Spaces:
No application file
No application file
File size: 2,700 Bytes
921475c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 |
"""This module contains utilities for anomaly detection."""
import logging
import sys
from typing import List, Optional, Union
from torchvision.transforms import transforms
from . import transforms_video
def register_logger(log_file: Optional[str] = None, stdout: bool = True) -> None:
"""Register a logger.
Args:
log_file (str, optional): Path to the file where log should be written.
If `None`, log wouldn't be written to any file. Defaults to None.
stdout (bool, optional): If `True`, the log would be printed to stdout. Defaults to True.
"""
log = logging.getLogger() # root logger
for hdlr in log.handlers[:]: # remove all old handlers
log.removeHandler(hdlr)
handlers: List[Union[logging.FileHandler, logging.StreamHandler]] = []
if stdout:
handlers.append(logging.StreamHandler(stream=sys.stdout))
if log_file is not None:
handlers.append(logging.FileHandler(log_file))
logging.basicConfig(
format="%(asctime)s %(message)s",
handlers=handlers,
level=logging.INFO,
)
logging.root.setLevel(logging.INFO)
def build_transforms(mode: str = "c3d") -> transforms.Compose:
"""Build transforms to use for training an anomaly detection model.
Args:
mode (str, optional): Mode for which transforms should be constructed.
Either c3d | i3d | mfnet | 3dResNet. Defaults to "c3d".
Raises:
NotImplementedError: The provided mode is not implemented.
Returns:
transforms.Compose
"""
if mode == "c3d":
mean = [124 / 255, 117 / 255, 104 / 255]
std = [1 / (0.0167 * 255)] * 3
resize = 128, 171
crop = 112
elif mode == "i3d":
mean = [0, 0, 0]
std = [1, 1, 1]
elif mode == "mfnet":
mean = [0.485, 0.456, 0.406]
std = [0.229, 0.224, 0.225]
elif mode == "3dResNet":
mean = [0.4345, 0.4051, 0.3775]
std = [0.2768, 0.2713, 0.2737]
else:
raise NotImplementedError(f"Mode {mode} not implemented")
if mode == "c3d":
res = transforms.Compose(
[
transforms_video.ToTensorVideo(),
transforms_video.ResizeVideo(resize),
transforms_video.CenterCropVideo(crop),
transforms_video.NormalizeVideo(mean=mean, std=std),
]
)
else:
res = transforms.Compose(
[
transforms_video.ToTensorVideo(),
transforms_video.NormalizeVideo(mean=mean, std=std),
]
)
return res
|