Пример #1
0
Файл: pil.py Проект: necla-ml/ML
from ml import logging

try:
    from PIL import *
except Exception as e:
    logging.warn("pillow unavailable, run `mamba install pillow` to install") 
Пример #2
0
#   - GTX Titan X
# SM61 or SM_61, compute_61
#   – GTX 1080, GTX 1070, GTX 1060, GTX 1050, GTX 1030,
#   - Titan Xp, Tesla P40, Tesla P4,
#   - Discrete GPU on the NVIDIA Drive PX2
# SM70 or SM_70, compute_70
#   - Titan V
# SM75 or SM_75, compute_75
#   – GTX/RTX Turing
#   – GTX 1660 Ti, RTX 2060, RTX 2070, RTX 2080,
#   - Titan RTX,

if not os.environ.get('TORCH_CUDA_ARCH_LIST'):
    # os.environ['TORCH_CUDA_ARCH_LIST'] = '5.2;6.1;7.0;7.5;8.0;8.6+PTX'
    logging.warn(
        f'TORCH_CUDA_ARCH_LIST not set, build based on local GPU capability={torch.cuda.get_device_capability(0)}'
    )

cwd = Path(__file__).parent
pkg = sh('basename -s .git `git config --get remote.origin.url`').lower()
PKG = pkg.upper()


def write_version_py(path,
                     major=None,
                     minor=None,
                     patch=None,
                     suffix='',
                     sha='Unknown'):
    if major is None or minor is None or patch is None:
        major, minor, patch = sh("git describe --abbrev=0 --tags")[1:].split(
Пример #3
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from typing import Union
from ml import logging

try:
    from ml.vision.io import *
except Exception as e:
    logging.warn(f"{e}, ml.vision.io unavailable, run `mamba install ml-vision -c NECLA-ML` to install")
else:
    from pathlib import Path
    from ml.vision import io
    import torch as th

    def load(path: Union[str, Path], *args):
        r"""Load a file in supported image or video formats.

        Other args and kwargs from APIs to support:
        - read_image(path: str, mode: torchvision.io.image.ImageReadMode = <ImageReadMode.UNCHANGED: 0>) → torch.Tensor
        - read_video(filename: str, start_pts: int = 0, end_pts: Optional[float] = None, pts_unit: str = "pts") -> Tuple[torch.Tensor, torch.Tensor, Dict[str, Any]]
        """
        suffix = Path(path).suffix.lower() 
        if suffix in ['.png', '.jpg', '.jpeg']:
            return io.read_image(str(path), *args)
        else:
            # Tuple[torch.Tensor, torch.Tensor, Dict[str, Any]]
            return io.read_video(str(path), *args)


    def save(data: th.Tensor, path: Union[str, Path], *args, **kwargs):
        """Encode image to save in jpeg or png.
        Args:
            data (PIL.Image, accimage.Image, Tensor[C, H, W, dtype=uint8] or Tensor[T, H, W, C, dtype=uint8]))
Пример #4
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from ml import logging

try:
    from av import *
except Exception as e:
    logging.warn("PyAV unavailable, run `mamba install av -c conda-forge` to install") 
Пример #5
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from ml import logging

try:
    from cv2 import *
except Exception as e:
    logging.warn(
        "opencv unavailable, run `mamba install opencv -c conda-forge` to install"
    )