Repair images using text prompts and masks
Repair images by removing unwanted elements
Clean and restore images using a web server
Enhance faces in images
Restore image clarity and remove blur
Restore and clean images by removing scratches and inpainting
Replace faces in photos easily
Repair images by inpainting missing or unwanted parts
It will enhance and unblur the user images
Repair images by filling in missing parts
Enhance images with advanced restoration
Enhance blurry images to improve clarity
FLUX.1 [Inpainting] is an AI-powered tool designed to restore and repair damaged or degraded images, particularly old photos. It leverages advanced algorithms to fill in missing or corrupted parts of an image using text prompts and masks, ensuring a seamless and natural-looking restoration. Ideal for photographers, historians, and anyone looking to preserve memories, FLUX.1 [Inpainting] is user-friendly and versatile, catering to both casual users and professionals.
• Text-based repair: Use textual descriptions to guide the restoration process. • Mask-guided repair: Define specific areas to repair using masks for precise control. • Compatibility with multiple image formats: Supports various image file types for flexibility. • Automatic damage detection: Identifies and repairs damaged areas without manual input. • High-resolution output: Maintains or enhances image quality during restoration.
What file formats does FLUX.1 [Inpainting] support?
FLUX.1 [Inpainting] supports a wide range of image formats, including JPEG, PNG, TIFF, and BMP, ensuring compatibility with most digital photos.
Can I use my own masks for more precise repairs?
Yes, FLUX.1 [Inpainting] allows you to upload custom masks to specify exactly which areas of the image you want to repair, giving you full control over the restoration process.
How does FLUX.1 [Inpainting] handle heavily damaged images?
FLUX.1 [Inpainting] uses advanced AI algorithms to analyze the surrounding areas and context, enabling it to make educated guesses about missing details, even in heavily damaged images. For best results, provide a clear text prompt or use a detailed mask.