Collection of Docker images for ML/DL and video processing projects

Overview

dokai-logo

Build and push Generic badge

Collection of Docker images for ML/DL and video processing projects.

Overview of images

Three types of images differ by tag postfix:

  • base: Python with ML and CV packages, CUDA (11.4.2), cuDNN (8.2.4), FFmpeg (4.4) with NVENC support
  • pytorch: PyTorch (1.10.0-rc1), torchvision (0.10.1), torchaudio (0.9.1) and torch based libraries
  • tensor-stream: Tensor Stream for real-time video streams decoding on GPU

Example

Pull an image

docker pull ghcr.io/osai-ai/dokai:21.09-pytorch

Docker Hub mirror

docker pull osaiai/dokai:21.09-pytorch

Check available GPUs inside container

docker run --rm \
    --gpus=all \
    ghcr.io/osai-ai/dokai:21.09-pytorch \
    nvidia-smi

Example of using dokai image for DL pipeline you can find here.

Versions

base

dokai:20.09-base

ghcr.io/osai-ai/dokai:20.09-base

FFmpeg (release/4.3), nv-codec-headers (sdk/9.1)
Python (3.6.9)

pip==20.2.3
setuptools==50.3.0
packaging==20.4
numpy==1.19.2
opencv-python==4.4.0.42
scipy==1.5.2
matplotlib==3.3.2
pandas==1.1.2
notebook==6.1.4
scikit-learn==0.23.2
scikit-image==0.17.2
albumentations==0.4.6
Cython==0.29.21
Pillow==7.2.0
trafaret-config==2.0.2
pyzmq==19.0.2
librosa==0.8.0
psutil==5.7.2
dataclasses==0.7

dokai:20.10-base

ghcr.io/osai-ai/dokai:20.10-base

FFmpeg (release/4.3), nv-codec-headers (sdk/9.1)
Python (3.6.9)

pip==20.2.4
setuptools==50.3.2
packaging==20.4
numpy==1.19.2
opencv-python==4.4.0.44
scipy==1.5.3
matplotlib==3.3.2
pandas==1.1.3
notebook==6.1.4
scikit-learn==0.23.2
scikit-image==0.17.2
albumentations==0.5.0
Cython==0.29.21
Pillow==8.0.0
trafaret-config==2.0.2
pyzmq==19.0.2
librosa==0.8.0
psutil==5.7.2
dataclasses==0.7
pydantic==1.6.1
requests==2.24.0

dokai:20.12-base

ghcr.io/osai-ai/dokai:20.12-base

CUDA (11.1), cuDNN (8.0.5)
FFmpeg (release/4.3), nv-codec-headers (sdk/9.1)
Python (3.8.5)

pip==20.3.3
setuptools==51.0.0
packaging==20.8
numpy==1.19.4
opencv-python==4.4.0.46
scipy==1.5.4
matplotlib==3.3.3
pandas==1.1.5
notebook==6.1.5
scikit-learn==0.23.2
scikit-image==0.18.0
albumentations==0.5.2
Cython==0.29.21
Pillow==8.0.1
trafaret-config==2.0.2
pyzmq==20.0.0
librosa==0.8.0
psutil==5.8.0
pydantic==1.7.3
requests==2.25.1

dokai:21.01-base

ghcr.io/osai-ai/dokai:21.01-base

CUDA (11.1.1), cuDNN (8.0.5)
FFmpeg (release/4.3), nv-codec-headers (sdk/10.0)
Python (3.8.5)

pip==20.3.3
setuptools==51.3.3
packaging==20.8
numpy==1.19.5
opencv-python==4.5.1.48
scipy==1.6.0
matplotlib==3.3.3
pandas==1.2.0
notebook==6.2.0
scikit-learn==0.24.1
scikit-image==0.18.1
albumentations==0.5.2
Cython==0.29.21
Pillow==8.1.0
trafaret-config==2.0.2
pyzmq==21.0.1
librosa==0.8.0
psutil==5.8.0
pydantic==1.7.3
requests==2.25.1

dokai:21.02-base

ghcr.io/osai-ai/dokai:21.02-base

CUDA (11.2.1), cuDNN (8.1.0)
FFmpeg (release/4.3), nv-codec-headers (sdk/10.0)
Python (3.8.5)

pip==21.0.1
setuptools==53.0.0
packaging==20.9
numpy==1.20.1
opencv-python==4.5.1.48
scipy==1.6.1
matplotlib==3.3.4
pandas==1.2.2
scikit-learn==0.24.1
scikit-image==0.18.1
Pillow==8.1.0
librosa==0.8.0
albumentations==0.5.2
pyzmq==22.0.3
Cython==0.29.22
numba==0.52.0
requests==2.25.1
psutil==5.8.0
trafaret-config==2.0.2
pydantic==1.7.3
PyYAML==5.4.1
notebook==6.2.0
ipywidgets==7.6.3
tqdm==4.57.0
pytest==6.2.2
mypy==0.812
flake8==3.8.4

dokai:21.03-base

ghcr.io/osai-ai/dokai:21.03-base

CUDA (11.2.2), cuDNN (8.1.1)
FFmpeg (release/4.4), nv-codec-headers (sdk/10.0)
Python (3.8.5)

pip==21.0.1
setuptools==54.2.0
packaging==20.9
numpy==1.20.1
opencv-python==4.5.1.48
scipy==1.6.1
matplotlib==3.3.4
pandas==1.2.3
scikit-learn==0.24.1
scikit-image==0.18.1
Pillow==8.1.2
librosa==0.8.0
albumentations==0.5.2
pyzmq==22.0.3
Cython==0.29.22
numba==0.53.0
requests==2.25.1
psutil==5.8.0
trafaret-config==2.0.2
pydantic==1.8.1
PyYAML==5.4.1
notebook==6.3.0
ipywidgets==7.6.3
tqdm==4.59.0
pytest==6.2.2
mypy==0.812
flake8==3.9.0

dokai:21.05-base

ghcr.io/osai-ai/dokai:21.05-base

CUDA (11.3), cuDNN (8.2.0)
FFmpeg (release/4.4), nv-codec-headers (sdk/10.0)
Python (3.8.5)

pip==21.1.1
setuptools==56.2.0
packaging==20.9
numpy==1.20.3
opencv-python==4.5.2.52
scipy==1.6.3
matplotlib==3.4.2
pandas==1.2.4
scikit-learn==0.24.2
scikit-image==0.18.1
Pillow==8.2.0
librosa==0.8.0
albumentations==0.5.2
pyzmq==22.0.3
Cython==0.29.23
numba==0.53.1
requests==2.25.1
psutil==5.8.0
trafaret-config==2.0.2
pydantic==1.8.1
PyYAML==5.4.1
notebook==6.3.0
ipywidgets==7.6.3
tqdm==4.60.0
pytest==6.2.4
mypy==0.812
flake8==3.9.2

dokai:21.07-base

ghcr.io/osai-ai/dokai:21.07-base

CUDA (11.3.1), cuDNN (8.2.0)
FFmpeg (release/4.4), nv-codec-headers (sdk/10.0)
Python (3.8.10)

pip==21.1.3
setuptools==57.0.0
packaging==20.9
numpy==1.21.0
opencv-python==4.5.2.54
scipy==1.7.0
matplotlib==3.4.2
pandas==1.2.5
scikit-learn==0.24.2
scikit-image==0.18.2
Pillow==8.2.0
librosa==0.8.1
albumentations==1.0.0
pyzmq==22.1.0
Cython==0.29.23
numba==0.53.1
requests==2.25.1
psutil==5.8.0
trafaret-config==2.0.2
pydantic==1.8.2
PyYAML==5.4.1
notebook==6.4.0
ipywidgets==7.6.3
tqdm==4.61.1
pytest==6.2.4
mypy==0.910
flake8==3.9.2

dokai:21.08-base

ghcr.io/osai-ai/dokai:21.08-base

CUDA (11.4.1), cuDNN (8.2.2)
FFmpeg (release/4.4), nv-codec-headers (sdk/11.0)
Python (3.8.10)

pip==21.2.3
setuptools==57.4.0
packaging==21.0
numpy==1.21.1
opencv-python==4.5.3.56
scipy==1.7.1
matplotlib==3.4.2
pandas==1.3.1
scikit-learn==0.24.2
scikit-image==0.18.2
Pillow==8.3.1
librosa==0.8.1
albumentations==1.0.3
pyzmq==22.2.1
Cython==0.29.24
numba==0.53.1
requests==2.26.0
psutil==5.8.0
pydantic==1.8.2
PyYAML==5.4.1
notebook==6.4.3
ipywidgets==7.6.3
tqdm==4.62.0
pytest==6.2.4
mypy==0.910
flake8==3.9.2

dokai:21.09-base

ghcr.io/osai-ai/dokai:21.09-base

CUDA (11.4.2), cuDNN (8.2.4)
FFmpeg (release/4.4), nv-codec-headers (sdk/11.0)
Python (3.8.10)

pip==21.2.4
setuptools==58.1.0
packaging==21.0
numpy==1.21.2
opencv-python==4.5.3.56
scipy==1.7.1
matplotlib==3.4.3
pandas==1.3.3
scikit-learn==1.0
scikit-image==0.18.3
Pillow==8.3.2
librosa==0.8.1
albumentations==1.0.3
pyzmq==22.3.0
Cython==0.29.24
numba==0.53.1
requests==2.26.0
psutil==5.8.0
pydantic==1.8.2
PyYAML==5.4.1
notebook==6.4.4
ipywidgets==7.6.5
tqdm==4.62.3
pytest==6.2.5
mypy==0.910
flake8==3.9.2

pytorch

dokai:20.09-pytorch

ghcr.io/osai-ai/dokai:20.09-pytorch

additionally to dokai:20.09-base:

torch==1.6.0
torchvision==0.7.0
pytorch-argus==0.1.2
timm==0.2.1
apex (master)

dokai:20.10-pytorch

ghcr.io/osai-ai/dokai:20.10-pytorch

additionally to dokai:20.10-base:

torch==1.6.0
torchvision==0.7.0
pytorch-argus==0.1.2
timm==0.2.1
apex (master)

dokai:20.12-pytorch

ghcr.io/osai-ai/dokai:20.12-pytorch

additionally to dokai:20.12-base:

torch==1.7.1 (source, v1.7.1 tag)
torchvision==0.8.2 (source, v0.8.2 tag)
pytorch-argus==0.2.0
timm==0.3.2
kornia==0.4.1
apex (source, master branch)

dokai:21.01-pytorch

ghcr.io/osai-ai/dokai:21.01-pytorch

additionally to dokai:21.01-base:

torch==1.8.0a0+4aea007 (source, master branch)
torchvision==0.8.2 (source, v0.8.2 tag)
pytorch-argus==0.2.0
timm==0.3.4
kornia==0.4.1
apex (source, master branch)

dokai:21.02-pytorch

ghcr.io/osai-ai/dokai:21.02-pytorch

additionally to dokai:21.02-base:

torch==1.9.0a0+c2b9283 (source, master branch)
torchvision==0.8.2 (source, v0.8.2 tag)
pytorch-argus==0.2.0
timm==0.4.4 (source, master branch)
kornia==0.4.1
pretrainedmodels==0.7.4
efficientnet-pytorch==0.7.0
segmentation-models-pytorch==0.1.3
apex (source, master branch)

dokai:21.03-pytorch

ghcr.io/osai-ai/dokai:21.03-pytorch

additionally to dokai:21.03-base:

torch==1.8.0 (source, v1.8.0 tag)
torchvision==0.9.0 (source, v0.9.0 tag)
torchaudio==0.8.0 (source, v0.8.0 tag)
pytorch-argus==0.2.1
timm==0.4.5
kornia==0.5.0
pretrainedmodels==0.7.4
efficientnet-pytorch==0.7.0
segmentation-models-pytorch==0.1.3
apex (source, master branch)

dokai:21.05-pytorch

ghcr.io/osai-ai/dokai:21.05-pytorch

additionally to dokai:21.05-base:

torch==1.8.1 (source, v1.8.1 tag)
torchvision==0.9.1 (source, v0.9.1 tag)
torchaudio==0.8.1 (source, v0.8.1 tag)
pytorch-argus==0.2.1
timm==0.4.8 (source, master branch)
kornia==0.5.1
pretrainedmodels==0.7.4
efficientnet-pytorch==0.7.1
segmentation-models-pytorch==0.1.3
apex (source, master branch)

dokai:21.07-pytorch

ghcr.io/osai-ai/dokai:21.07-pytorch

additionally to dokai:21.07-base:

torch==1.9.0 (source, v1.9.0 tag)
torchvision==0.10.0 (source, v0.10.0 tag)
torchaudio==0.9.0 (source, v0.9.0 tag)
pytorch-argus==0.2.1
pretrainedmodels==0.7.4
efficientnet-pytorch==0.7.1
timm==0.4.12
segmentation-models-pytorch==0.1.3
kornia==0.5.5
apex (source, master branch)

dokai:21.08-pytorch

ghcr.io/osai-ai/dokai:21.08-pytorch

additionally to dokai:21.08-base:

MAGMA (2.6.1)

torch==1.10.0a0+git5b8389e (source, master branch)
torchvision==0.10.0 (source, v0.10.0 tag)
torchaudio==0.9.0 (source, v0.9.0 tag)
pytorch-ignite==0.4.6
pytorch-argus==0.2.1
pretrainedmodels==0.7.4
efficientnet-pytorch==0.7.1
timm==0.4.12
segmentation-models-pytorch==0.2.0
kornia==0.5.8
apex (source, master branch)

dokai:21.09-pytorch

ghcr.io/osai-ai/dokai:21.09-pytorch

additionally to dokai:21.09-base:

MAGMA (2.6.1)

torch==1.10.0-rc1 (source, v1.10.0-rc1 tag)
torchvision==0.10.1 (source, v0.10.1 tag)
torchaudio==0.9.1 (source, v0.9.1 tag)
pytorch-ignite==0.4.6
pytorch-argus==0.2.1
pretrainedmodels==0.7.4
efficientnet-pytorch==0.7.1
timm==0.4.12
segmentation-models-pytorch==0.2.0
kornia==0.5.11
apex (source, master branch)

tensor-stream

dokai:20.09-tensor-stream

ghcr.io/osai-ai/dokai:20.09-tensor-stream

additionally to dokai:20.09-pytorch:

tensor-stream==0.4.6 (dev)

dokai:20.10-tensor-stream

ghcr.io/osai-ai/dokai:20.10-tensor-stream

additionally to dokai:20.10-pytorch:

tensor-stream==0.4.6 (dev)

dokai:20.12-tensor-stream

ghcr.io/osai-ai/dokai:20.12-tensor-stream

additionally to dokai:20.12-pytorch:

tensor-stream==0.4.6 (source, dev branch)

dokai:21.01-tensor-stream

ghcr.io/osai-ai/dokai:21.01-tensor-stream

additionally to dokai:21.01-pytorch:

tensor-stream==0.4.6 (source, dev branch)

dokai:21.02-tensor-stream

ghcr.io/osai-ai/dokai:21.02-tensor-stream

additionally to dokai:21.02-pytorch:

tensor-stream==0.4.6 (source, dev branch)

dokai:21.03-tensor-stream

ghcr.io/osai-ai/dokai:21.03-tensor-stream

additionally to dokai:21.03-pytorch:

tensor-stream==0.4.6 (source, dev branch)

dokai:21.05-tensor-stream

ghcr.io/osai-ai/dokai:21.05-tensor-stream

additionally to dokai:21.05-pytorch:

tensor-stream==0.4.6 (source, dev branch)

dokai:21.07-tensor-stream

ghcr.io/osai-ai/dokai:21.07-tensor-stream

additionally to dokai:21.07-pytorch:

tensor-stream==0.4.6 (source, dev branch)

dokai:21.08-tensor-stream

ghcr.io/osai-ai/dokai:21.08-tensor-stream

additionally to dokai:21.08-pytorch:

tensor-stream==0.4.6 (source, dev branch)

dokai:21.09-tensor-stream

ghcr.io/osai-ai/dokai:21.09-tensor-stream

additionally to dokai:21.09-pytorch:

tensor-stream==0.4.6 (source, dev branch)

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Comments
  • Does not work `torchaudio.transforms.MelSpectrogram`, no MKL

    Does not work `torchaudio.transforms.MelSpectrogram`, no MKL

    I used docker pulled from ghcr.io/osai-ai/dokai:21.05-pytorch.

    The following code gives an error:

    python -c 'import torchaudio; import torch; a = torch.randn(2, 4663744); torchaudio.transforms.MelSpectrogram(44100)(a)'

    /usr/local/lib/python3.8/dist-packages/torchaudio-0.8.0a0+e4e171a-py3.8-linux-x86_64.egg/torchaudio/functional/functional.py:357: UserWarning: At least one mel filterbank has all zero values. The value for `n_mels` (128) may be set too high. Or, the value for `n_freqs` (201) may be set too low.
      warnings.warn(
    Traceback (most recent call last):
      File "<string>", line 1, in <module>
      File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
        result = self.forward(*input, **kwargs)
      File "/usr/local/lib/python3.8/dist-packages/torchaudio-0.8.0a0+e4e171a-py3.8-linux-x86_64.egg/torchaudio/transforms.py", line 480, in forward
        specgram = self.spectrogram(waveform)
      File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
        result = self.forward(*input, **kwargs)
      File "/usr/local/lib/python3.8/dist-packages/torchaudio-0.8.0a0+e4e171a-py3.8-linux-x86_64.egg/torchaudio/transforms.py", line 96, in forward
        return F.spectrogram(
      File "/usr/local/lib/python3.8/dist-packages/torchaudio-0.8.0a0+e4e171a-py3.8-linux-x86_64.egg/torchaudio/functional/functional.py", line 91, in spectrogram
        spec_f = torch.stft(
      File "/usr/local/lib/python3.8/dist-packages/torch/functional.py", line 580, in stft
        return _VF.stft(input, n_fft, hop_length, win_length, window,  # type: ignore
    RuntimeError: fft: ATen not compiled with MKL support
    

    and this check python -c 'import torch; a = torch.randn(10); print(a.to_mkldnn().layout)' works correctly.

    opened by Ayagoz 2
  • Expired link to nv-codec-headers repo

    Expired link to nv-codec-headers repo

    Hi, git.videolan.org is experiencing some issues again, it looks like the certificate for the domain is expired or something like that (but it was alive just a week ago!). Also, they are migrating to code.videolan.org, however nv-codec-headers is not there yet.

    The current link does not work: https://github.com/osai-ai/dokai/blob/6f99608b70881de43740bc84c34f42249f4f65aa/docker/Dockerfile.base#L43

    Temporary workaround: https://github.com/FFmpeg/nv-codec-headers.git

    opened by NikolasEnt 1
Releases(v22.11)
  • v22.11(Nov 22, 2022)

    Updates

    • TensorRT 8.5.1
    • torch 1.14.0a0+git71fe069 (source, close to v1.13.0 after commit "ada lovelace (arch 8.9) support #87436")
    • torchvision 0.14.0 (from source, v0.14.0 tag)
    • torchaudio 0.13.0 (from source, v0.13.0 tag)
    • Update other PyPI packages
    • Ada Lovelace architecture support
    • PyTorch image models benchmark link

    Images

    base

    Python with ML and CV packages, CUDA (11.8.0), cuDNN (8.6.0), FFmpeg (4.4) with NVENC/NVDEC support ghcr.io/osai-ai/dokai:22.11-base

    dokai:22.11-base

    Supported NVIDIA architectures: Pascal (sm_60, sm_61), Volta (sm_70), Turing (sm_75), Ampere (sm_80, sm_86), Ada Lovelace (sm_89).

    CUDA (11.8.0), cuDNN (8.6.0) FFmpeg (release/4.4), nv-codec-headers (sdk/11.0) Python (3.10.6) CMake (3.22.1)

    pip==22.3.1 setuptools==65.5.1 packaging==21.3 numpy==1.23.4 opencv-python==4.6.0.66 scipy==1.9.3 matplotlib==3.6.2 pandas==1.5.1 scikit-learn==1.1.3 scikit-image==0.19.3 Pillow==9.3.0 librosa==0.9.2 albumentations==1.3.0 pyzmq==24.0.1 Cython==0.29.32 numba==0.56.4 requests==2.28.1 psutil==5.9.4 pydantic==1.10.2 PyYAML==6.0 notebook==6.5.2 ipywidgets==8.0.2 tqdm==4.64.1 pytest==7.2.0 pytest-cov==4.0.0 mypy==0.991 flake8==5.0.4 pre-commit==2.20.0

    pytorch

    TensorRT (8.5.1) , PyTorch (1.13.0), torchvision (0.14.0), torchaudio (0.13.0) and torch based libraries. ghcr.io/osai-ai/dokai:22.11-pytorch

    dokai:22.11-pytorch

    additionally to dokai:22.11-base:

    TensorRT (8.5.1) MAGMA (2.6.2)

    torch==1.14.0a0+git71fe069 (source, close to v1.13.0 after commit "ada lovelace (arch 8.9) support #87436") torchvision==0.14.0 (source, v0.14.0 tag) torchaudio==0.13.0 (source, v0.13.0 tag) pytorch-ignite==0.4.10 pytorch-argus==1.0.0 pretrainedmodels==0.7.4 efficientnet-pytorch==0.7.1 pytorch-toolbelt==0.5.2 kornia==0.6.8 timm==0.6.11 segmentation-models-pytorch==0.3.0

    tensor-stream

    Tensor Stream for real-time video streams decoding on GPU.
    ghcr.io/osai-ai/dokai:22.11-tensor-stream

    dokai:22.11-tensor-stream

    additionally to dokai:22.11-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
    build_logs.zip(471.12 KB)
  • v22.03(Mar 28, 2022)

    Updates

    • CUDA 11.6.0
    • torch 1.11.0 (from source, v1.11.0 tag)
    • torchvision 0.12.0 (from source, v0.12.0 tag)
    • torchaudio 0.11.0 (from source, v0.11.0 tag)
    • CMake (3.22.2)
    • Update other PyPI packages
    • Update README

    Images

    base

    Python with ML and CV packages, CUDA (11.6.0), FFmpeg (4.4) with NVENC support.

    dokai:22.03-base

    ghcr.io/osai-ai/dokai:22.03-base

    CUDA (11.6.0) FFmpeg (release/4.4), nv-codec-headers (sdk/11.0)
    Python (3.8.10)
    CMake (3.22.2)

    pip==22.0.3
    setuptools==59.5.0
    packaging==21.3
    numpy==1.21.5
    opencv-python==4.5.5.62
    scipy==1.8.0
    matplotlib==3.5.1
    pandas==1.4.1
    scikit-learn==1.0.1
    scikit-image==0.18.3
    Pillow==8.4.0
    librosa==0.8.1
    albumentations==1.1.0
    pyzmq==22.3.0
    Cython==0.29.24
    numba==0.53.1
    requests==2.26.0
    psutil==5.8.0
    pydantic==1.8.2
    PyYAML==6.0
    notebook==6.4.5
    ipywidgets==7.6.5
    tqdm==4.62.3
    pytest==6.2.5
    mypy==0.910
    flake8==4.0.1

    pytorch

    PyTorch, torchvision and torch based libraries.

    dokai:22.03-pytorch

    ghcr.io/osai-ai/dokai:22.03-pytorch

    additionally to dokai:22.03-base:

    MAGMA (2.6.1)

    torch==1.11.0 (source, v1.11.0 tag)
    torchvision==0.12.0 (source, v0.12.0 tag)
    torchaudio==0.11.0 (source, v0.11.0 tag)
    pytorch-ignite==0.4.8
    pytorch-argus==1.0.0
    pretrainedmodels==0.7.4
    efficientnet-pytorch==0.7.1
    timm==0.5.4
    segmentation-models-pytorch==0.2.1
    kornia==0.6.3

    tensor-stream

    Tensor Stream.

    dokai:22.03-tensor-stream

    ghcr.io/osai-ai/dokai:22.03-tensor-stream

    additionally to dokai:22.03-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
  • v21.11(Nov 9, 2021)

    Updates

    • torch 1.10.0 (from source, v1.10.0 tag)
    • torchvision 0.11.1 (from source, v0.11.1 tag)
    • torchaudio 0.10.0 (from source, v0.10.0 tag)
    • CMake (3.21.4)
    • Remove Apex installation
    • Update other PyPI packages

    Images

    base

    Python with ML and CV packages, CUDA (11.4.2), cuDNN (8.2.4), FFmpeg (4.4) with NVENC support.
    ghcr.io/osai-ai/dokai:21.11-base

    dokai:21.11-base

    CUDA (11.4.2), cuDNN (8.2.4)
    FFmpeg (release/4.4), nv-codec-headers (sdk/11.0)
    Python (3.8.10)
    CMake (3.21.4)

    pip==21.3.1
    setuptools==58.5.3
    packaging==21.2
    numpy==1.21.4
    opencv-python==4.5.4.58
    scipy==1.7.2
    matplotlib==3.4.3
    pandas==1.3.4
    scikit-learn==1.0.1
    scikit-image==0.18.3
    Pillow==8.4.0
    librosa==0.8.1
    albumentations==1.1.0
    pyzmq==22.3.0
    Cython==0.29.24
    numba==0.53.1
    requests==2.26.0
    psutil==5.8.0
    pydantic==1.8.2
    PyYAML==6.0
    notebook==6.4.5
    ipywidgets==7.6.5
    tqdm==4.62.3
    pytest==6.2.5
    mypy==0.910
    flake8==4.0.1

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:21.11-pytorch

    dokai:21.11-pytorch

    additionally to dokai:21.11-base:

    MAGMA (2.6.1)

    torch==1.10.0 (source, v1.10.0 tag)
    torchvision==0.11.1 (source, v0.11.1 tag)
    torchaudio==0.10.0 (source, v0.10.0 tag)
    pytorch-ignite==0.4.7
    pytorch-argus==1.0.0
    pretrainedmodels==0.7.4
    efficientnet-pytorch==0.7.1
    timm==0.4.12
    segmentation-models-pytorch==0.2.0
    kornia==0.6.1

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:21.11-tensor-stream

    dokai:21.11-tensor-stream

    additionally to dokai:21.11-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
  • v21.09(Sep 30, 2021)

    Updates

    • CUDA 11.4.2, cuDNN 8.2.4
    • Build torch 1.10.0-rc1 (from source, v1.10.0-rc1 tag)
    • FFmpeg with HTTPS support
    • kornia 0.5.11
    • Update other PyPI packages

    Images

    base

    Python with ML and CV packages, CUDA (11.4.2), cuDNN (8.2.4), FFmpeg (4.4) with NVENC support.
    ghcr.io/osai-ai/dokai:21.09-base

    dokai:21.09-base

    CUDA (11.4.2), cuDNN (8.2.4)
    FFmpeg (release/4.4), nv-codec-headers (sdk/11.0)
    Python (3.8.10)

    pip==21.2.4
    setuptools==58.1.0
    packaging==21.0
    numpy==1.21.2
    opencv-python==4.5.3.56
    scipy==1.7.1
    matplotlib==3.4.3
    pandas==1.3.3
    scikit-learn==1.0
    scikit-image==0.18.3
    Pillow==8.3.2
    librosa==0.8.1
    albumentations==1.0.3
    pyzmq==22.3.0
    Cython==0.29.24
    numba==0.53.1
    requests==2.26.0
    psutil==5.8.0
    pydantic==1.8.2
    PyYAML==5.4.1
    notebook==6.4.4
    ipywidgets==7.6.5
    tqdm==4.62.3
    pytest==6.2.5
    mypy==0.910
    flake8==3.9.2

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:21.09-pytorch

    dokai:21.09-pytorch

    additionally to dokai:21.09-base:

    MAGMA (2.6.1)

    torch==1.10.0-rc1 (source, v1.10.0-rc1 tag)
    torchvision==0.10.1 (source, v0.10.1 tag)
    torchaudio==0.9.1 (source, v0.9.1 tag)
    pytorch-ignite==0.4.6
    pytorch-argus==0.2.1
    pretrainedmodels==0.7.4
    efficientnet-pytorch==0.7.1
    timm==0.4.12
    segmentation-models-pytorch==0.2.0
    kornia==0.5.11
    apex (source, master branch)

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:21.09-tensor-stream

    dokai:21.09-tensor-stream

    additionally to dokai:21.09-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
  • v21.08(Aug 12, 2021)

    Updates

    • CUDA 11.4.1, cuDNN 8.2.2
    • nv-codec-headers (sdk/11.0)
    • MAGMA 2.6.1
    • Build torch 1.10.0a0+git5b8389e from source (master branch)
    • pytorch-ignite 0.4.6
    • segmentation-models-pytorch 0.2.0
    • kornia 0.5.8
    • Update other PyPI packages

    Images

    base

    Python with ML and CV packages, CUDA (11.4.1), cuDNN (8.2.2), FFmpeg (4.4) with NVENC support.
    ghcr.io/osai-ai/dokai:21.08-base

    dokai:21.08-base

    CUDA (11.4.1), cuDNN (8.2.2)
    FFmpeg (release/4.4), nv-codec-headers (sdk/11.0)
    Python (3.8.10)

    pip==21.2.3
    setuptools==57.4.0
    packaging==21.0
    numpy==1.21.1
    opencv-python==4.5.3.56
    scipy==1.7.1
    matplotlib==3.4.2
    pandas==1.3.1
    scikit-learn==0.24.2
    scikit-image==0.18.2
    Pillow==8.3.1
    librosa==0.8.1
    albumentations==1.0.3
    pyzmq==22.2.1
    Cython==0.29.24
    numba==0.53.1
    requests==2.26.0
    psutil==5.8.0
    pydantic==1.8.2
    PyYAML==5.4.1
    notebook==6.4.3
    ipywidgets==7.6.3
    tqdm==4.62.0
    pytest==6.2.4
    mypy==0.910
    flake8==3.9.2

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:21.08-pytorch

    dokai:21.08-pytorch

    additionally to dokai:21.08-base:

    MAGMA (2.6.1)

    torch==1.10.0a0+git5b8389e (source, master branch)
    torchvision==0.10.0 (source, v0.10.0 tag)
    torchaudio==0.9.0 (source, v0.9.0 tag)
    pytorch-ignite==0.4.6
    pytorch-argus==0.2.1
    pretrainedmodels==0.7.4
    efficientnet-pytorch==0.7.1
    timm==0.4.12
    segmentation-models-pytorch==0.2.0
    kornia==0.5.8
    apex (source, master branch)

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:21.08-tensor-stream

    dokai:21.08-tensor-stream

    additionally to dokai:21.08-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
  • v21.07(Jul 2, 2021)

    Updates

    • CUDA 11.3.1
    • Build torch 1.9.0 from source (v1.9.0 tag)
    • torchvision 0.10.0 from source (v0.10.0 tag)
    • torchaudio 0.9.0 from source (v0.9.0 tag)
    • timm 0.4.12
    • kornia 0.5.5
    • Update other PyPI packages

    Images

    base

    Python with ML and CV packages, CUDA (11.3.1), cuDNN (8.2.0), FFmpeg (4.4) with NVENC support.
    ghcr.io/osai-ai/dokai:21.07-base

    dokai:21.07-base

    CUDA (11.3.1), cuDNN (8.2.0)
    FFmpeg (release/4.4), nv-codec-headers (sdk/10.0)
    Python (3.8.10)

    pip==21.1.3
    setuptools==57.0.0
    packaging==20.9
    numpy==1.21.0
    opencv-python==4.5.2.54
    scipy==1.7.0
    matplotlib==3.4.2
    pandas==1.2.5
    scikit-learn==0.24.2
    scikit-image==0.18.2
    Pillow==8.2.0
    librosa==0.8.1
    albumentations==1.0.0
    pyzmq==22.1.0
    Cython==0.29.23
    numba==0.53.1
    requests==2.25.1
    psutil==5.8.0
    trafaret-config==2.0.2
    pydantic==1.8.2
    PyYAML==5.4.1
    notebook==6.4.0
    ipywidgets==7.6.3
    tqdm==4.61.1
    pytest==6.2.4
    mypy==0.910
    flake8==3.9.2

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:21.07-pytorch

    dokai:21.07-pytorch

    additionally to dokai:21.07-base:

    torch==1.9.0 (source, v1.9.0 tag)
    torchvision==0.10.0 (source, v0.10.0 tag)
    torchaudio==0.9.0 (source, v0.9.0 tag)
    pytorch-argus==0.2.1
    pretrainedmodels==0.7.4
    efficientnet-pytorch==0.7.1
    timm==0.4.12
    segmentation-models-pytorch==0.1.3
    kornia==0.5.5
    apex (source, master branch)

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:21.07-tensor-stream

    dokai:21.07-tensor-stream

    additionally to dokai:21.07-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
  • v21.05(May 11, 2021)

    Updates

    • CUDA 11.3, cuDNN 8.2.0
    • Build torch 1.8.1 from source (v1.8.1 tag)
    • torchvision 0.9.1 from source (v0.9.1 tag)
    • torchaudio 0.8.1 from source (v0.8.1 tag)
    • timm 0.4.8 from source (master branch)
    • Update other PyPI packages

    Images

    base

    Python with ML and CV packages, CUDA (11.3), cuDNN (8.2.0), FFmpeg (4.4) with NVENC support.
    ghcr.io/osai-ai/dokai:21.05-base

    dokai:21.05-base

    CUDA (11.3), cuDNN (8.2.0)
    FFmpeg (release/4.4), nv-codec-headers (sdk/10.0)
    Python (3.8.5)

    pip==21.1.1
    setuptools==56.2.0
    packaging==20.9
    numpy==1.20.3
    opencv-python==4.5.2.52
    scipy==1.6.3
    matplotlib==3.4.2
    pandas==1.2.4
    scikit-learn==0.24.2
    scikit-image==0.18.1
    Pillow==8.2.0
    librosa==0.8.0
    albumentations==0.5.2
    pyzmq==22.0.3
    Cython==0.29.23
    numba==0.53.1
    requests==2.25.1
    psutil==5.8.0
    trafaret-config==2.0.2
    pydantic==1.8.1
    PyYAML==5.4.1
    notebook==6.3.0
    ipywidgets==7.6.3
    tqdm==4.60.0
    pytest==6.2.4
    mypy==0.812
    flake8==3.9.2

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:21.05-pytorch

    dokai:21.05-pytorch

    additionally to dokai:21.05-base:

    torch==1.8.1 (source, v1.8.1 tag)
    torchvision==0.9.1 (source, v0.9.1 tag)
    torchaudio==0.8.1 (source, v0.8.1 tag)
    pytorch-argus==0.2.1
    timm==0.4.8 (source, master branch)
    kornia==0.5.1
    pretrainedmodels==0.7.4
    efficientnet-pytorch==0.7.1
    segmentation-models-pytorch==0.1.3
    apex (source, master branch)

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:21.05-tensor-stream

    dokai:21.05-tensor-stream

    additionally to dokai:21.05-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
  • v21.03(Mar 25, 2021)

    Updates

    • CUDA 11.2.2, cuDNN 8.1.1
    • FFmpeg 4.4
    • Build torch 1.8.0 from source (v1.8.0 tag)
    • torchvision 0.9.0
    • Add PyTorch package: torchaudio 0.8.0
    • timm 0.4.5
    • pytorch-argus 0.2.1
    • Update other PyPI packages
    • Support more GPU architectures for FFmpeg

    Images

    base

    Python with ML and CV packages, CUDA (11.2.2), cuDNN (8.1.1), FFmpeg (4.4) with NVENC support.
    ghcr.io/osai-ai/dokai:21.03-base

    dokai:21.03-base

    ghcr.io/osai-ai/dokai:21.03-base

    CUDA (11.2.2), cuDNN (8.1.1)
    FFmpeg (release/4.4), nv-codec-headers (sdk/10.0)
    Python (3.8.5)

    pip==21.0.1
    setuptools==54.2.0
    packaging==20.9
    numpy==1.20.1
    opencv-python==4.5.1.48
    scipy==1.6.1
    matplotlib==3.3.4
    pandas==1.2.3
    scikit-learn==0.24.1
    scikit-image==0.18.1
    Pillow==8.1.2
    librosa==0.8.0
    albumentations==0.5.2
    pyzmq==22.0.3
    Cython==0.29.22
    numba==0.53.0
    requests==2.25.1
    psutil==5.8.0
    trafaret-config==2.0.2
    pydantic==1.8.1
    PyYAML==5.4.1
    notebook==6.3.0
    ipywidgets==7.6.3
    tqdm==4.59.0
    pytest==6.2.2
    mypy==0.812
    flake8==3.9.0

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:21.03-pytorch

    dokai:21.03-pytorch

    additionally to dokai:21.03-base:

    torch==1.8.0 (source, v1.8.0 tag)
    torchvision==0.9.0 (source, v0.9.0 tag)
    torchaudio==0.8.0 (source, v0.8.0 tag)
    pytorch-argus==0.2.1
    timm==0.4.5
    kornia==0.5.0
    pretrainedmodels==0.7.4
    efficientnet-pytorch==0.7.0
    segmentation-models-pytorch==0.1.3
    apex (source, master branch)

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:21.03-tensor-stream

    dokai:21.03-tensor-stream

    additionally to dokai:21.03-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
  • v21.02(Feb 23, 2021)

    New features

    • CUDA 11.2.1, cuDNN 8.1.0
    • Build torch 1.9.0a0+c2b9283 from source (master branch)
    • Install timm 0.4.4 from source (master branch)
    • Add more Python packages: tqdm, PyYAML, pytest, mypy, flake8
    • Add more PyTorch packages: pretrainedmodels, efficientnet-pytorch, segmentation-models-pytorch
    • Update other PyPI packages

    Images

    base

    Python with ML and CV packages, CUDA (11.2.1), cuDNN (8.1.0), FFmpeg with NVENC support.
    ghcr.io/osai-ai/dokai:21.02-base

    dokai:21.02-base

    CUDA (11.2.1), cuDNN (8.1.0)
    FFmpeg (release/4.3), nv-codec-headers (sdk/10.0)
    Python (3.8.5)

    pip==21.0.1
    setuptools==53.0.0
    packaging==20.9
    numpy==1.20.1
    opencv-python==4.5.1.48
    scipy==1.6.1
    matplotlib==3.3.4
    pandas==1.2.2
    scikit-learn==0.24.1
    scikit-image==0.18.1
    Pillow==8.1.0
    librosa==0.8.0
    albumentations==0.5.2
    pyzmq==22.0.3
    Cython==0.29.22
    numba==0.52.0
    requests==2.25.1
    psutil==5.8.0
    trafaret-config==2.0.2
    pydantic==1.7.3
    PyYAML==5.4.1
    notebook==6.2.0
    ipywidgets==7.6.3
    tqdm==4.57.0
    pytest==6.2.2
    mypy==0.812
    flake8==3.8.4

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:21.02-pytorch

    dokai:21.02-pytorch

    additionally to dokai:21.02-base:

    torch==1.9.0a0+c2b9283 (source, master branch)
    torchvision==0.8.2 (source, v0.8.2 tag)
    pytorch-argus==0.2.0
    timm==0.4.4 (source, master branch)
    kornia==0.4.1
    pretrainedmodels==0.7.4
    efficientnet-pytorch==0.7.0
    segmentation-models-pytorch==0.1.3
    apex (source, master branch)

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:21.02-tensor-stream

    dokai:21.02-tensor-stream

    additionally to dokai:21.02-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
  • v21.01(Jan 21, 2021)

    New features

    • CUDA 11.1.1
    • nv-codec-headers (sdk/10.0)
    • Build torch 1.8.0a0+4aea007 from source (master branch)
    • Update other PyPI packages
    • Docker Hub mirror

    Images

    base

    Python with ML and CV packages, CUDA, FFmpeg with NVENC support.
    ghcr.io/osai-ai/dokai:21.01-base

    dokai:21.01-base

    CUDA (11.1.1), cuDNN (8.0.5)
    FFmpeg (release/4.3), nv-codec-headers (sdk/10.0)
    Python (3.8.5)

    pip==20.3.3
    setuptools==51.3.3
    packaging==20.8
    numpy==1.19.5
    opencv-python==4.5.1.48
    scipy==1.6.0
    matplotlib==3.3.3
    pandas==1.2.0
    notebook==6.2.0
    scikit-learn==0.24.1
    scikit-image==0.18.1
    albumentations==0.5.2
    Cython==0.29.21
    Pillow==8.1.0
    trafaret-config==2.0.2
    pyzmq==21.0.1
    librosa==0.8.0
    psutil==5.8.0
    pydantic==1.7.3
    requests==2.25.1

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:21.01-pytorch

    dokai:21.01-pytorch

    additionally to dokai:21.01-base:

    torch==1.8.0a0+4aea007 (source, master branch)
    torchvision==0.8.2 (source, v0.8.2 tag)
    pytorch-argus==0.2.0
    timm==0.3.4
    kornia==0.4.1
    apex (source, master branch)

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:21.01-tensor-stream

    dokai:21.01-tensor-stream

    additionally to dokai:21.01-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
  • v20.12(Dec 24, 2020)

    New features

    • CUDA 11.1, cuDNN 8.0.5, Ubuntu 20.04, Python 3.8.5
    • Build PyTorch and torchvision from source
    • Build CUDA libraries for Ampere architecture (TORCH_CUDA_ARCH_LIST="6.0;6.1;7.0;7.5;8.0;8.6")
    • kornia

    Images

    base

    Python with ML and CV packages, CUDA, FFmpeg with NVENC support.
    ghcr.io/osai-ai/dokai:20.12-base

    dokai:20.12-base

    CUDA (11.1), cuDNN (8.0.5) FFmpeg (release/4.3), nv-codec-headers (sdk/9.1)
    Python (3.8.5)

    pip==20.3.3
    setuptools==51.0.0
    packaging==20.8
    numpy==1.19.4
    opencv-python==4.4.0.46
    scipy==1.5.4
    matplotlib==3.3.3
    pandas==1.1.5
    notebook==6.1.5
    scikit-learn==0.23.2
    scikit-image==0.18.0
    albumentations==0.5.2
    Cython==0.29.21
    Pillow==8.0.1
    trafaret-config==2.0.2
    pyzmq==20.0.0
    librosa==0.8.0
    psutil==5.8.0
    pydantic==1.7.3
    requests==2.25.1

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:20.12-pytorch

    dokai:20.12-pytorch

    additionally to dokai:20.12-base:

    torch==1.7.1 (source, v1.7.1 tag)
    torchvision==0.8.2 (source, v0.8.2 tag)
    pytorch-argus==0.2.0
    timm==0.3.2
    kornia==0.4.1
    apex (source, master branch)

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:20.12-tensor-stream

    dokai:20.12-tensor-stream

    additionally to dokai:20.12-pytorch:

    tensor-stream==0.4.6 (source, dev branch)

    Source code(tar.gz)
    Source code(zip)
  • v20.10(Oct 22, 2020)

    New features

    • pydantic
    • requests

    Fix

    • Build Tensor Stream for lower cuDNN versions 3.7+PTX;5.0;6.0;6.1;7.0;7.5

    Images

    base

    Python with ML and CV packages, CUDA, FFmpeg with NVENC support.
    ghcr.io/osai-ai/dokai:20.10-base

    dokai:20.10-base

    FFmpeg (release/4.3), nv-codec-headers (sdk/9.1)
    Python (3.6.9)

    pip==20.2.4
    setuptools==50.3.2
    packaging==20.4
    numpy==1.19.2
    opencv-python==4.4.0.44
    scipy==1.5.3
    matplotlib==3.3.2
    pandas==1.1.3
    notebook==6.1.4
    scikit-learn==0.23.2
    scikit-image==0.17.2
    albumentations==0.5.0
    Cython==0.29.21
    Pillow==8.0.0
    trafaret-config==2.0.2
    pyzmq==19.0.2
    librosa==0.8.0
    psutil==5.7.2
    dataclasses==0.7
    pydantic==1.6.1
    requests==2.24.0

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:20.10-pytorch

    dokai:20.10-pytorch

    additionally to dokai:20.10-base:

    torch==1.6.0
    torchvision==0.7.0
    pytorch-argus==0.1.2
    timm==0.2.1
    apex (master)

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:20.10-tensor-stream

    dokai:20.10-tensor-stream

    additionally to dokai:20.10-pytorch:

    tensor-stream==0.4.6 (dev)

    Source code(tar.gz)
    Source code(zip)
  • v20.09(Sep 29, 2020)

    base

    Python with ML and CV packages, CUDA, FFmpeg with NVENC support.
    ghcr.io/osai-ai/dokai:20.09-base

    dokai:20.09-base

    FFmpeg (release/4.3), nv-codec-headers (sdk/9.1)
    Python (3.6.9)

    pip==20.2.3
    setuptools==50.3.0
    packaging==20.4
    numpy==1.19.2
    opencv-python==4.4.0.42
    scipy==1.5.2
    matplotlib==3.3.2
    pandas==1.1.2
    notebook==6.1.4
    scikit-learn==0.23.2
    scikit-image==0.17.2
    albumentations==0.4.6
    Cython==0.29.21
    Pillow==7.2.0
    trafaret-config==2.0.2
    pyzmq==19.0.2
    librosa==0.8.0
    psutil==5.7.2
    dataclasses==0.7

    pytorch

    PyTorch, torchvision, Apex and torch based libraries.
    ghcr.io/osai-ai/dokai:20.09-pytorch

    dokai:20.09-pytorch

    additionally to dokai:20.09-base:

    torch==1.6.0
    torchvision==0.7.0
    pytorch-argus==0.1.2
    timm==0.2.1
    apex (master)

    tensor-stream

    Tensor Stream.
    ghcr.io/osai-ai/dokai:20.09-tensor-stream

    dokai:20.09-tensor-stream

    additionally to dokai:20.09-pytorch:

    tensor-stream==0.4.6 (dev)

    Source code(tar.gz)
    Source code(zip)
Owner
OSAI
OSAI is developing automatic systems that help to analyze a game and provide real-time game data with Computer Vision and AI in Sports.
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