Skip to main content

Deploy AI Systems Yourself (DAISY) Kit. DaisyKit Python is the wrapper of DaisyKit SDK, an AI framework focusing on the ease of deployment.

Project description

Daisykit Python

https://pypi.org/project/daisykit/

Daisykit is an easy AI toolkit for software engineers to integrate pretrained AI models and pipelines into their projects. You DON'T need to be an AI engineer to build AI software. This open source project includes:

  • Daisykit SDK - C++, the core of models and algorithms in NCNN deep learning framework.
  • Daisykit Python wrapper for easy integration with Python.
  • Daisykit Android - Example app demonstrate how to use Daisykit SDK in Android.

How to install ?

For Windows:

pip3 install daisykit

For Ubuntu:

  • Install dependencies
sudo apt install pybind11-dev # Pybind11 - For Python/C++ Wrapper
sudo apt install libopencv-dev # For OpenCV
sudo apt install libvulkan-dev # Optional - For GPU support
  • Install DaisyKit (compile from source)
pip3 install --upgrade pip # Ensure pip is updated
pip3 install daisykit

For other platforms:

  • Install OpenCV, Pybind11 and Vulkan development package (if you want GPU support)

  • Install DaisyKit (compile from source)

pip3 install --upgrade pip # Ensure pip is updated
pip3 install daisykit

Examples

Read Documentation.

Note for Python build

Current CD (continuous delivery) flow is partial, which means we only have prebuilt linux wheels for x86_64 and for Windows.

  • Prebuilt wheels for linux x86_64 are built with Github actions.
  • Windows wheels (64bit) are built manually on a local machine.
  • macOS prebuilt wheels are not available for now. However, you can install dependencies (OpenCV, Vulkan) manually, then install Daisykit with pip command.

We will be happy if you can make a pull request to make the CD build fully automated. A good choice is using Github flow for all building tasks.

Current steps for Windows build:

bash ./build_tools/py_windows/build_dk_all_pythons_windows.sh
bash ./build_tools/py_windows/build_dk_python_source_dist.sh
bash ./build_tools/upload_pypi.sh

Bug report

Please open an issue on our official repository if you find any error.

https://github.com/DaisyLabSolutions/daisykit

Project details


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

daisykit-0.1.20220430-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (47.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

daisykit-0.1.20220430-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (21.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686

daisykit-0.1.20220430-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (47.9 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

daisykit-0.1.20220430-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (21.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686

daisykit-0.1.20220430-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (47.9 MB view details)

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

daisykit-0.1.20220430-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl (21.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686

daisykit-0.1.20220430-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (47.9 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ x86-64

daisykit-0.1.20220430-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl (21.6 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ i686

File details

Details for the file daisykit-0.1.20220430-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for daisykit-0.1.20220430-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9db708b3d60cc4549c4a55bd0e66ec93585805917418bb8e856a9407ad1de1a7
MD5 fc0ac7944fddc2a1791c95190427a247
BLAKE2b-256 97e900a11f970ebf995f0eb307a4f29bf194ba893427f64bc802edcaf562c4d6

See more details on using hashes here.

File details

Details for the file daisykit-0.1.20220430-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for daisykit-0.1.20220430-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 18d1a937d4d31c88c3aa9363772ecca46db59fd950e169613a5b8194591acf9a
MD5 69e2375e27cb7ed0942470b265cd4932
BLAKE2b-256 1c7bb99d4afc6d6aabccca6e976aec1eb2948a56521d624b8fd5a2c0c0bc2e99

See more details on using hashes here.

File details

Details for the file daisykit-0.1.20220430-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for daisykit-0.1.20220430-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 aaa870be06268a4032006c5b4d8dfd960541776a6008ab5792a3534a66a45a36
MD5 f0accb51907784ef64fd65bc914d9ead
BLAKE2b-256 08c08001d052ce1b5198a864d909c378f03667d0da1a2d2353cd96fcfdbb6317

See more details on using hashes here.

File details

Details for the file daisykit-0.1.20220430-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for daisykit-0.1.20220430-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 b8cfbe6d667a6af4b9708e68935eec88dceff810ee7ee7adda2267b8e95bc573
MD5 8e16d5c50c935b17b679946c63ec67a9
BLAKE2b-256 74bf8568dae24911bd4635f1f3e256b69366e32a7411124fdc1ba652a1f2bee0

See more details on using hashes here.

File details

Details for the file daisykit-0.1.20220430-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for daisykit-0.1.20220430-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d18c9d9766d86503e80db264aa30e89bf3807840561b808918b84b3469b13756
MD5 2be1cf6c81ac28a3e78d6bea01bb6e80
BLAKE2b-256 8fc86d40e80e9c9bef61d8792dd2017deb5b80e84aa0c3a21c1480f7c1f32bcc

See more details on using hashes here.

File details

Details for the file daisykit-0.1.20220430-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for daisykit-0.1.20220430-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 d81058cdd83bee27e413c5e8f75bdf6ddb72d10dedd3cb0cae5b39af884b8402
MD5 a5581bb4547ab34a7d659e40a1213c2f
BLAKE2b-256 b326265049f8d51ea39cc0c3ad86ada51b331579350504c51d0138eb9e1e9deb

See more details on using hashes here.

File details

Details for the file daisykit-0.1.20220430-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for daisykit-0.1.20220430-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4237a828e5c72822848ee4ddaa9e0727da3c8345c4e62784bcd80493934ab8bc
MD5 23feb14bdd70e900d1e4874384db7ec4
BLAKE2b-256 7d0443453878b5a9ebde3bac1ddc37537969c833465f2ef08504e7ad23516fe5

See more details on using hashes here.

File details

Details for the file daisykit-0.1.20220430-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for daisykit-0.1.20220430-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 17c00a0de614eab07386beab9a32076ae5e487fa591aa1b731285e649b598200
MD5 ef26d43d63fdcaa9b9c91449180d8628
BLAKE2b-256 ff26218bd1ea258927c4918e1d8c263362576cdd2b45bfeb82feec6991f7d20c

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