Decode a QR code trapped inside a PDF or a phone screenshot without needing a camera.
Check a Pix payment QR code's payee, amount, and tamper status before paying.
Verify whether a QR code link points to the real domain or a lookalike/shortener.
Share a PDF from a messaging app directly into the qrme app on Android to decode it.
| lggurgel/qrme | 0xallam/my-recipe | 0xhassaan/nn-from-scratch | |
|---|---|---|---|
| Stars | 0 | — | 0 |
| Language | Python | Python | Python |
| Last pushed | — | 2022-11-22 | — |
| Maintenance | — | Dormant | — |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 2/5 | 4/5 |
| Audience | general | general | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires Docker and Docker Compose installed, setup is a single make up command.
qrme solves a very specific annoyance: you have a QR code trapped inside a PDF or a screenshot on your phone, and you cannot point your phone's camera at its own screen to scan it. Instead, you upload the PDF or photo to qrme and it decodes every QR code inside it on the server, handing you back the content as text you can copy. No signup is required, and the uploaded file is deleted right after decoding. The results are more than plain text. qrme looks at what kind of QR code it found and organizes the answer accordingly. A Pix payment code, for example, shows the payee, the amount, and a check confirming the code has not been tampered with. A link shows the real underlying domain along with warnings if it uses a link shortener or looks like it is imitating another domain. Wifi passwords, contact cards, and two factor authentication codes are also recognized and broken into clear fields rather than dumped as raw text. qrme is installable as a Progressive Web App. On Android, it can register itself in the system share sheet, so you can share a PDF from a messaging app directly into qrme for decoding. On a desktop computer, you can simply paste a screenshot onto the page. Under the hood, the project runs Django for the web API, Celery workers for the actual decoding, Redis as the task queue and cache, and Postgres for the database, all wired together with Docker Compose for local setup. PDFs are converted to images before scanning, and decoding tries a fast library first, falling back to a second method for low contrast or skewed codes. The project takes privacy seriously: uploaded files are deleted immediately after processing, decoded results expire automatically after an hour, and files are checked by their actual content rather than trusted by file extension. It is released under the MIT license.
qrme decodes every QR code inside an uploaded PDF or photo on the server, returning typed, readable results like payment codes, links, and Wifi credentials.
Mainly Python. The stack also includes Python, Django, Celery.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly general.
This repo across BitVibe Labs
Verify against the repo before relying on details.