Permalink to Image OperationsImage Operations

Three packages work on a picture and hand back a picture. None of them produces a Track: each output is an image you reference downstream — as a Seedance reference frame, as a Media Item, or as the source of another operation.

They all need an endpoint. image-compose and image-transform ask for the raster capability, which @hypit/provider-image-opencv-local answers by running OpenCV in a bounded Python process on your own machine; background-removal asks for its own capability, which @hypit/provider-kie answers remotely. Select the supporting Endpoint in your Runtime Profile when using these operations.

Permalink to composing-layersComposing layers

compose:Image paints layers onto one canvas, in the order they are written, and hands back a PNG.

<import as="compose" from="@hypit/image-compose@1"/>

The element takes id and canvas, and optionally background — which must carry alpha, as #RRGGBBAA, and defaults to fully transparent. Its children are compose:Layer, at least one and at most sixty-four, each empty:

<compose:Image id="card" canvas={portrait} background="#00000000">
  <compose:Layer source={background.image} frame={full} fit="cover"/>
  <compose:Layer source={product.image} frame={product-frame} fit="contain"/>
</compose:Image>

Output: {card.image} — an image, not a Track.

Permalink to correcting-an-imageCorrecting an image

An image:Program is a named list of operations; an image:Transform runs one over a source. The split is deliberate: a program written once is applied to every shot that needs the same treatment.

<import as="image" from="@hypit/image-transform@1"/>

image:Program takes only id, and holds its operations as children, applied in the order written:

A program may hold at most one Encode, and it must be last. Every operation but Blur, Rotate and Crop runs on defaults alone, so <image:Denoise/> is a complete instruction.

image:Transform takes id, source and program, all required.

<image:Program id="clean-gpt-image">
  <image:Denoise/>
  <image:Encode format="png"/>
</image:Program>

<image:Transform id="clean-shot" source={shot.image} program={clean-gpt-image}/>

Output: {clean-shot.image}. The program on its own produces no image — it is a recipe, and naming it in a Transform is what runs it.

Permalink to removing-a-backgroundRemoving a background

<import as="remove" from="@hypit/background-removal@1"/>

remove:Background is empty and takes id and source. It picks no model, threshold or storage — that is the endpoint's business, not the Source's.

<remove:Background id="cutout" source={portrait.image}/>

Output: {cutout.image} — typically fed to a Media Item so a presenter sits over the picture rather than in a box.

Permalink to removing-a-moving-persons-backgroundRemoving a moving person's background

For a presenter over another picture, process the generated or supplied video with @hypit/volcengine-matting, served by a supporting HypiHub Endpoint:

<import as="matte" from="@hypit/volcengine-matting@1"/>
<matte:Portrait id="cutout" source={performance.video}/>

Normalize cutout.video to prepare it for the timeline. If it establishes the spoken program, align that prepared media to its Script Segment and assemble it through Speech Track. Present the picture with Media Track or a project scene, at the chosen location and paint order. As B-roll, the normalized cutout can enter Media Track directly. Matting changes the picture's background; the composition determines its role.