Shortcuts

# mmcv.image.misc 源代码

# Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional

import numpy as np

import mmcv

try:
import torch
except ImportError:
torch = None

[文档]def tensor2imgs(tensor,
mean: Optional[tuple] = None,
std: Optional[tuple] = None,
to_rgb: bool = True) -> list:
"""Convert tensor to 3-channel images or 1-channel gray images.

Args:
tensor (torch.Tensor): Tensor that contains multiple images, shape (
N, C, H, W). :math:C can be either 3 or 1.
mean (tuple[float], optional): Mean of images. If None,
(0, 0, 0) will be used for tensor with 3-channel,
while (0, ) for tensor with 1-channel. Defaults to None.
std (tuple[float], optional): Standard deviation of images. If None,
(1, 1, 1) will be used for tensor with 3-channel,
while (1, ) for tensor with 1-channel. Defaults to None.
to_rgb (bool, optional): Whether the tensor was converted to RGB
format in the first place. If so, convert it back to BGR.
For the tensor with 1 channel, it must be False. Defaults to True.

Returns:
list[np.ndarray]: A list that contains multiple images.
"""

if torch is None:
raise RuntimeError('pytorch is not installed')
assert torch.is_tensor(tensor) and tensor.ndim == 4
channels = tensor.size(1)
assert channels in [1, 3]
if mean is None:
mean = (0, ) * channels
if std is None:
std = (1, ) * channels
assert (channels == len(mean) == len(std) == 3) or \
(channels == len(mean) == len(std) == 1 and not to_rgb)

num_imgs = tensor.size(0)
mean = np.array(mean, dtype=np.float32)
std = np.array(std, dtype=np.float32)
imgs = []
for img_id in range(num_imgs):
img = tensor[img_id, ...].cpu().numpy().transpose(1, 2, 0)
img = mmcv.imdenormalize(
img, mean, std, to_bgr=to_rgb).astype(np.uint8)
imgs.append(np.ascontiguousarray(img))
return imgs


© Copyright 2018-2022, OpenMMLab. Revision 270c293c.

Built with Sphinx using a theme provided by Read the Docs.
Versions
latest
stable
2.x
v1.7.0
v1.6.2
v1.6.1
v1.6.0
v1.5.3
v1.5.2_a
v1.5.1
v1.5.0
v1.4.8
v1.4.7
v1.4.6
v1.4.5
v1.4.4
v1.4.3
v1.4.2
v1.4.1
v1.4.0
v1.3.18
v1.3.17
v1.3.16
v1.3.15
v1.3.14
v1.3.13