Remove an old price from a product photo
Clear an outdated price or campaign label from an authorized catalog image before preparing the next version.
Remove text in image files such as captions, labels and dates. AI estimates the area hidden by the lettering from nearby visual context, so you can review and download a clean 2K result without Photoshop.
Upload an image and click Remove Image Text
By clicking Generate, you confirm you own or are licensed to edit this image and that the edit is not intended to deceive a third party—including visa or immigration submissions, fake refund or transaction proofs, and email or chat screenshots altered to falsify sender, content, or timestamp.
We do not process IDs, passports, visa support letters, official seals, bank statements, or tampered receipts. Violations result in account termination without refund; request logs are preserved and may be shared with law enforcement, including authorities in the intended victim's jurisdiction. See Acceptable Use.
Upload an image and submit your changes to see the result.
Use the same focused workflow for an old product price, screenshot note or poster message.
Clear an outdated price or campaign label from an authorized catalog image before preparing the next version.
Remove an obsolete UI note, username or tutorial annotation before adding accurate replacement information.
Clean a date, short headline or promotion from owned artwork while keeping the surrounding composition available for reuse.
There is no manual masking step: upload, process, then inspect the reconstructed area.
Choose a clear JPG, PNG, WebP or GIF that you own or have permission to modify.
The image text remover detects visible lettering and estimates the pixels hidden behind it from the surrounding scene.
Inspect edges, patterns and faces at full size. Download the 2K result, or retry when a complex area needs another pass.
Every removed word hides part of the source image. The AI creates an estimate from what remains visible around it.
Plain color, open sky and gentle blur provide consistent context. Short, sharp lettering over these areas is usually the most predictable starting point.
Busy textures, repeated patterns, gradients, faces and large covered areas require the model to infer more missing detail. Inspect the result closely and expect that some images need a retry or manual retouching.
Content teams, online sellers, documentation writers and individual creators use it when visible words should disappear rather than be replaced.
Clean obsolete UI copy, labels and annotations from product documentation or tutorials.
Remove an old price, supplier note or campaign badge from catalog images you may edit.
Erase an expired date, event line or social caption before creating a new version.
Clean a date stamp, caption or short note while retaining an untouched source copy.
It removes text that is baked into flattened image pixels and returns a finished picture. It does not create an editable text layer or preserve the hidden original pixels.
Start with the clearest source, process one authorized image, then check fine edges and patterns at full size before publishing the download.
Choose the workflow according to speed, background complexity and the control the final image requires.
Best for a quick first result without drawing a mask, sampling pixels or learning retouching controls. The model automatically finds visible text and rebuilds the area.
Better when a retoucher needs exact area selection, manual pixel sampling and fine control over repeated patterns, faces or important object boundaries.
Understand reconstruction limits, supported files and responsible use before processing.
Choose the next tool based on what the finished picture should contain.
Replace existing wording while following its visible typography and effects.
Edit text in image →Provide the current phrase and the exact replacement for a focused update.
Change text in image →Translate visible copy and rebuild it for a different language.
Translate text in image →Upload an authorized file, review the reconstructed background and download the result.
Remove text from image