To extract a subject from an existing image with GPT Image 2, use the image-edit workflow, request a fully transparent background, and set the output format to PNG. Then inspect the saved file itself: a checkerboard preview alone does not prove it contains transparency. OpenAI documents transparent backgrounds as a preview capability, so treat the prompt as an instruction—not a guarantee of clean edges or exact preservation.
Choose editing for an existing image
Background removal from a supplied photo is an image-edit task: provide the source image and describe what should remain and what must be removed. Use image generation when you want a new asset created from a prompt rather than an extraction from an existing image. OpenAI’s image prompting guide describes both generation and editing for GPT Image 2.
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For the documented edit endpoint, the Python reference lists PNG, WebP, and JPG inputs under 50 MB, with up to 16 images accepted. These are endpoint constraints, not general rules for every interface that may use the model; check the current image edit API reference before relying on them. The endpoint also documents a mask option, but a mask is not required for an ordinary prompt-based extraction.
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Prepare the source and write a specific prompt
Choose an image where the subject is identifiable and important edges are visible. State what to isolate and which details matter, such as shape, color, or readable labels. A useful starting prompt is:
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Extract the subject and isolate it on a fully transparent background. Preserve its geometry, color, and readable details. Keep clean edges without halos or fringing. Do not add a backdrop, checkerboard, scenery, or shadow.
Adapt the instructions to the subject—for example, call out a product label or a fine outline that must remain visible. These criteria tell the model what to aim for; they do not guarantee exact preservation or flawless edges. OpenAI’s prompting guide includes similar guidance for preserving geometry and legibility while avoiding halos and unwanted backgrounds.
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Request transparent output in PNG format
Set the background to transparent and the output format to png. The OpenAI image API reference lists transparent, opaque, and auto background settings, and specifies PNG or WebP for transparent output. PNG is the direct choice when the deliverable must be a transparent PNG; WebP is an alternative only if the receiving workflow supports it. Do not use JPEG for a transparent deliverable.
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GPT Image 2 transparent backgrounds are documented as preview support in both the prompting guide and the image generation API reference. The edit endpoint accepts an image and prompt and supports a transparent-background parameter; consult the current edit API reference for its available settings.
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Check the saved PNG before delivery
Review the file you saved, not just the model’s preview. Look for the common problems named in OpenAI’s prompting guidance: halos or fringing, an imperfect silhouette, altered geometry, illegible labels, and unwanted shadows or backgrounds. A practical check is to open the PNG over both light and dark solid backgrounds and zoom in around fine edges.
- Confirm the subject’s outline is not clipped and important details remain legible.
- Check that no checkerboard pattern was baked into the image. A checkerboard shown by a preview can simply be a display convention, not proof of alpha transparency.
- Use an image editor that displays transparency, or a metadata-capable tool, to confirm that the saved file actually contains transparent pixels.
This is a practical visual and file check, not a formal validation standard prescribed by the cited OpenAI pages. The reviewed documentation does not specify a certification method for alpha transparency.
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Save and hand off the right file
Save the returned image data as a .png file, then open that saved file to verify it. OpenAI’s guide includes an example that decodes returned base64 image data and writes a PNG, illustrating that the deliverable is the saved file rather than merely an on-screen preview. Before handing it off, confirm the recipient can accept PNG transparency and meet any separate project requirements for dimensions, color, or filename; the cited API documentation does not establish a general delivery or color-profile policy.
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