BGCut

How it works

From uploaded photo to editable transparent cutout

BGCut turns an image into a transparent PNG through steps you can inspect at every point that matters. Automatic segmentation does the first pass; comparison and refinement resolve what automation misses.

The five steps of every image

  1. The browser validates the image

    Choose files, drag them in, paste from the clipboard, or start with a sample. BGCut accepts PNG, JPG, WebP, HEIC, and HEIF up to 20MB each, ten images per batch. The server checks the file again — actual decodability, not just the extension — so damaged uploads fail with a clear error instead of a bad result.

  2. A model estimates the subject mask

    RMBG (the default) or BiRefNet analyzes the image and estimates which pixels belong to the foreground. The output is a soft alpha mask, not a rectangular crop, so hair, fabric, and anti-aliased edges keep partially transparent pixels. Processing time, output size, and peak GPU memory are reported for every run.

  3. Preview backgrounds expose edge problems

    A cutout can look fine on the checkerboard while carrying a pale halo from its old background. Switch between transparent, white, and soft-gray previews, and drag the before/after slider. Previews never change the exported file.

  4. Smart and manual tools correct the mask

    Smart erase removes a connected object near a stroke; smart restore does the inverse. Manual brushes give pixel-level control with adjustable size and hardness. Every operation can be undone, and reset always returns to the model output — experimenting is safe.

  5. Export as a real transparent PNG

    The result downloads as a PNG with its alpha channel intact, plus an optional baked shadow for product shots. Nothing is stored as a permanent gallery, and no account is involved.

Try BGCut