# GSoC 2026 – Question about QR/Barcode/ArUco Deep Detector project

**URL:** <https://forum.opencv.org/t/gsoc-2026-question-about-qr-barcode-aruco-deep-detector-project/24274>\
**Category:** Uncategorized\
**Tags:** gsoc\
**Created:** [December 22, 2025, 4:40pm UTC](https://forum.opencv.org/t/gsoc-2026-question-about-qr-barcode-aruco-deep-detector-project/24274 "2025-12-22T16:40:24Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Satya\_sravanthi\_Mand](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.opencv.org/satya_sravanthi_mand/32/12792_2.png) [@Satya\_sravanthi\_Mand](https://forum.opencv.org/u/Satya_sravanthi_Mand)\
**Post date:** [December 22, 2025, 4:40pm UTC](https://forum.opencv.org/t/gsoc-2026-question-about-qr-barcode-aruco-deep-detector-project/24274/1 "2025-12-22T16:40:24Z")

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Hello mentors,

I’m interested in the QR/Barcode/ArUco deep detector project for GSoC 2026.  
I tested the existing ONNX-based deep detector using OpenCV DNN and verified  
the input preprocessing (1×3×640×640) and multi-scale outputs.

When testing on clean QR images, I observed low confidence compared to  
OpenCV’s classical QRCodeDetector, which suggests room for improving  
generalization.

I’m planning to prototype a lightweight YOLO-style detector, export to ONNX,  
and evaluate it using OpenCV DNN before extending to Barcode and ArUco.

I’d appreciate your guidance on whether this approach aligns with the  
project expectations.

Thank you.