AiPicDetect frequently asked questions

It reports a probability, not a verdict. Scores near 50% are labelled Uncertain; treat any single result as a signal and combine it with other evidence. Read more on how accurate AI image detectors are.

On this public instance, yes: the picture is uploaded to the AiPicDetect server (a Google Cloud Run container run by the author), scored in memory and never written to disk. The scrubbed copy is held in memory only until 100 newer results replace it or the container restarts, and nothing is sent to a third-party API. If you want nothing to leave your machine, run AiPicDetect yourself with one Docker command. Details are on the privacy page.

Yes. The code, the Docker image, the CLI and the GitHub Action are all in the AiPicDetect repository under the MIT licence. The detector is an open Hugging Face model you can inspect or replace.

Yes. After checking a picture, use Download clean copy. AiPicDetect rebuilds the image from its pixels, so EXIF, XMP, IPTC, C2PA and the ICC profile are all left behind. How the scrubber works.

JPEG, PNG, WebP, HEIC/HEIF and most formats Pillow can decode, up to 50 MB.

C2PA content credentials and editing-software tags are provenance hints. The panel shows which blocks (EXIF, XMP, IPTC, C2PA, ICC) the file carries so you can weigh them alongside the score. See C2PA content credentials and how to remove image metadata.

Yes. Set AIPICDETECT_DETECTOR_MODEL to any Hugging Face image-classification model whose labels name AI/fake vs. human/real content.

Yes. AiPicDetect is open source under the MIT licence. The hosted instance is free to use with a limit of 10 analyses per IP address every 24 hours; a self-hosted copy has no limit.

It runs, but re-encoding, resizing and screenshots remove some of the pixel-level traces the classifier relies on, so expect lower confidence and more Uncertain results.

No. AiPicDetect scores generated-versus-real pixel statistics in general; it does not identify the generator, and it has no knowledge of generators released after its model's training data was collected.

Heavy filters, HDR processing, upscaling, illustrations and 3D renders share statistical features with generated images. The score is a probability, not proof; false positives happen.

Yes. After the first run downloads the model into the Hugging Face cache, a self-hosted AiPicDetect needs no network access.

Yes: 10 analyses per client IP in any rolling 24-hour window. Responses carry X-RateLimit-Remaining, and a request over the limit returns 429 with a Retry-After header.