# Saving images

## Current limitations of encoder

- `Libheif` does not support editing files in place(it is not possible just to change metadata)

- `HEIF` format does not provide information in what quality image was encoded

## Save parameters

Method `save` in both `HeifFile` and `Pillow` supports the same parameters. There is only two differences between them:

- Pillow’s `save` by default has `save_all=False` and `HeifFile` has `save_all=True`

- When saving to memory for `HeifFile` you do not need to specify `format` parameter.

Here is description of it: `save()`

## Saving 16 bit images

All 16 bit images that was created with:

- `add_from_pillow()`

- `add_frombytes()`

- or images opened in `I` Pillow modes when using as a Pillow plugin

Will be saved by default in 10 bit mode.

To `save` 16 bit image in 12 bit set `options().save_to_12bit` to `True`.

Images opened from file will be saved based on `info["bit_depth"]` value if it is present.

## Order Of Images

All information here is only for files that has multiply images and when first image in file is not a PrimaryImage

Lets imagine that we have file with 3 images and second image in file is a primary image.

    im = open_heif("image.heif")
    im_pil = Image.open("image.heif")

Both `im` and `im_pil` points to the second image in file, that is a primary image.

This asserts will pass:

    assert im.info["primary"] == True
    assert im[0].info["primary"] == False
    assert im[1].info["primary"] == True
    assert im[2].info["primary"] == False

    assert im_pil.info["primary"] == True
    im_pil.seek(0)
    assert im_pil.info["primary"] == False
    im_pil.seek(1)
    assert im_pil.info["primary"] == True
    im_pil.seek(2)
    assert im_pil.info["primary"] == False

And next code will produce the same behavior results(during enumerating all frames):

    for frame in im:
        print(frame.mode, frame.size)

    for frame in ImageSequence.Iterator(im_pil):
        print(frame.mode, frame.size)

## Primary image when saving image sequences

First image will be primary, unless after first image there is no images with info[“primary”] set to `True`. So, last image with info[“primary”] == `True` will be the primary image.

In most cases you do not need to bother yourself with this, as other image formats are much simpler and has no such abilities.

When you need to change primary image for some reason, just set info[“primary”] of image to `True` and all images after that should not have info[“primary”] == `True`.

Method `save` supports `primary_index` parameter, that accepts `index of image` or `-1` to set last image as PrimaryImage.

Specifying `primary_index` during `save` has highest priority.

## NCLX color profile

By default, since version 0.14.0, if the image already had an NCLX color profile, it will be saved during encoding.

Note

If you need old behaviour and for some reason do not need NCLX profile be saved you can set global option `SAVE_NCLX_PROFILE` to `False`.

To change it, you can specify your values for NCLX color conversion for `save` operation in two ways.

Set output NCLX profile:

> Note

> Avalaible only from 0.14.0 version.

>     buf = BytesIO()
>     im.save(buf, format="HEIF", matrix_coefficients=0, color_primaries=1)

> In this case the default output NCLX profile will be created, and values you provide in such way, will replace the values from default output profile.

Edit NCLX profile in image.info:

>     buf = BytesIO()
>     im.info["nclx_profile"]["matrix_coefficients"] = 0  # code assumes that image has already "nclx_profile"
>     im.info["nclx_profile"]["color_primaries"] = 1
>     im.save(buf, format="HEIF")

> Under the hood it is much complex, as second way will change the input NCLX profile.

The preferable way is to specify new NCLX values during `save`.

Here is additional info, from the libheif repo with relevant information:

https://github.com/strukturag/libheif/discussions/931 https://github.com/strukturag/libheif/issues/995

## Lossless encoding

Note

Parameter `matrix_coefficients` avalaible only from 0.14.0 version.

Although the HEIF format is not intended for lossless encoding, it is possible with some encoders that support it.

You need to specify `matrix_coefficients=0` (which will tell libheif to perform the conversion in the RGB color space) and chrome subsampling equal to “4:4:4”.

    im_rgb = Image.merge(
        "RGB",
        [
            Image.linear_gradient(mode="L"),
            Image.linear_gradient(mode="L").transpose(Image.ROTATE_90),
            Image.linear_gradient(mode="L").transpose(Image.ROTATE_180),
        ],
    )
    buf = BytesIO()
    im_rgb.save(buf, format="HEIF", quality=-1, chroma=444, matrix_coefficients=0)

That’s all.