What is AI Inpainting?
A technology that uses AI to redraw specific areas of an image. It can remove unwanted objects or add new elements while maintaining perfect harmony of lighting and texture.
Interactive Demo
1. Original Image
User uploads an image with an unwanted object (e.g., a rock on grass).
2. Masking
User paints over the unwanted area. This white area tells AI: "Please redraw within this boundary".
3. Diffusion Generation
AI analyzes surrounding texture and lighting. It starts from random noise and gradually "denoises" to predict reasonable fill content.
4. Final Blending
Generated pixels blend seamlessly with the original image. The rock is gone, replaced by natural grass.
Core Principles: From Noise to Image
1. Context Awareness (Encoder)
Not just copy-paste. The AI model first uses an Encoder to observe pixels surrounding the masked area.
🤔 Logic: "I see green grass everywhere, light coming from the left, so the empty space should also be lit grass."
2. Diffusion Model
Where the magic happens. Modern Inpainting is often based on Diffusion Models. AI treats the masked area as pure "random noise".
🌫️ Process: It finds patterns in this chaos, removing noise step-by-step until the noise becomes a clear image matching the surroundings.
3. Latent Space
Calculations often happen in a compressed Latent Space rather than huge pixel space. This allows AI to understand high-level concepts (like "this is a dog").
🧩 Result: Ensures generated objects are semantically correct, not just color-matched but structurally sound.
Common Use Cases
- Remove Objects/Watermarks Tourists in the background? Clean up the background in one click.
- Old Photo Restoration Fix creases, stains, or missing corners on old photographs.
- E-commerce Swap Keep the model but change the coffee in hand to a cola.
- Creative Outpainting Reverse logic of Inpainting, drawing scenery outside the borders.