A room shot too dark, a cafe glowing yellow, a skyline lost in haze, an album print gone flat: say what looks wrong and the fixer corrects the tones in one pass, while a keep-list holds skin tones, whites, and colors where they belong.
Auto tools guess what to change and you accept whatever comes back. Here the sentence is the instruction: too dark, too yellow, too hazy, too flat. Saying it out loud points the fix at the actual problem, and sharpening the wording steers the retry.
Corrections can overshoot: skin turns gray, wood loses its warmth, a white shirt glows blue. The keep-list names what must stay natural, and the fix adjusts the tones around them instead of through them.
Correction works on what the camera captured. A blown-out window stays white because no detail was recorded there, and deep blur stays soft because the edges were never seen. What a fix can do is large: it re-balances every pixel that did capture the scene.
Generative results can vary, and a first pass sometimes lifts too little or cools too far. Say more: which corner is dark, how strong the cast reads, what must not shift. Failed tasks refund credits, so dialing in a fix costs patience, not money.
An AI image fixer repairs photos that are tonally wrong: shot too dark, warmed into orange by indoor bulbs, hazed over by distance, or faded by years in a drawer. Auto tools guess at the correction and sliders demand the vocabulary; this fixer takes the diagnosis as a sentence instead. You name the defect and how strong it reads, list the colors that must stay natural, and generate. It handles the four common tonal defects in one place, and it pairs naturally with the named-target tools next door: an unwanted object goes to the object remover, a shadow across a face goes to the shadow remover, and whatever the scene needs after that can happen to fix photos online for free in the same editor.
Fix your photo online for freeFive steps from a defective photo to a clean download. The whole loop runs in the editor on this page, in the browser, with nothing to install.
Drop in a JPEG, PNG, or WebP up to 20MB. Photos with a clear defect and some untouched highlight and shadow room give the fix the most to work with.
Say what reads wrong and how much: "shot too dark, faces barely visible" beats "make it better". Then the keep-list: skin tones natural, whites neutral, colors true to the room.
Keep the original ratio for most fixes. 1K at 3 credits fits inside the daily free allowance, and bigger sizes cost more credits when you need them.
Set the result beside the original. Whites should read white, shadows should hold detail, and nothing should have moved: a fix that rearranged the scene is a wrong fix.
Download full resolution with no watermark, or keep going in the same workspace: sharpen next, remove a leftover object, or resize for where the photo is headed.
Auto-enhance pushes every photo toward the same glossy default, whether it needed it or not. Naming the defect keeps the fix on the problem, so the photo still looks like your photo afterward.
Exposure, temperature, tint, dehaze: the sliders exist whether or not you know their names. Here you say "too yellow" and the equivalent correction happens without touching a curve.
Downloads are full resolution and watermark-free, and every fix stays in your workspace. Send the corrected frame to the enhancer for sharpening, or the old-photo restorer when the damage is physical.
Three ways to get the same job done. The honest differences, not a product takedown.
| Dimension | Manual editor | Auto-fix tools | This image fixer |
|---|---|---|---|
| Pointing at the problem | Pick the right slider and judge the amount | One button; the model decides what to change | Name the defect and its strength in the prompt |
| Protecting the rest | Masking and careful slider work | Whatever the preset preserves | Keep-list in the prompt: skin tones, whites, true colors |
| Defects per edit | One slider per defect, one photo at a time | One combined pass, no per-defect control | Several named defects can go in one sentence; one photo at a time |
| Output | Whatever your software exports | Often re-generated at fixed sizes, sometimes watermarked | Original ratio, full-resolution download, no watermark |
| Learning curve | Learn exposure, temperature, tint, and curves | Low, but you accept what you get | A sentence: defect, strength, keep-list |
| Rerunning | Undo and re-adjust the sliders | Press the button again and hope | Rerun with a sharper description; failed tasks refund credits |
The prompt is the whole control surface. These three rules cover most of what goes wrong.
Fix the [defect] in this photo; keep [skin tones, whites, colors] natural.
Too vague
“Make this photo look better.”
More useful prompt
“Fix the underexposure in this living room photo and lift the shadows to natural brightness; keep the wall color and wood tones true.”
Too vague
“Remove the yellow from my photo.”
More useful prompt
“Fix the orange tungsten cast and bring the whites back to neutral; keep skin tones healthy and the wooden table warm.”
Too vague
“Make the city clearer.”
More useful prompt
“Fix the gray haze over the skyline and restore contrast and color depth; keep every building edge in place and do not redraw the scene.”
Most everyday photos now come from a phone, and the misses are tonal: a dim restaurant, a yellow living room, a washed-out sky. An ai image fixer turns those near-misses into keepers in one sentence, without an editing app.
Product shots that drift warm or read dim erode trust at the listing. Sellers run the ai image fixer over a batch before it goes live, keeping colors true so the item that arrives matches the photo.
Scans and inherited prints fade toward yellow and gray. Keepers re-balance them a sentence at a time, then hand physically damaged originals to the old-photo restorer for tears and scratches the fixer cannot judge.
Practical guides and product updates from the team.
How the fixer works, what photo color correction it covers, and where its recovery limits sit.
Upload one defective photo, name what reads wrong, and compare the correction to the original before you download.
