iMoonLab/Hyper-YOLOv1.1
The source code of IEEE TPAMI 2025 "Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computation".
This project offers an advanced object detection system that helps computer vision engineers more accurately identify and locate multiple objects within images. It takes raw image datasets and outputs bounding boxes and labels for detected objects, improving upon existing YOLO models. This is ideal for machine learning engineers, computer vision researchers, and AI developers working on visual recognition tasks.
119 stars. No commits in the last 6 months.
Use this if you need to perform state-of-the-art object detection and want to leverage recent advancements in hypergraph computation for improved accuracy in your visual AI applications.
Not ideal if you are looking for a simple, off-the-shelf object detection tool without the need for model training or if you lack experience with deep learning frameworks and data preparation for computer vision.
Stars
119
Forks
17
Language
Python
License
GPL-3.0
Category
Last pushed
Dec 16, 2024
Commits (30d)
0
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