{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/22"},{"label":"Utilities","url":"https://skillfed.io/packages/category/utilities/11"},{"label":"Image Recognition","url":"https://skillfed.io/packages/category/scientific-engineering-image-recognition"}],"enrichment":{"capability":"QReader detects and decodes QR codes from images using a YOLOv8 model combined with Pyzbar, handling difficult and damaged QR codes through image preprocessing.","skillfed_tags":["qr-code-detection","computer-vision","yolov8"],"use_cases":["Batch scanning of QR codes from document images or photographs in data entry workflows.","Automated inventory or asset tracking systems that need to read QR codes from imperfect camera feeds.","Mobile app backends that process user-uploaded images containing QR codes.","Quality control in manufacturing: detecting and decoding QR labels on products or packaging.","Archival digitization projects where QR codes may be faded, creased, or partially obscured."],"what_it_does":"QReader is a Python library for detecting and decoding QR codes from images, combining a YOLOv8-based detector with Pyzbar decoding. It specializes in handling difficult QR codes\u2014those that are damaged, poorly lit, rotated, or otherwise challenging\u2014by applying adaptive image preprocessing after detection. The library exposes a simple API: instantiate a QReader object once, then call detect_and_decode() on images to retrieve decoded strings, or call detect() to get bounding boxes and confidence scores for each QR found.\n\nThe package depends on numpy for array operations, opencv-python for image manipulation, pyzbar for the actual QR decoding step, and qrdet (the standalone YOLOv8 detector model). It ships as a pure Python wheel with low install friction. Configuration options include model size (nano to large), detection confidence threshold, character re-encoding for non-ASCII charsets, and custom model weight storage paths\u2014useful for constrained environments.","worth_installing":"Yes, if you need robust QR detection and decoding from real-world images. The library is production-stable (Development Status 5), has low install friction, carries no security vulnerabilities, and uses a permissive license. Maintenance is aging but not abandoned. Install only if you can satisfy the system-level pyzbar dependencies and accept that the last release was in February 2025."},"id":"qreader","links":{"html":"https://skillfed.io/packages/qreader","md":"https://skillfed.io/packages/qreader.md","pypi":"https://pypi.org/project/qreader/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-02-16","license_spdx":null,"license_treatment":"permissive","name":"qreader","python_support":"unspecified","summary":"Robust and Straight-Forward solution for reading difficult and tricky QR codes within images in Python. Supported by a YOLOv8 QR Segmentation model."},"popularity":{"monthly_downloads":79777,"position":14332,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"3.16"}