Checking Midjourney output
QA your Midjourney images before your audience does
Midjourney produces some of the most polished AI imagery available — which is exactly why its failures are dangerous: they hide inside pictures that look finished. A beautiful frame with a six-fingered hand, a melted logotype or a headline that almost spells the word is worse than an ugly draft, because it gets approved. Chekr scans the finished image, not the model, so every Midjourney version is covered.
What typically goes wrong in Midjourney images
- Rendered text that degrades on longer words, prices and non-English strings
- Hands and interlocking fingers in multi-person scenes
- Props and jewellery that melt where they touch skin or fabric
- Background objects that are almost — but not quite — real things
- A strong house style that can drift from your brand guidelines
How Chekr checks it
Upload the exported image (or send it via the API) and Chekr runs all nine checks on the pixels themselves: text and typography, anatomy, artifacts, object physics, texture coherence, lighting, brand rules, provenance and reverse-image IP risk. Because the scan judges output rather than the generator, it works identically for every Midjourney version, style reference and personalization setting.
Findings come back pinned on the image with severity and confidence, and most carry a one-click fix that regenerates only the affected region — the garbled word, the extra finger — leaving the rest of the frame exactly as Midjourney made it.
Frequently asked
Does Chekr work with any Midjourney version?
Yes. Chekr inspects the finished image, not the model, so V6, V7 and whatever ships next are all covered the moment you upload the output.
Midjourney keeps improving — do I still need QA?
Failure rates fall with each version, but they do not reach zero, and volume multiplies whatever remains. One bad image in a hundred is still a bad campaign asset every week for a team generating daily.
Can Chekr check whether a Midjourney image is too close to an existing photo?
Yes — the IP-similarity check runs a web-scale reverse-image search and returns the closest match with a similarity score, so you see proximity to existing work before you publish, not after someone else does.