iMoonLab/Hyper-YOLO
The source code of IEEE TPAMI 2025 "Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computation".
Hyper-YOLO helps you accurately identify and locate multiple objects within images or video frames. It takes in raw image or video data and outputs bounding boxes and labels for detected objects, or precise pixel-level masks for object segmentation. This is for machine learning engineers or researchers who are developing advanced computer vision applications.
217 stars. No commits in the last 6 months.
Use this if you need state-of-the-art object detection or instance segmentation with improved accuracy and efficiency for real-world computer vision tasks.
Not ideal if you are looking for a plug-and-play solution without deep technical knowledge or if your primary need is not highly precise object detection.
Stars
217
Forks
17
Language
Python
License
AGPL-3.0
Category
Last pushed
Dec 16, 2024
Commits (30d)
0
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