Function create_gif

plib/render.py:467–520

Create a gif from the images Args: images: (n, h, w, 3) or list of (h, w, 3), float, range = 0-1 filename: filename of the output gif

(
        images: T.Union[torch.Tensor, np.ndarray, T.List[torch.Tensor], T.List[np.ndarray]],
        filename: str,
        fps: float,
        loop: bool = True,
)

def create_gif(
        images: T.Union[torch.Tensor, np.ndarray, T.List[torch.Tensor], T.List[np.ndarray]],
        filename: str,
        fps: float,
        loop: bool = True,
):
    """
    Create a gif from the images

    Args:
        images:
            (n, h, w, 3) or list of (h, w, 3), float, range = 0-1
        filename:
            filename of the output gif
    """

    assert filename.lower().endswith('gif'), f'{filename}'
    if isinstance(images, torch.Tensor):
        images = images.detach().cpu().numpy()

    if isinstance(images, (list, tuple)):
        images = [
            img.detach().cpu().numpy() if isinstance(img, torch.Tensor) else img
            for img in images]

    if isinstance(images, np.ndarray):
        images = [images[i] for i in range(images.shape[0])]

    # make sure the range is 0-255
    images = [(np.clip(img, a_min=0, a_max=1) * 255).astype(np.uint8) for img in images]

    # numpy to pil image
    images = [Image.fromarray(img) for img in images]

    # avoid dithering
    try:
        images = [img.quantize(method=Image.Quantize.MEDIANCUT) for img in images]
    except:
        images = [img.quantize(method=Image.MEDIANCUT) for img in images]

    # save gif
    images[0].save(
        filename,
        save_all=True,
        append_images=images[1:],
        optimize=False,
        duration=int((1000 + fps - 1) / fps),
        loop=loop,
    )

    # save png for first image as a reference
    images[0].save(
        filename[:-4] + '_oneimg.png'
    )


def gif_to_nparray(