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Try FLUX Erase in the Workbench

Run this model interactively, tune parameters, and compare outputs.
Model ID: flux-erase FLUX Erase removes whatever a mask covers and rebuilds the scene behind it, matching the surrounding lighting, texture and background so nothing looks patched. Objects, people, text, watermarks and whole compositions can be taken out. There is no prompt: the mask alone says what goes. The mask is a black-and-white image at the same resolution as the input, white where pixels are to be removed and black where they are kept. A dilation setting expands the mask edge by up to 25 pixels before removal, which helps with soft-edged subjects and shadows. The output keeps the input’s size. The model was trained at about 1 megapixel across aspect ratios from 1:2 to 2:1, and inputs near that range give the best results.

Example request

Use the Workbench as a request builder: configure parameters for this model in the UI, then open the API tab to copy the exact cURL or Python call.
See the image editing reference for more details.

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Request parameters

Required parameters

Optional parameters