PNG image cleanup
Clean logos, graphics, screenshots and exported designs without first converting the PNG to JPG.
Upload the PNG directly, select all text or describe a specific area, then review the reconstructed background. A flattened PNG may still contain transparency, but visible words are pixels rather than editable type. Check transparent edges after downloading if the source uses an alpha channel.
Try it on your image
Upload JPG, PNG or WebP files. Add a short instruction when only selected text should be removed.
Drag and drop images here, or click to choose files.
JPG, JPEG, PNG or WebP · Up to 20 MB each · Up to 10 images per batch
Step by step
Keep the original pixel dimensions and transparency when it matters to the design.
For UI screenshots and graphics, identify the label by position, color or nearby object.
Inspect logos, icons, line art and any semi-transparent border around the repaired area.
PNG supports transparency but not editable Canva or Photoshop layers. Once a design is exported as PNG, its words become part of the pixel image.
If you have the source design, delete its text layer there. If the PNG is the only file, AI reconstruction can provide a clean background for new wording.
Transparent areas need special review because a generated fill may be opaque. Inspect the downloaded file against both light and dark backgrounds when the alpha channel is important.
For interface screenshots and flat graphics, also check straight dividers, icon edges and small type nearby. Selective instructions help preserve labels that should remain.
FAQ
Yes. PNG is accepted directly, so there is no need to introduce JPG compression before cleanup.
Transparency behavior depends on where the edit occurs. Always inspect the exported alpha edges against contrasting backgrounds.
PNG is a flattened image format. Editable type exists only in the original design or layered source file.
Yes. Identify the label by its location, color or nearby visual and say which other labels must stay.
Keep exploring
Upload a supported image, target all text or selected words and review the reconstructed background.
