def rgb_to_hsv(image: torch.Tensor, eps: float = 1e-8) -> torch.Tensor:
    r"""Convert an image from RGB to HSV.

    .. image:: _static/img/rgb_to_hsv.png

    The image data is assumed to be in the range of (0, 1).

    Args:
        image: RGB Image to be converted to HSV with shape of :math:`(*, 3, H, W)`.
        eps: scalar to enforce numarical stability.

    Returns:
        HSV version of the image with shape of :math:`(*, 3, H, W)`.
        The H channel values are in the range 0..2pi. S and V are in the range 0..1.

    .. note::
       See a working example `here <https://kornia.github.io/tutorials/nbs/color_conversions.html>`__.

    Example:
        >>> input = torch.rand(2, 3, 4, 5)
        >>> output = rgb_to_hsv(input)  # 2x3x4x5

    """
    if not isinstance(image, torch.Tensor):
        raise TypeError(f"Input type is not a torch.Tensor. Got {type(image)}")

    if len(image.shape) < 3 or image.shape[-3] != 3:
        raise ValueError(f"Input size must have a shape of (*, 3, H, W). Got {image.shape}")

    max_rgb, argmax_rgb = image.max(-3)
    min_rgb, argmin_rgb = image.min(-3)
    deltac = max_rgb - min_rgb

    v = max_rgb
    s = deltac / (max_rgb + eps)

    deltac = torch.where(deltac == 0, torch.ones_like(deltac), deltac)
    rc, gc, bc = torch.unbind((max_rgb.unsqueeze(-3) - image), dim=-3)

    h1 = bc - gc
    h2 = (rc - bc) + 2.0 * deltac
    h3 = (gc - rc) + 4.0 * deltac

    h = torch.stack((h1, h2, h3), dim=-3) / deltac.unsqueeze(-3)
    h = torch.gather(h, dim=-3, index=argmax_rgb.unsqueeze(-3)).squeeze(-3)
    h = (h / 6.0) % 1.0
    h = 2.0 * math.pi * h  # we return 0/2pi output

    return torch.stack((h, s, v), dim=-3)
Convert an image from RGB to HSV.

    .. image:: _static/img/rgb_to_hsv.png

    The image data is assumed to be in the range of (0, 1).

    Args:
        image: RGB Image to be converted to HSV with shape of :math:`(*, 3, H, W)`.
        eps: scalar to enforce numarical stability.

    Returns:
        HSV version of the image with shape of :math:`(*, 3, H, W)`.
        The H channel values are in the range 0..2pi. S and V are in the range 0..1.

    .. note::
       See a working example `here <https://kornia.github.io/tutorials/nbs/color_conversions.html>`__.

    Example:
        >>> input = torch.rand(2, 3, 4, 5)
        >>> output = rgb_to_hsv(input)  # 2x3x4x5

    
kornia/color/hsv.py