63b7689705a4f355efcd4729cf4dc86083cfe9f1cd9
MD5 52d471b370d065af071f26f8bc312f5b
BLAKE2b-256 ad5fbbf2eb6cab2956329f3a338bbf4cf4659bd125fd20eacd574b9201d4735f

See more details on using hashes here.

File details

Details for the file spectacularAI-1.40.1-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for spectacularAI-1.40.1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 22354b951005b69e41733eb5ab3c4c2217ad3d21a362a2fb2d8ae0cb5df43d40
MD5 f96754ce43d905e6e9a24c8d690b2df3
BLAKE2b-256 70087e07777bfd8e4e26d7975fcb4834555b7c012d6d1e7bcb6025561f7d8e01

See more details on using hashes here.

File details

Details for the file spectacularAI-1.40.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for spectacularAI-1.40.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7dfde0768a83ea370940a0c9768b427d5c1647650548d9aca4455691dbc9cfe0
MD5 2467150172bb056625454dc59403a8f5
BLAKE2b-256 7a4f110d25cee00a1d548bec76c3833722310d9ed305841677a8eee55965985e

See more details on using hashes here.

File details

Details for the file spectacularAI-1.40.1-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for spectacularAI-1.40.1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 290c3e4bea00571ceb549657d1fda0976a76d14e8e4e8e9cc070bcaf8f9f621a
MD5 2d1a50e8852368bea7159e9a4086f89f
BLAKE2b-256 e49a5e835309b61f69db4ade5d27735db4885397a1ea98da4a14864b405cefb6

See more details on using hashes here.

File details

Details for the file spectacularAI-1.40.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for spectacularAI-1.40.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 35dc058996ad60ebf9214b2e12f970a0e6e0c13de85729ff006effbc0d92e92c
MD5 192ba8171a4ae691413d30b875b94145
BLAKE2b-256 389d0272e7b24a8e469526455d0b46d866e1b12c2129fcc721f43f0daafdc94f

See more details on using hashes here.

File details

Details for the file spectacularAI-1.40.1-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for spectacularAI-1.40.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 cc339a33d0bfa7abde7eefd6cc522171efc0b28d8a3c9a6bb9e1c3a403bd1b58
MD5 2bfae871c34bf5353ee02fe18d6f4d40
BLAKE2b-256 424da2ebaf629d41fe169dbc41b7e646f026eeb5d45f0804a00562bde85e8a38

See more details on using hashes here.

File details

Details for the file spectacularAI-1.40.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for spectacularAI-1.40.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f1af144f42bdc545b5c8a6f3333b1536b22731434d961bea94585462e4ff52d9
MD5 136c0d14a6586fdc81a584dbfb0fbb77
BLAKE2b-256 5be054aebad87ee74310730e590f9c3db63fdee5a2d22f5d6d66e5fa1b68d642

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page