pynvvl
PyNVVL is a thin wrapper of NVIDIA Video Loader (NVVL). This package enables you to load videos directly to GPU memory and access them as CuPy ndarrays with zero copy. The pre-built binaries of PyNVVL include NVVL itself, so you do not need to install NVVL.
CUDA 8.0, 9.0, 9.1, or 9.2
Python 2.7.6+, 3.4.7+, 3.5.1+, or 3.6.0+
CuPy v4.5.0
Ubuntu 16.04
Python 2.7.6+, 3.4.7+, 3.5.1+, and 3.6.0+
CUDA 8.0, 9.0, 9.1, and 9.2
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# [For CUDA 9.2]pip install pynvvl-cuda92
import pynvvlimport matplotlib.pyplot as plt# 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 is flickr-2-6-3-3-5-2-7-6-5626335276_4.mp4
from 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.
Please specify the GPU device id when you create a NVVLVideoLoader
object.
You can also specify the logging level with the argument log_level
for the constructor of NVVLVideoLoader
.
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'.
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. 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.
Requirements:
Docker
nvidia-docker (v1/v2)
bash docker/build_wheels.sh
The setup.py
script searches for necessary libraries.
Requirements: the following libraries should be available in LIBRARY_PATH
.
libnvvl.so
libavformat.so.57
libavfilter.so.6
libavcodec.so.57
libavutil.so.55
You can build libnvvl.so
in the nvvl
repository. Follow the instructions
of nvvl
library. The build
directory must be in LIBRARY_PATH
.
The 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 in LIBRARY_PATH
as well.
python setup.py develop python setup.py bdist_wheel
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