Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.6%) to scientific vocabulary
Last synced: 7 months ago
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JSON representation
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Repository
Basic Info
- Host: GitHub
- Owner: devrnrwls
- License: agpl-3.0
- Language: Python
- Default Branch: main
- Size: 698 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
- Releases: 0
Created over 2 years ago
· Last pushed over 2 years ago
Metadata Files
Readme
Contributing
License
Citation
Security
README.md
Documentation
See below for a quickstart installation and usage example, and see the YOLOv8 Docs for full documentation on training, validation, prediction and deployment.
Install
Pip install the ultralytics package including all [requirements](https://github.com/ultralytics/ultralytics/blob/main/requirements.txt) in a [**Python>=3.8**](https://www.python.org/) environment with [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [Pytorch version Site] https://pytorch.org/get-started/previous-versions/ ```bash pip install -r requirements.txt #CUDA 11.6 pip install torch==1.13.0+cu116 torchvision==0.14.0+cu116 --extra-index-url https://download.pytorch.org/whl/cu116 pip install ultralytics ``` For alternative installation methods including [Conda](https://anaconda.org/conda-forge/ultralytics), [Docker](https://hub.docker.com/r/ultralytics/ultralytics), and Git, please refer to the [Quickstart Guide](https://docs.ultralytics.com/quickstart).Usage
#### CustomDataset 학습 전 셋팅이 필요한 yaml 파일들 ```bash (training hyperparameter) ./ultralytics/cfg/default.yaml (dataset path) ./ultralytics/cfg/default.yaml 안에 data에서 customDataset.yaml 위치 지정 (참고로 data root path는 해당 위치에 지정되어 있음) ~/.config/Ultralytics/settings.yaml (참고로 dataset 기본 양식 위치) ./ultralytics/models/yolo/detect/customDataset.yaml ``` #### Train File ```bash ./ultralytics/models/yolo/detect/train.py (폴더 최상단으로 이동) ``` #### predict setup ```bash (training hyperparameter) ./ultralytics/cfg/default.yaml (학습에 사용한 모델 settings 예시) model: ./runs/detect/train19/weights/last.pt (Prediction settings 에서 예측할 폴더 설정 예시 ) source: './predict_dataset3' ``` #### Predict File ```bash ./ultralytics/models/yolo/detect/predict.py (폴더 최상단으로 이동) ``` [Models](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/cfg/models) download automatically from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases). See YOLOv8 [Python Docs](https://docs.ultralytics.com/usage/python) for more examples.Owner
- Name: devson
- Login: devrnrwls
- Kind: user
- Repositories: 1
- Profile: https://github.com/devrnrwls
Citation (CITATION.cff)
cff-version: 1.2.0
preferred-citation:
type: software
message: If you use this software, please cite it as below.
authors:
- family-names: Jocher
given-names: Glenn
orcid: "https://orcid.org/0000-0001-5950-6979"
- family-names: Chaurasia
given-names: Ayush
orcid: "https://orcid.org/0000-0002-7603-6750"
- family-names: Qiu
given-names: Jing
orcid: "https://orcid.org/0000-0003-3783-7069"
title: "YOLO by Ultralytics"
version: 8.0.0
# doi: 10.5281/zenodo.3908559 # TODO
date-released: 2023-1-10
license: AGPL-3.0
url: "https://github.com/ultralytics/ultralytics"