yolo-sgf

YOLO-SGF: Lightweight network for object detection in complex infrared images based on improved YOLOv8

https://github.com/tracygc/yolo-sgf

Science Score: 49.0%

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  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
    Links to: sciencedirect.com
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (8.3%) to scientific vocabulary
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Repository

YOLO-SGF: Lightweight network for object detection in complex infrared images based on improved YOLOv8

Basic Info
  • Host: GitHub
  • Owner: Tracygc
  • License: agpl-3.0
  • Language: Python
  • Default Branch: main
  • Size: 1.25 MB
Statistics
  • Stars: 6
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing License Citation

README.md

YOLO-SGF

YOLO-SGF: Lightweight network for object detection in complex infrared images based on improved YOLOv8

PAPER: https://www.sciencedirect.com/science/article/pii/S1350449524004237

ultralytics

YOLOv8

Pip[**Python>=3.8**](https://www.python.org/)`ultralytics`[**PyTorch>=1.8**](https://pytorch.org/get-started/locally/)[](https://github.com/ultralytics/ultralytics/blob/main/pyproject.toml) [![PyPI - Version](https://img.shields.io/pypi/v/ultralytics?logo=pypi&logoColor=white)](https://pypi.org/project/ultralytics/) [![Downloads](https://static.pepy.tech/badge/ultralytics)](https://pepy.tech/project/ultralytics) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/ultralytics?logo=python&logoColor=gold)](https://pypi.org/project/ultralytics/) ```bash pip install ultralytics ``` [Conda](https://anaconda.org/conda-forge/ultralytics)[Docker](https://hub.docker.com/r/ultralytics/ultralytics)Git[](https://docs.ultralytics.com/quickstart) [![Conda Version](https://img.shields.io/conda/vn/conda-forge/ultralytics?logo=condaforge)](https://anaconda.org/conda-forge/ultralytics) [![Docker Image Version](https://img.shields.io/docker/v/ultralytics/ultralytics?sort=semver&logo=docker)](https://hub.docker.com/r/ultralytics/ultralytics)

Usage

CLI

YOLOv8 CLI yolo yolo imgsz=640 YOLOv8 CLI

Python

YOLOv8 Python CLI

YOLO-SGF--Train

YOLO-SGF train_detect.pypython

YOLO-SGFcfg/models/yoloSGF.yaml

lossutils/loss.pyBboxLoss bbox_iou

cite

@article{GUO2024105539,
title = {YOLO-SGF: Lightweight network for object detection in complex infrared images based on improved YOLOv8},
journal = {Infrared Physics & Technology},
volume = {142},
pages = {105539},
year = {2024},
issn = {1350-4495},
doi = {https://doi.org/10.1016/j.infrared.2024.105539},
author = {Cong Guo and Kan Ren and Qian Chen},
}

Owner

  • Login: Tracygc
  • Kind: user

GitHub Events

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Dependencies

examples/YOLOv8-ONNXRuntime-Rust/Cargo.toml cargo
docker/Dockerfile docker
  • pytorch/pytorch 2.3.1-cuda12.1-cudnn8-runtime build
examples/YOLOv8-Action-Recognition/requirements.txt pypi
  • transformers *
  • ultralytics *
pyproject.toml pypi
  • matplotlib >=3.3.0
  • numpy >=1.23.0,<2.0.0
  • opencv-python >=4.6.0
  • pandas >=1.1.4
  • pillow >=7.1.2
  • psutil *
  • py-cpuinfo *
  • pyyaml >=5.3.1
  • requests >=2.23.0
  • scipy >=1.4.1
  • seaborn >=0.11.0
  • torch >=1.8.0
  • torchvision >=0.9.0
  • tqdm >=4.64.0
  • ultralytics-thop >=2.0.0