Remove captions, titles and date stamps from an image you own, then compare the rebuilt area with the texture and objects around it.
Layout preview — image with overlaid text. This is not a generated result.
The same coastal photo before and after its overlaid text is removed. The text remover rebuilds each covered area from what surrounds it, so judge the repair at the size you will use.
Captions, titles, subtitles, text banners, date stamps and text stickers laid over the image are removed, and the covered area is reconstructed to match the surrounding texture, color and light. The rebuilt area is generated, not recovered, so it cannot reveal what the overlaid text was hiding.
Wording that belongs to the scene, such as signs, street names, product packaging and printed text on objects, is meant to stay. The match is not infallible: a label, a sticker and a graphic caption can look alike, and there is no brush to protect one line of overlaid text.
Start with the exact spots where letters sat: faint outlines, repeated patches and sudden gradient changes in the sea, sky or walls. Then compare faces, edges and colors across the whole image, because the image is regenerated and unmarked pixels are not guaranteed to stay identical.
Use the text remover on images you own or may edit, then add your new wording in a layout tool.
DateClean background
Reuse the artwork when only a flattened export of your own poster is left. The tool cannot protect the venue line while removing the date, so other overlaid text can change too; keep a copy of anything that must stay. Check where letters crossed faces or detailed shapes, then add the new title and date as editable text.
Sale badgeClean product
An expired sale badge or promotional line can come off a product image you own. Look for the clean original in your catalog first. If only the marked image remains, inspect the silhouette, printed packaging and texture near the overlaid text, and do not use a smooth result that changes the product.
SubtitleClean still
Capture the still from an unsubtitled export when one exists, and remove burned-in subtitles only as a fallback. One image cannot consult neighboring frames, so a repair around a moving hand or face can look fine as a thumbnail and fail when enlarged. The text remover works on a single image and does not remove subtitles from a whole video.
Three steps in the panel above.
If the words still live as a text layer in your design file, edit or hide that layer instead; an exported image holds only pixels. Otherwise upload a JPEG, PNG or WebP image up to 10 MB that you own or may edit. Each image in a batch is its own task.
There is no selection brush: every piece of overlaid text in the image is targeted, so remove or note anything that must stay. Compare the repaired area with the original before running again. If the overlay hid most of an important subject, repeating cannot supply the true detail.
Text removal costs 60 credits per image, shown on the Generate button before you confirm. The result keeps the upload format and is limited to 2048 pixels on its longest edge, so a larger source returns smaller. Keep the original, then add verified wording in an editable layout.
Four points about removing text from an image: what is targeted, what stays, why there is no brush and how to check the repair.
01
The text remover aims at overlaid text: captions, titles, subtitles, text banners, date stamps and text stickers laid over the picture. The covered area is reconstructed to match its surroundings, so the output is a generated repair, not a recovered original.
02
Signs, street names, packaging and printed text on objects belong to the photograph and are meant to stay. A sticker, a label and a graphic caption can look alike, so check that nothing you needed was repaired away.
03
There is no selection tool: the text remover targets every piece of overlaid text in the image. Upload, press Generate and inspect the repaired area. If a line must stay, copy it first and add it back in a layout tool afterwards.
04
Start where the letters sat: faint outlines, repeated patches and sudden gradient changes in sea, sky or walls. Then compare faces, edges and colors across the whole image, because regeneration can change small things elsewhere. Another pass costs credits again and cannot supply detail the overlay hid.
When the problem is not overlaid text, these tools fit the job better.
A text remover removes overlaid wording from an image and reconstructs the area the wording covered. The Potto AI text remover runs an automatic cleanup aimed at text only, so captions, titles, subtitles and date stamps are targeted without a brush. The output is a generated reconstruction, not a recovered hidden original and not an editable text-layer document. Compare both the repaired region and the whole image.
No. A caption or date stamp is overlaid text placed on top of an image, while a photographed sign, street name or product label is part of the scene. The text remover is built to remove the overlay and keep scene text, but a label, a sticker and a graphic caption can look alike, so identify what should change and review the result accordingly. This automatic workflow has no selection brush that could guarantee the distinction.
This page removes text; it does not typeset replacement wording. After you review the cleanup, add verified new wording in an editable layout, with the correct translation, font and placement for the destination. A text-free output is not a finished localized design.
Yes. If the words still exist as a text layer in your design file, edit or hide that layer there; it keeps the untouched background without asking a model to invent the covered pixels. An exported image combines lettering and artwork into pixels. Use the text remover when only the export is left, and keep the original for comparison.
Upload a JPEG, PNG or WebP image up to 10 MB that you own or have permission to edit. The result keeps the upload format and its longest edge is limited to 2048 pixels, so a larger source returns smaller; keep the full original for work that needs its dimensions. Plans with batch access can process up to 10 images at once, and each image is a separate task that needs its own review. Removing text does not grant rights to the underlying image.
Upload the image and press Generate. The text remover targets every piece of overlaid text in the picture, so there is nothing to select or mask. If a line must stay, such as a caption you still need, make a copy of it first and add it back in a layout tool after the cleanup. Run once, inspect the repaired area, and only then decide whether another pass is worth its credits.
Start with the exact places where the overlaid text sat, looking for faint outlines, dark fragments and repeated patterns. Then compare faces, object edges, colors and framing across the whole image, because regeneration can change small things elsewhere. Finally view the image in its destination layout. A subtle color patch can show on a large plain background even when it is invisible at thumbnail size.
You can upload images before signing in. Removing text opens the sign-in dialog, and the uploads stay in the text remover.
Each image is its own task: a failed one shows the reason and a retry, and its credits are released without affecting the others. Running the text remover again on a finished result is a new, charged request.
Removing text costs 60 credits per image. With several images, each one is priced and charged on its own, and the total appears before you confirm.
Upload an image you own, remove the overlaid text and check the repaired area before you download.
