Package: pynvvl-cuda92
PyNVVLPyNVVL is a thin wrapper ofNVIDIA Video Loader (NVVL). This package enables you to load videos directoly to GPU memory and access them asCuPyndarrays with zero copy. The pre-built binaries of PyNVVL include NVVL itself, so you do not need to install NVVL.RequirementsCUDA 8.0, 9.0, 9.1, or 9.2Python 2.7.6+, 3.4.7+, 3.5.1+, or 3.6.0+CuPyv4.5.0Tested EnvironmentUbuntu 16.04Python 2.7.6+, 3.4.7+, 3.5.1+, and 3.6.0+CUDA 8.0, 9.0, 9.1, and 9.2Install the pre-built binaryPlease choose a right package depending on your CUDA version.# [For CUDA 8.0]pipinstallpynvvl-cuda80# [For CUDA 9.0]pipinstallpynvvl-cuda90# [For CUDA 9.1]pipinstallpynvvl-cuda91# [For CUDA 9.2]pipinstallpynvvl-cuda92Usageimportpynvvlimportmatplotlib.pyplotasplt# Create NVVLVideoLoader objectloader=pynvvl.NVVLVideoLoader(device_id=0,log_level='error')# Show the number of frames in the videon_frames=loader.frame_count('examples/sample.mp4')print('Number of frames:',n_frames)# Load a video and return it as a CuPy arrayvideo=loader.read_sequence('examples/sample.mp4',horiz_flip=True,scale_height=512,scale_width=512,crop_y=60,crop_height=385,crop_width=512,scale_method='Linear',normalized=True)print(video.shape)# => (91, 3, 385, 512): (n_frames, channels, height, width)print(video.dtype)# => float32# Get the first frame as numpy arrayframe=video[0].get()frame=frame.transpose(1,2,0)plt.imshow(frame)plt.savefig('examples/sample.png')This video isflickr-2-6-3-3-5-2-7-6-5626335276_4.mp4from the Moments-In-Time dataset.Note that cropping is performed after scaling. In the above example, NVVL performs scaling up from 256 x 256 to 512 x 512 first, then cropping the region [60:60 + 385, 0:512]. See the following section to know more about the transformation options.VideoLoader optionsPlease specify the GPU device id when you create aNVVLVideoLoaderobject.
You can also specify the logging level with a argumentlog_levelfor the constructor ofNVVLVideoLoader.Wrapper of NVVL VideoLoader

    Args:
        device_id (int): Specify the device id used to load a video.
        log_level (str): Logging level which should be either 'debug',
            'info', 'warn', 'error', or 'none'.
            Logs with levels >= log_level is shown. The default is 'warn'.Transformation Optionspynvvl.NVVLVideoLoader.read_sequencecan take some options to specify the color space, the value range, and what transformations you want to perform to the video.Loads the video from disk and returns it as a CuPy ndarray.

    Args:
        filename (str): The path to the video.
        frame (int): The initial frame number of the returned sequence.
            Default is 0.
        count (int): The number of frames of the returned sequence.
            If it is None, whole frames of the video are loaded.
        channels (int): The number of color channels of the video.
            Default is 3.
        scale_height (int): The height of the scaled video.
            Note that scaling is performed before cropping.
            If it is 0 no scaling is performed. Default is 0.
        scale_width (int): The width of the scaled video.
            Note that scaling is performed before cropping.
            If it is 0, no scaling is performed. Default is 0.
        crop_x (int): Location of the crop within the scaled frame.
            Must be set such that crop_y + height <= original height.
            Default is 0.
        crop_y (int): Location of the crop within the scaled frame.
            Must be set such that crop_x + width <= original height.
            Default is 0.
        crop_height (int): The height of cropped region of the video.
            If it is None, no cropping is performed. Default is None.
        crop_width (int): The width of cropped region of the video.
            If it is None, no cropping is performed. Default is None.
        scale_method (str): Scaling method. It should be either of
            'Nearest' or 'Lienar'. Default is 'Linear'.
        horiz_flip (bool): Whether horizontal flipping is performed or not.
            Default is False.
        normalized (bool): If it is True, the values of returned video is
            normalized into [0, 1], otherwise the value range is [0, 255].
            Default is False.
        color_space (str): The color space of the values of returned video.
            It should be either 'RGB' or 'YCbCr'. Default is 'RGB'.
        chroma_up_method (str): How the chroma channels are upscaled from
            yuv 4:2:0 to 4:4:4. It should be 'Linear' currently.
        out (cupy.ndarray): Alternate output array where place the result.
            It must have the same shape and the dtype as the expected
            output, and its order must be C-contiguous.How to buildBuild wheels using Docker:Requirements:Dockernvidia-docker (v1/v2)bash docker/build_wheels.shSetup development environment without Docker:Thesetup.pyscript searches for necessary libraries.Requirements: the following libraries are available inLIBRARY_PATH.libnvvl.solibavformat.so.57libavfilter.so.6libavcodec.so.57libavutil.so.55You can buildlibnvvl.soin thenvvlrepository. Follow the instructions
ofnvvllibrary. Thebuilddirectory must be inLIBRARY_PATH.Other three libraries are available as packages in Ubuntu 16.04.
They are installed under/usr/lib/x86_64-linux-gnu, so they must be inLIBRARY_PATHas well.python setup.py develop
python setup.py bdist_wheel