Remove Unwanted Objects from a Photo
Nothing here is erased. Whatever stood behind the object you want gone was never photographed, so it cannot be recovered — it has to be invented, from what surrounds it and from what scenes like yours usually look like. That means the object leaving is the easy half and never the part that fails. What fails is the replacement, and it fails in ways you can learn to spot in about five seconds.
Use this without the search next time. Prathom Workbench puts Prathom's tools in your toolbar.
Add to Chrome — freeDrop an image here, or click to browse
Up to 25 MB. Uploaded temporarily, deleted after processing.
What it does
- Objects removed and the surface behind them rebuilt
- Perspective and lighting explicitly preserved
- A different reconstruction on every run
- Roughly one megapixel output
How to use Remove Objects
- 1
Check what is behind the thing you want gone
A plain wall, grass, or sky is nearly free. A tiled floor, a bookshelf, or a face is expensive, because all of it has to be reconstructed convincingly.
- 2
Run the removal
The photo is read at about one megapixel and repainted with the unwanted objects absent and the surfaces behind them rebuilt.
- 3
Look at the patterns, not the gap
Follow any repeating structure through the area that was filled. Broken tile grids and interrupted brick courses are what give a removal away.
How it works
Your photo is scaled so its total area is around one megapixel, keeping the original proportions. An image-editing model reads that copy along with a fixed instruction: remove the unwanted objects and reconstruct the surfaces behind them so the scene reads as continuous, preserving the people, the remaining objects, the perspective, the lighting, and the composition, and adding nothing new.
A second instruction names the failures this job actually has — altered subject, changed lighting, warped perspective, blurred patch, cloned artifacts, broken pattern, extra objects, text, watermarks.
The repaint runs at seventy per cent strength, which is higher than the restoration passes on this site because there is real content to build rather than damage to clean. The seed is not fixed, so each run invents a different filling.
There is no ground truth
This is the thing to hold on to when judging a result.
A restoration tool has a target. The scratch covered something that existed, the noise obscured a texture that was really there, and success means getting closer to a thing the photograph is evidence of.
Removal has no such target. The wall behind the bin was not photographed. No information about it exists anywhere in your file. So the model does not recover it — it composes something that would be consistent with everything around it, using what it knows about walls.
That reframes the question. Asking whether the fill is accurate is meaningless, because there is nothing for it to be accurate to. The only question available is whether the fill is consistent, and consistency is something you can actually check.
What to check, in order
Four things, and they take a few seconds.
Repeating patterns first. Tiles, bricks, floorboards, fence slats, panelling, railings. These have a rhythm your eye can count along, so a fill that changes the spacing or drops a unit is visible without effort. This is the single most common giveaway.
Straight lines second. A skirting board, a table edge, a window frame, the join between wall and floor. A line that enters the filled region and leaves it at a slightly different angle is a failure that people notice without knowing why.
Perspective third. Anything receding towards a vanishing point must keep receding at the same rate. The instruction names warped perspective for a reason.
Shadows last. The removed object may have been casting one, and a shadow left behind by something that is no longer there is unmistakable once seen.
Easy backgrounds and expensive ones
The difficulty of a removal is almost entirely a property of what was behind it.
Grass, foliage, gravel, sand, water, sky, wood grain, concrete, and carpet are close to free. They are irregular by nature, so an invented patch has nothing to be checked against — there is no correct arrangement of blades of grass.
Tiles, brickwork, text, patterned fabric, bookshelves, railings, and faces are expensive. Each carries structure a viewer can verify, and a wrong reconstruction is not merely imperfect, it is legible as wrong.
The practical version: before running this, look at what is behind the thing you want gone and decide whether an invented version of it could be checked. If it could, expect to run several attempts, and expect some of them to be unusable.
Publication gate
This page ships once the workflow has been run against an object on an irregular surface, an object against a tiled wall, an object casting a visible shadow, and a scene with strong perspective lines, with each fill checked for pattern continuity and shadow consistency.
Examples
Object on a plain surface
The easy case, and the one worth trying first. Wood grain is irregular, so an invented patch of it cannot be checked against anything.
Object against structure
The hard case. Tiles have a grid your eye can count along, so a fill that shifts the spacing even slightly is obvious immediately.
Frequently asked questions
Can I choose which object gets removed?
Not on this page. There is no brush or selection here — the instruction asks for unwanted objects to go, and the model decides from context what looks unwanted. That usually means small foreign items in an otherwise coherent scene. If several things could qualify, you have no way to say which you meant.
Why does the filled area look slightly wrong even though the object is gone?
Because that area is invented rather than recovered. The model paints something plausible for the surroundings, and plausible is not the same as correct. It goes wrong most visibly where the surroundings contain structure the eye can verify, such as a repeating pattern, a straight edge, or a receding line.
Should I run it again if I do not like the result?
Yes, and this page is built for that. The seed is not fixed, so every run reconstructs the area differently rather than repeating itself. Three attempts on a difficult fill will usually include one that holds together, and comparing them also shows you which parts were guesswork.
Why is my result smaller than the photo I uploaded?
The image is scaled to about one megapixel before the model reads it and generated at those dimensions, keeping the aspect ratio. That also means the whole photograph is regenerated rather than only the patched region, so the untouched parts of the picture are redrawn too.
Is the AI Remove Objects tool free, and do I need an account?
There is no paid tier for Remove Objects, which means there is no free version being held back against one. You do not sign in, you do not enter a card, and the file you download carries no mark. What the page does ask of you is patience with the queue, because the job runs on a shared GPU host and finishes in its own time.