DataBytes-Organisation/DiscountMate_new
Jan 2026 – Jan 2026
1 Month active
Languages Used
Python
Technical Skills
OpenCVPythonYOLOdata scrapingimage processingobject detection
St3venLe
PROFILE
St3venle
Nguyen Chuong developed an automated tile product image scraping script for the DataBytes-Organisation/DiscountMate_new repository, focusing on extracting tile images from PDF catalogs. Leveraging Python, OpenCV, and YOLO, Nguyen designed an end-to-end pipeline that detects and processes product images, reducing manual collection and streamlining catalog digitization. The solution enables efficient extraction and standardization of images for downstream product listing workflows. Delivered as a single, reusable feature, the script accommodates future catalog formats and integrates object detection with image processing. Nguyen’s work demonstrates depth in applying computer vision and data scraping techniques to automate repetitive tasks and support scalable catalog management.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
70
Activity Months1
Your Network
41 people
Work History
January 2026
1 Commits • 1 Features
Jan 1, 2026In Jan 2026, delivered an automated tile product image scraping script for DataBytes-Organisation/DiscountMate_new, enabling extraction of tile images from PDF catalogs using YOLO for object detection and OpenCV for image processing. This work reduces manual image collection, accelerates catalog digitization, and enables downstream workflows for product listing and image standardization. The feature was implemented end-to-end and merged via a single commit, establishing a reusable image extraction pipeline for future catalog formats.
1 Commits • 1 Features
Jan 1, 2026In Jan 2026, delivered an automated tile product image scraping script for DataBytes-Organisation/DiscountMate_new, enabling extraction of tile images from PDF catalogs using YOLO for object detection and OpenCV for image processing. This work reduces manual image collection, accelerates catalog digitization, and enables downstream workflows for product listing and image standardization. The feature was implemented end-to-end and merged via a single commit, establishing a reusable image extraction pipeline for future catalog formats.
January 2026
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
OpenCVPythonYOLOdata scrapingimage processingobject detection
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