tensorlayer/prepro.py
def hsv_to_rgb(hsv):
    """Input HSV image [0~1] return RGB image [0~255].

    Parameters
    -------------
    hsv : numpy.array
        An image with values between 0.0 and 1.0

    Returns
    -------
    numpy.array
        A processed image.
    """
    # Translated from source of colorsys.hsv_to_rgb
    # h,s should be a numpy arrays with values between 0.0 and 1.0
    # v should be a numpy array with values between 0.0 and 255.0
    # hsv_to_rgb returns an array of uints between 0 and 255.
    rgb = np.empty_like(hsv)
    rgb[..., 3:] = hsv[..., 3:]
    h, s, v = hsv[..., 0], hsv[..., 1], hsv[..., 2]
    i = (h * 6.0).astype('uint8')
    f = (h * 6.0) - i
    p = v * (1.0 - s)
    q = v * (1.0 - s * f)
    t = v * (1.0 - s * (1.0 - f))
    i = i % 6
    conditions = [s == 0.0, i == 1, i == 2, i == 3, i == 4, i == 5]
    rgb[..., 0] = np.select(conditions, [v, q, p, p, t, v], default=v)
    rgb[..., 1] = np.select(conditions, [v, v, v, q, p, p], default=t)
    rgb[..., 2] = np.select(conditions, [v, p, t, v, v, q], default=p)
    return rgb.astype('uint8')
def hsv_to_rgb(hsv):
    """Input HSV image [0~1] return RGB image [0~255].

    Parameters
    -------------
    hsv : numpy.array
        An image with values between 0.0 and 1.0

    Returns
    -------
    numpy.array
        A processed image.
    """
    # Translated from source of colorsys.hsv_to_rgb
    # h,s should be a numpy arrays with values between 0.0 and 1.0
    # v should be a numpy array with values between 0.0 and 255.0
    # hsv_to_rgb returns an array of uints between 0 and 255.
    rgb = np.empty_like(hsv)
    rgb[..., 3:] = hsv[..., 3:]
    h, s, v = hsv[..., 0], hsv[..., 1], hsv[..., 2]
    i = (h * 6.0).astype('uint8')
    f = (h * 6.0) - i
    p = v * (1.0 - s)
    q = v * (1.0 - s * f)
    t = v * (1.0 - s * (1.0 - f))
    i = i % 6
    conditions = [s == 0.0, i == 1, i == 2, i == 3, i == 4, i == 5]
    rgb[..., 0] = np.select(conditions, [v, q, p, p, t, v], default=v)
    rgb[..., 1] = np.select(conditions, [v, v, v, q, p, p], default=t)
    rgb[..., 2] = np.select(conditions, [v, p, t, v, v, q], default=p)
    return rgb.astype('uint8')
Input HSV image [0~1] return RGB image [0~255].

    Parameters
    -------------
    hsv : numpy.array
        An image with values between 0.0 and 1.0

    Returns
    -------
    numpy.array
        A processed image.