Free Batch Object Remover: 100% Private

Beyond Traditional Retouching

In traditional photo editing software, removing an unwanted object required meticulous manual labor with clone stamps and patch tools. An editor had to find an appropriate source area with similar lighting and texture, feather the edges, and painstakingly paint over the unwanted item. This method often left noticeable seams, repetitive patterns, and unnatural lighting breaks.

An AI object remover takes a different approach: you mark the region to change, and an inpainting model generates replacement pixels using the surrounding image as context. This can create a plausible continuation of a wall, sky, or texture, but it cannot reveal the hidden original pixels.

Modern Inpainting in the Browser

EraseKit uses an image inpainting model to generate a fill for the selected region. This process estimates plausible content from surrounding context; it does not reveal hidden pixels. See this CVPR research paper on image inpaintingfor technical background.

The app loads the model and runs it with ONNX Runtime Web. It tries WebGPU when available and supported, then uses WebAssembly when WebGPU cannot be used. Image processing stays in the browser; site and model downloads are separate network requests.

Remove Unwanted Objects

Street furniture, power lines, trash receptacles, stray plastic bottles, construction cones, and road signage frequently compromise otherwise pristine landscape or street photography.

With EraseKit, a brief stroke with the brush highlights the intrusion. The AI inpainter fills the gap with the continuous texture of the sidewalk, brickwork, or greenery, restoring your scene's natural balance.

Remove Background Crowds

Capturing memorable portraits at popular travel landmarks often means unintentionally photographing dozens of tourists in your frame.

EraseKit reconstructs architectural facades, staircases, and horizons behind unwanted people. Remember to paint over ground shadows and water reflections to maintain realistic lighting consistency.

Remove Logos and Watermarks

Prominent date stamps, camera watermark overlays, sponsored logos on clothing, or stickers on products can detract from an image's aesthetic focus.

EraseKit can attempt to fill selected visible marks using nearby image context. Detailed surfaces may not reconstruct cleanly, so inspect the result.

Ideal Scenarios for Apply to All

• Camera timestamps & date marks: Images exported from security cameras, trail cameras, or vintage digital cameras that embed fixed date stamps in the lower corner.
• Fixed watermark & logo overlays: Photo collections exported from templates where a watermark or brand logo sits in the exact same proportional margin on every photo.
• Tripod-mounted photography sequences: Timelapse frames or bracketed exposures where an immovable obstruction (a railing, microphone boom, or sensor dust spot) remains stationery.
• Studio product catalogs: Product photos shot with a fixed camera rig on a lightbox where staging clips or tape marks appear in uniform positions.

When Individual Selection Is Preferred

• Dynamic, moving subjects: Photobombers walking across different parts of the frame in successive shots require painting over their new position on each image.
• Handheld photography with shifting angles: If the camera perspective or horizon shifts between shots, fixed coordinates will not align with the target object.
• Mixed aspect ratios with variable framing: If your batch mixes square Instagram crops with panoramic landscapes, coordinate scaling may shift slightly relative to the visual content.

EraseKit works well for

• Removing a selected distraction when surrounding image context can guide a plausible fill.
• Repeating one selection across up to 30 images when framing and target position match.
• Editing locally in the browser without uploading images to an EraseKit processing server.
• Exporting to a canvas with the same dimensions as the source image.

Consider another workflow when

• You need the exact hidden original content; inpainting generates an estimate.
• The target moves or changes position between images; Apply to All repeats coordinates and does not track objects.
• You need fine manual control over details around the selected area.
• The image requires high-detail retouching; large-image processing scales the generated patch back to the original canvas.

PNG, JPG & WEBP

EraseKit accepts PNG, JPG/JPEG, and WebP images. PNG results are exported as PNG; JPEG and WebP results are re-encoded to their respective formats.

Up to 30 Images per Session

To ensure stability across devices with varying memory capacities, EraseKit supports batch sessions of up to 30 images at once. Once finished, download them all in a single compressed ZIP archive.

Adaptive WebGPU & WASM

EraseKit tries WebGPU when available and supported. If WebGPU is unavailable or fails, it uses WebAssembly. Processing time varies by device, browser, image dimensions, and available memory.