Spectacular AI SDK for OAK (Depth AI)

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for spectacularAI from gravatar.com spectacularAI

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Free for non-commercial use (Free for non-commercial use)
  • Author: Spectacular AI Ltd
  • Tags vio, slam
  • Requires: Python >=3
Classifiers

Project description

The SDK performs 6-DoF pose tracking based on visual-inertial odometry (VIO), 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 (C++ version), CPU architectures (ARM) and commercial licensing options, contact us at https://www.spectacularai.com

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for spectacularAI from gravatar.com spectacularAI

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Free for non-commercial use (Free for non-commercial use)
  • Author: Spectacular AI Ltd
  • Tags vio, slam
  • Requires: Python >=3
Classifiers

Release history Release notifications | RSS feed

1.37.0

1.36.0

1.35.0

1.34.0

1.33.0

1.32.0

1.31.0

1.30.0

1.29.0

1.28.0

1.27.0

1.26.2

1.26.1

1.25.1

1.25.0

1.24.1

1.24.0

1.23.1

1.23.0

1.22.1

1.22.0

1.21.0

1.20.0

1.19.1

1.19.0

1.18.2

1.18.1

1.16.1

1.16.0

1.15.0

1.14.0

1.13.1

1.12.1

1.12.0

1.11.0

1.10.0

1.9.0

1.8.0

1.7.0

1.6.0

1.5.0

1.4.0

1.3.0

1.2.0

1.1.1

1.1.0

1.0.0

0.23.0

0.22.0

0.21.0

0.20.1

0.20.0

0.19.0

0.18.0

0.17.2

0.17.0

0.16.0

This version

0.15.0

0.14.0

0.13.0

0.12.1

0.12.0

0.11.0

0.10.0

0.9.0

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

spectacularAI-0.15.0-cp310-cp310-win_amd64.whl (2.8 MB view details)

Uploaded CPython 3.10 Windows x86-64

spectacularAI-0.15.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

spectacularAI-0.15.0-cp39-cp39-win_amd64.whl (2.8 MB view details)

Uploaded CPython 3.9 Windows x86-64

spectacularAI-0.15.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

spectacularAI-0.15.0-cp38-cp38-win_amd64.whl (2.8 MB view details)

Uploaded CPython 3.8 Windows x86-64

spectacularAI-0.15.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

spectacularAI-0.15.0-cp37-cp37m-win_amd64.whl (2.8 MB view details)

Uploaded CPython 3.7m Windows x86-64

spectacularAI-0.15.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

File details

Details for the file spectacularAI-0.15.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: spectacularAI-0.15.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 2.8 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.5

File hashes

Hashes for spectacularAI-0.15.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 1d9998c81113d99817d998da27e45ccba82521a73fca1549a30061f2fe08a3fa
MD5 de83623a275b1c2e70a7091cf065cbf0
BLAKE2b-256 877d5c3e167b61c9845f4be2f317413c0061c652740d024e257271a76f17b2c2

See more details on using hashes here.

File details

Details for the file spectacularAI-0.15.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for spectacularAI-0.15.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8d3620b1f49c825b2295486baf7fcacd4ce036edf9b5d13b030522891d96ced5
MD5 75a39e0eb99dd3246a44d6a6f1300134
BLAKE2b-256 0de88282211bfc7aac94a8d7c21dfc4a4f63e54ac0c6a8b5093afc9f81237988

See more details on using hashes here.

File details

Details for the file spectacularAI-0.15.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: spectacularAI-0.15.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 2.8 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.5

File hashes

Hashes for spectacularAI-0.15.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 d034b275c48bc7fced31127e35a9af1ab2966d4a8e56796cd79817c106483b66
MD5 8870058b6960cce08424e3a50709a50f
BLAKE2b-256 3b58705e41bb0582eaebafefbbfd05ed9019e0e0bc1f82fa40a589c8c2074eda

See more details on using hashes here.

File details

Details for the file spectacularAI-0.15.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for spectacularAI-0.15.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8a59fbdc395f4299202569d466eda79de618f57da2d39dacaec8ba07d267cb39
MD5 e73802daf1a41c241c3ae9a89a4de50c
BLAKE2b-256 799eb9e31d40714098bcae6a87b7de674e3866e34e24117e223629bccd1c2ffa

See more details on using hashes here.

File details

Details for the file spectacularAI-0.15.0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: spectacularAI-0.15.0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 2.8 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.5

File hashes

Hashes for spectacularAI-0.15.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 07f86160bcd00183c4ef7fc5ea400ec33f081b82490f82bad240b3c33af5f8c4
MD5 805ae3b9b24ad00d4c4ed9991b968f68
BLAKE2b-256 21d63d771e6f34e587a7517e3461ac96f889bb8c8dd384fec959ab61c0741f9f

See more details on using hashes here.

File details

Details for the file spectacularAI-0.15.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for spectacularAI-0.15.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 47c34aa47e24174da66269b88d3ab7b2f9d7c497e79bceb0c8c96487899b87d5
MD5 ba2977ea151803cafc44ff21214b79d1
BLAKE2b-256 0dedec49ea5e0ed069d4f32f9432a7bc213ed5ae87f25e6407f29752d6d494c9

See more details on using hashes here.

File details

Details for the file spectacularAI-0.15.0-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: spectacularAI-0.15.0-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 2.8 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.5

File hashes

Hashes for spectacularAI-0.15.0-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 50126e3ae773c77976ea83ba048b18eaf5631df936d27d15a3e618960b6f063f
MD5 01a8bf9a69cf1c65473fac7c720619c3
BLAKE2b-256 40b22416cb046525e635959c7ab398f8dad860cb72601a84e87060409b2dbf20

See more details on using hashes here.

File details

Details for the file spectacularAI-0.15.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for spectacularAI-0.15.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8560111e00d2de74ca6484e1f26781643d7311ff5846b796ee6a8dbcdd4fd6a4
MD5 1d6bf80e84af3a12b40a652ce9e23d0d
BLAKE2b-256 b7235c54c303caeec0ca28dfc812be2cb72f9dfa54951f7d8223de24825a4d5d

See more details on using hashes here.

Supported by

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