AI Inpainting for Perfect Image Edits
Fix unwanted objects or fill missing areas in photos using AI inpainting. See how GPT-Image 2.0 and Flixly tools deliver clean results on real files without artifacts.
TL;DR
AI inpainting with GPT-Image 2.0 on Flixly removes objects from 4000x3000 photos at 9 credits for a 2048 mask. Upload to the image-to-image tool, draw the mask, and generate. Results keep lighting and texture consistent on product shots and portraits while basic editors leave drift or repetition.
Removing a stray power line from a product photo without leaving a blurry patch or mismatched texture takes precision that most free tools still can't deliver.
Users hit this when a client photo has a reflection in a window or a logo that must disappear before upload. The result is either obvious cloning artifacts or hours spent in manual masking.
The Daily Inpainting Headache
A 4000x3000 product shot arrives with a price tag sticker on the front. Standard clone tools copy surrounding pixels but shift the wood grain. The final file shows a repeating pattern that fails QA.
Another case involves a portrait where a microphone boom crosses the frame. Masking it out leaves skin tones that do not match the neck shadow. Both examples cost time on revisions.
Why Basic Tools Fall Short
Free web editors apply small diffusion passes that stop at 512-pixel masks. Larger areas produce color drift or texture repetition. Batch processing often resets the mask on every new layer.
Local software requires GPU memory above 8 GB for anything beyond 1024x1024. Export settings then compress the file and reintroduce noise around the edited zone.
How Flixly Handles Inpainting with GPT-Image 2.0
Flixly routes the masked area through GPT-Image 2.0 at 2048-pixel context. The model samples the full image before generating the fill. This keeps lighting direction and material grain consistent.
Users start at the Image to Image page. They upload the base file, draw the mask, and select GPT-Image 2.0 from the model list. A 2048x2048 section processes in one pass.
The same workflow supports FLUX Kontext for tighter color matching on skin or fabric. Results export as PNG with alpha preserved.
Step-by-Step Inpainting Workflow
Upload the source to AI Image Tools.
Draw or paste the mask over the area to replace.
Choose GPT-Image 2.0 or FLUX Kontext and set strength to 0.75.
Run the generation. Preview shows three variants.
Download the clean file or push it to Image to Image for further compositing.
Mask Types That Work
- Hard edge masks for logos and text
- Soft feather masks for hair or shadows
- Multiple disconnected masks in one job
Output Sizes Tested
- 1024x1024 at 4 credits
- 2048x2048 at 9 credits
- 4096x4096 at 18 credits
Limits and Edge Cases
Transparent objects such as glass still produce refraction errors. Reflections on metal require a second pass with adjusted strength. Very large masks above 40 percent of the frame can drift from source lighting.
Text that overlaps the mask area needs a separate Text to Image generation to rebuild lettering.
Comparison of Inpainting Models
| Model | Max Mask Size | Typical Credit Cost | Best Use Case |
|---|---|---|---|
| GPT-Image 2.0 | 2048 px | 9 | Product photos |
| FLUX Kontext | 1536 px | 7 | Portraits and fabrics |
| Seedance 2.0 | 1024 px | 5 | Quick background fixes |
FAQ
How large can the mask be before quality drops? GPT-Image 2.0 maintains detail up to roughly 40 percent of a 2048-pixel image before lighting mismatch appears.
Does inpainting work on transparent PNGs? The pipeline accepts alpha channels and returns the edited layer with transparency intact.
Can I use the same mask across multiple frames? No. Each generation treats the mask as a single image task. Video frame sequences require the separate Image to Video flow.
What file formats are supported for upload? JPEG, PNG, and WebP up to 25 MB each.
Is there a way to preview before credits are spent? The dashboard shows a low-resolution draft at no cost before the final run.
How do I keep consistent skin tones across two separate edits? Run both edits in one session with the same seed value and reference the first output as a second mask layer.
Frequently Asked Questions
How large can the mask be before quality drops?▾
GPT-Image 2.0 maintains detail up to roughly 40 percent of a 2048-pixel image before lighting mismatch appears.
Does inpainting work on transparent PNGs?▾
The pipeline accepts alpha channels and returns the edited layer with transparency intact.
Can I use the same mask across multiple frames?▾
No. Each generation treats the mask as a single image task. Video frame sequences require the separate image-to-video flow.
What file formats are supported for upload?▾
JPEG, PNG, and WebP up to 25 MB each.
Is there a way to preview before credits are spent?▾
The dashboard shows a low-resolution draft at no cost before the final run.
