Source code for torchvision

import warnings
import os

from .extension import _HAS_OPS

from torchvision import models
from torchvision import datasets
from torchvision import ops
from torchvision import transforms
from torchvision import utils
from torchvision import io

import torch

    from .version import __version__  # noqa: F401
except ImportError:

# Check if torchvision is being imported within the root folder
if (not _HAS_OPS and os.path.dirname(os.path.realpath(__file__)) ==
        os.path.join(os.path.realpath(os.getcwd()), 'torchvision')):
    message = ('You are importing torchvision within its own root folder ({}). '
               'This is not expected to work and may give errors. Please exit the '
               'torchvision project source and relaunch your python interpreter.')

_image_backend = 'PIL'

_video_backend = "pyav"

[docs]def set_image_backend(backend): """ Specifies the package used to load images. Args: backend (string): Name of the image backend. one of {'PIL', 'accimage'}. The :mod:`accimage` package uses the Intel IPP library. It is generally faster than PIL, but does not support as many operations. """ global _image_backend if backend not in ['PIL', 'accimage']: raise ValueError("Invalid backend '{}'. Options are 'PIL' and 'accimage'" .format(backend)) _image_backend = backend
[docs]def get_image_backend(): """ Gets the name of the package used to load images """ return _image_backend
[docs]def set_video_backend(backend): """ Specifies the package used to decode videos. Args: backend (string): Name of the video backend. one of {'pyav', 'video_reader'}. The :mod:`pyav` package uses the 3rd party PyAv library. It is a Pythonic binding for the FFmpeg libraries. The :mod:`video_reader` package includes a native C++ implementation on top of FFMPEG libraries, and a python API of TorchScript custom operator. It is generally decoding faster than :mod:`pyav`, but perhaps is less robust. .. note:: Building with FFMPEG is disabled by default in the latest master. If you want to use the 'video_reader' backend, please compile torchvision from source. """ global _video_backend if backend not in ["pyav", "video_reader"]: raise ValueError( "Invalid video backend '%s'. Options are 'pyav' and 'video_reader'" % backend ) if backend == "video_reader" and not io._HAS_VIDEO_OPT: message = ( "video_reader video backend is not available." " Please compile torchvision from source and try again" ) warnings.warn(message) else: _video_backend = backend
def get_video_backend(): return _video_backend def _is_tracing(): return torch._C._get_tracing_state()


Access comprehensive developer documentation for PyTorch

View Docs


Get in-depth tutorials for beginners and advanced developers

View Tutorials


Find development resources and get your questions answered

View Resources