v0.0.2a2

Update: Use stream to create CuPy ndarray and wait for the NVVL processing finishes.

PyNVVL

PyNVVL is a thin wrapper of NVIDIA Video Loader (NVVL). This package enables you to load videos directoly to GPU memory and access them as CuPy ndarrays with zero copy.

Requirements

• Python 2.7.6+, 3.4.7+, 3.5.1+, 3.6.0+
• CuPy v4.0.0

Tested Environment

• Ubuntu 16.04
• Python 2.7.6+, 3.4.7+, 3.5.1+, 3.6.0+

Install the pre-built binary

Please choose a right package depending on your CUDA version.

# [For CUDA 8.0]
pip install pynvvl-cuda80

# [For CUDA 9.0]
pip install pynvvl-cuda90

# [For CUDA 9.1]
pip install pynvvl-cuda91

Usage

import pynvvl
import matplotlib.pyplot as plt

# Create NVVLVideoLoader object
loader = pynvvl.NVVLVideoLoader(device_id=0)

# Show the number of frames in the video
n_frames = loader.frame_count('examples/sample.mp4')
print('Number of frames:', n_frames)

# Load a video and return it as a CuPy array
video = loader.read_sequence(
    'examples/sample.mp4',
    horiz_flip=True,
    crop_y=30,
    crop_height=190,
    scale_method='Nearest',
    normalized=True
)

print(video.shape)  # => (91, 3, 256, 256): (n_frames, channels, height, width)
print(video.dtype)  # => float32

# Get the first frame as numpy array
frame = video[0].get()
frame = frame.transpose(1, 2, 0)

plt.imshow(frame)
plt.savefig('examples/sample.png')

This video is from the Moments-In-Time dataset.

Transformation Options

pynvvl.NVVLVideoLoader.read_sequence can 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.

How to build wheels

Requirements for build

• Docker
• nvidia-docker (v1/v2)

bash docker/build_wheels.sh