def img2tensor(imgs, bgr2rgb=True, float32=True):
    """Numpy array to tensor.

    Args:
        imgs (list[ndarray] | ndarray): Input images.
        bgr2rgb (bool): Whether to change bgr to rgb.
        float32 (bool): Whether to change to float32.

    Returns:
        list[tensor] | tensor: Tensor images. If returned results only have
            one element, just return tensor.
    """

    def _totensor(img, bgr2rgb, float32):
        if img.shape[2] == 3 and bgr2rgb:
            if img.dtype == 'float64':
                img = img.astype('float32')
            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        img = torch.from_numpy(img.transpose(2, 0, 1))
        if float32:
            img = img.float()
        return img

    if isinstance(imgs, list):
        return [_totensor(img, bgr2rgb, float32) for img in imgs]
    else:
        return _totensor(imgs, bgr2rgb, float32)
Numpy array to tensor.

Args:
imgs (list[ndarray] | ndarray): Input images.
bgr2rgb (bool): Whether to change bgr to rgb.
float32 (bool): Whether to change to float32.

Returns:
list[tensor] | tensor: Tensor images. If returned results only have
one element, just return tensor.
opensora/models/super_resolution/basicsr/utils/img_util.py