AI-powered object removal using LaMa (Large Mask Inpainting).

Remove unwanted objects from photos by providing an image and a binary mask indicating what to remove.

This model uses the LaMa architecture with Fast Fourier Convolutions, designed for high-quality inpainting of large areas, complex textures, and high-resolution images.

How it works: Upload your image and a mask. The model analyzes surrounding context and fills in the masked areas with matching textures and patterns.

Common uses: - Remove people, objects, or distractions from photos - Clean product images for e-commerce - Remove furniture or elements from real estate photos - Edit photos for social media - Prepare images for design and compositing

Inputs: - Image: Your photo (JPEG or PNG) - Mask: Binary mask (white = remove, black = keep) - Resolution: Supports up to 2048px

Performance: ~2-3 seconds per image on T4 GPU

API-ready: Simple REST API with JSON input/output. Built for integration into apps, workflows, and automated pipelines.

See the application here (Built on top of this replicate model): https://www.imgour.com/image-object-remove/