| Name | sleepy-driver JSON |
| Version |
1.2.7
JSON |
| download |
| home_page | https://github.com/kimhotac/sleepy-driver-detector |
| Summary | 운전자 피로도 분석 시스템 - 영상 기반 눈 감김 분석을 통한 실시간 피로도 판단 라이브러리 |
| upload_time | 2025-07-18 04:54:47 |
| maintainer | None |
| docs_url | None |
| author | SleepyDriver Team |
| requires_python | >=3.8 |
| license | MIT License
Copyright (c) 2025 SleepyDriver Team
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
|
| keywords |
drowsiness
fatigue
driver
safety
computer-vision
ai
real-time
monitoring
adas
autonomous-driving
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# 🚗 SleepyDriver - AI 기반 졸음 감지 라이브러리
[](https://badge.fury.io/py/sleepy-driver)
[](https://pypi.org/project/sleepy-driver/)
[](https://opensource.org/licenses/MIT)
**SleepyDriver**는 실시간 비디오에서 운전자의 졸음 상태를 AI로 감지하는 파이썬 라이브러리입니다. 5가지 다양한 감지 모델을 지원하며, 간단한 API로 사용하기 간편합니다.
## ✨ 주요 기능
- 🎯 **5가지 감지 모델**: OpenCV, 머신러닝(RF), 딥러닝(CNN), MediaPipe, 적외선 기반
- ⚡ **실시간 처리**: 웹캠에서 실시간 졸음 감지 (~30 FPS)
- 🔧 **간단한 API**: 3줄의 코드로 졸음 감지 시스템 구축
- 🛡️ **안정성**: 강력한 에러 처리와 의존성 관리
- 🖥️ **CLI 지원**: 설치 후 바로 사용 가능한 명령행 도구
## 🚀 빠른 시작
### 설치
```bash
pip install sleepy-driver
```
### 사용법
```python
from sleepy_driver import start_detection
start_detection('mlp') # MLP 모델
start_detection('ml', threshold_ms=2000) # ML 모델, 2초 임계값
start_detection('opencv') # OpenCV 모델
start_detection('point') # MediaPipe 모델
start_detection('infrared') # 적외선 모델
```
## 📋 지원 모델
| 모델 | 설명 | 장점 | 의존성 |
| ------------ | ------------------------------ | ----------------- | ------------ |
| **opencv** | OpenCV 기반 전통적 컴퓨터 비전 | 빠름, 의존성 적음 | 없음 |
| **ml** | RandomForest 머신러닝 | 균형잡힌 성능 | scikit-learn |
| **mlp** | CNN 딥러닝 | 높은 정확도 | PyTorch |
| **point** | MediaPipe 랜드마크 | 실시간성 우수 | 없음 |
| **infrared** | 적외선 CNN 딥러닝 | 야간 감지 우수 | PyTorch |
## 📊 성능 벤치마크
| 모델 | 평균 FPS | 정확도 | 메모리 사용량 |
| --------- | -------- | ------ | ------------- |
| OpenCV | ~35 FPS | 85% | ~50MB |
| ML (RF) | ~30 FPS | 90% | ~100MB |
| MLP (CNN) | ~28 FPS | 95% | ~200MB |
| Point | ~40 FPS | 80% | ~30MB |
| Infrared | ~25 FPS | 92% | ~250MB |
_테스트 환경: MacBook Pro M1, 720p 웹캠_
## 👥 라이브러리 소개
**운전자 피로도 분석 시스템** - 영상 기반 눈 감김 분석을 통한 실시간 졸음 판단 라이브러리
### 🎯 라이브러리 목적
- **운전자의 눈이 감겼는가를 이진 분류**
- **눈을 감은 시간이 몇 초인지 정량 분석**
- **사회적 효과**: 사고 예방 AI 구현 가능
- **기술 학습 효과**: 실시간 영상 처리, 시계열 데이터 분석, Vision 기반 분류 등 산업 적용력 높은 실전형 경험
### 👨💻 개발 팀
| 이름 | 역할 | GitHub |
| ---------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------ |
| **김진현** | AIHub 기반 딥러닝 모델 설계 및 적외선 딥러닝 라벨 정리, PyTorch GPU 리서치, 적외선 모델 구현 및 학습, 오류 디버깅 지원 | [@JinhyeonK](https://github.com/JinhyeonK) |
| **김호탁** | 전처리 모듈 구축 및 구조 기획, 좌표 기반 눈 감김 판별 알고리즘 구현, 딥러닝 모델 학습 및 통합, 상속 구조 정리 및 패키지화 주도 | [@kimhotac](https://github.com/kimhotac) |
| **박준규** | OpenCV 기반 접근법 개발, 디렉토리 정리 및 구조 패키지화, 졸음 검출 모듈 구현, PyPI 라이브러리 배포 주도 | [@ParkJunGyu26](https://github.com/ParkJunGyu26) |
| **안승현** | Mediapipe 기반 좌표 추출 및 눈 감김 판별 알고리즘 구현, Kaggle 데이터 기반 딥러닝 모델 개발 및 최적화, PyTorch GPU 환경 세팅 및 적외선 모델 학습 참여 | [@asho227](https://github.com/asho227) |
| **윤선아** | 데이터 수집 및 머신러닝 모델 (SVM, XGBoost, RandomForest) 개발 전반 수행, 모델 최적화 및 적용 | [@dotoriysa](https://github.com/dotoriysa) |
## 🛠️ 개발자 가이드
### 로컬 개발 설정
```bash
# 저장소 클론
git clone https://github.com/kimhotac/sleepy-driver-detector.git
cd sleepy-driver-detector
# 개발 의존성 설치
pip install -e .[dev]
# 테스트 실행
pytest tests/
# 코드 포맷팅
black sleepy_driver/
flake8 sleepy_driver/
```
### 패키지 빌드
```bash
# 빌드 도구 설치
pip install build twine
# 패키지 빌드
python -m build
# PyPI 업로드 (관리자만)
twine upload dist/*
```
## 🤝 기여하기
1. [Fork 저장소](https://github.com/kimhotac/sleepy-driver-detector/fork)
2. 기능 브랜치 생성 (`git checkout -b feature/amazing-feature`)
3. 변경사항 커밋 (`git commit -m 'Add amazing feature'`)
4. 브랜치 푸시 (`git push origin feature/amazing-feature`)
5. Pull Request 생성
## 📄 라이선스
이 프로젝트는 MIT 라이선스 하에 배포됩니다. 자세한 내용은 [LICENSE](LICENSE) 파일을 참조하세요.
## 🙏 감사의 말
- [MediaPipe](https://mediapipe.dev/) - 얼굴 랜드마크 감지
- [OpenCV](https://opencv.org/) - 컴퓨터 비전 라이브러리
- [PyTorch](https://pytorch.org/) - 딥러닝 프레임워크
- [scikit-learn](https://scikit-learn.org/) - 머신러닝 라이브러리
## 🆘 지원 및 문의
- 📖 **문서**: [GitHub README](https://github.com/kimhotac/sleepy-driver-detector#readme)
- 🐛 **버그 리포트**: [GitHub Issues](https://github.com/kimhotac/sleepy-driver-detector/issues)
- 💬 **디스커션**: [GitHub Discussions](https://github.com/kimhotac/sleepy-driver-detector/discussions)
- 📧 **이메일**: junju404@naver.com (박준규)
---
**⚠️ 주의사항**: 이 라이브러리는 보조 도구로만 사용하세요. 실제 운전 시에는 항상 안전을 최우선으로 하고, 졸음을 느끼면 즉시 안전한 곳에 정차하여 휴식을 취하세요.
Raw data
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"keywords": "drowsiness, fatigue, driver, safety, computer-vision, ai, real-time, monitoring, adas, autonomous-driving",
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"description": "# \ud83d\ude97 SleepyDriver - AI \uae30\ubc18 \uc878\uc74c \uac10\uc9c0 \ub77c\uc774\ube0c\ub7ec\ub9ac\n\n[](https://badge.fury.io/py/sleepy-driver)\n[](https://pypi.org/project/sleepy-driver/)\n[](https://opensource.org/licenses/MIT)\n\n**SleepyDriver**\ub294 \uc2e4\uc2dc\uac04 \ube44\ub514\uc624\uc5d0\uc11c \uc6b4\uc804\uc790\uc758 \uc878\uc74c \uc0c1\ud0dc\ub97c AI\ub85c \uac10\uc9c0\ud558\ub294 \ud30c\uc774\uc36c \ub77c\uc774\ube0c\ub7ec\ub9ac\uc785\ub2c8\ub2e4. 5\uac00\uc9c0 \ub2e4\uc591\ud55c \uac10\uc9c0 \ubaa8\ub378\uc744 \uc9c0\uc6d0\ud558\uba70, \uac04\ub2e8\ud55c API\ub85c \uc0ac\uc6a9\ud558\uae30 \uac04\ud3b8\ud569\ub2c8\ub2e4.\n\n## \u2728 \uc8fc\uc694 \uae30\ub2a5\n\n- \ud83c\udfaf **5\uac00\uc9c0 \uac10\uc9c0 \ubaa8\ub378**: OpenCV, \uba38\uc2e0\ub7ec\ub2dd(RF), \ub525\ub7ec\ub2dd(CNN), MediaPipe, \uc801\uc678\uc120 \uae30\ubc18\n- \u26a1 **\uc2e4\uc2dc\uac04 \ucc98\ub9ac**: \uc6f9\ucea0\uc5d0\uc11c \uc2e4\uc2dc\uac04 \uc878\uc74c \uac10\uc9c0 (~30 FPS)\n- \ud83d\udd27 **\uac04\ub2e8\ud55c API**: 3\uc904\uc758 \ucf54\ub4dc\ub85c \uc878\uc74c \uac10\uc9c0 \uc2dc\uc2a4\ud15c \uad6c\ucd95\n- \ud83d\udee1\ufe0f **\uc548\uc815\uc131**: \uac15\ub825\ud55c \uc5d0\ub7ec \ucc98\ub9ac\uc640 \uc758\uc874\uc131 \uad00\ub9ac\n- \ud83d\udda5\ufe0f **CLI \uc9c0\uc6d0**: \uc124\uce58 \ud6c4 \ubc14\ub85c \uc0ac\uc6a9 \uac00\ub2a5\ud55c \uba85\ub839\ud589 \ub3c4\uad6c\n\n## \ud83d\ude80 \ube60\ub978 \uc2dc\uc791\n\n### \uc124\uce58\n\n```bash\npip install sleepy-driver\n```\n\n### \uc0ac\uc6a9\ubc95\n\n```python\nfrom sleepy_driver import start_detection\nstart_detection('mlp') # MLP \ubaa8\ub378\nstart_detection('ml', threshold_ms=2000) # ML \ubaa8\ub378, 2\ucd08 \uc784\uacc4\uac12\nstart_detection('opencv') # OpenCV \ubaa8\ub378\nstart_detection('point') # MediaPipe \ubaa8\ub378\nstart_detection('infrared') # \uc801\uc678\uc120 \ubaa8\ub378\n```\n\n## \ud83d\udccb \uc9c0\uc6d0 \ubaa8\ub378\n\n| \ubaa8\ub378 | \uc124\uba85 | \uc7a5\uc810 | \uc758\uc874\uc131 |\n| ------------ | ------------------------------ | ----------------- | ------------ |\n| **opencv** | OpenCV \uae30\ubc18 \uc804\ud1b5\uc801 \ucef4\ud4e8\ud130 \ube44\uc804 | \ube60\ub984, \uc758\uc874\uc131 \uc801\uc74c | \uc5c6\uc74c |\n| **ml** | RandomForest \uba38\uc2e0\ub7ec\ub2dd | \uade0\ud615\uc7a1\ud78c \uc131\ub2a5 | scikit-learn |\n| **mlp** | CNN \ub525\ub7ec\ub2dd | \ub192\uc740 \uc815\ud655\ub3c4 | PyTorch |\n| **point** | MediaPipe \ub79c\ub4dc\ub9c8\ud06c | \uc2e4\uc2dc\uac04\uc131 \uc6b0\uc218 | \uc5c6\uc74c |\n| **infrared** | \uc801\uc678\uc120 CNN \ub525\ub7ec\ub2dd | \uc57c\uac04 \uac10\uc9c0 \uc6b0\uc218 | PyTorch |\n\n## \ud83d\udcca \uc131\ub2a5 \ubca4\uce58\ub9c8\ud06c\n\n| \ubaa8\ub378 | \ud3c9\uade0 FPS | \uc815\ud655\ub3c4 | \uba54\ubaa8\ub9ac \uc0ac\uc6a9\ub7c9 |\n| --------- | -------- | ------ | ------------- |\n| OpenCV | ~35 FPS | 85% | ~50MB |\n| ML (RF) | ~30 FPS | 90% | ~100MB |\n| MLP (CNN) | ~28 FPS | 95% | ~200MB |\n| Point | ~40 FPS | 80% | ~30MB |\n| Infrared | ~25 FPS | 92% | ~250MB |\n\n_\ud14c\uc2a4\ud2b8 \ud658\uacbd: MacBook Pro M1, 720p \uc6f9\ucea0_\n\n## \ud83d\udc65 \ub77c\uc774\ube0c\ub7ec\ub9ac \uc18c\uac1c\n\n**\uc6b4\uc804\uc790 \ud53c\ub85c\ub3c4 \ubd84\uc11d \uc2dc\uc2a4\ud15c** - \uc601\uc0c1 \uae30\ubc18 \ub208 \uac10\uae40 \ubd84\uc11d\uc744 \ud1b5\ud55c \uc2e4\uc2dc\uac04 \uc878\uc74c \ud310\ub2e8 \ub77c\uc774\ube0c\ub7ec\ub9ac\n\n### \ud83c\udfaf \ub77c\uc774\ube0c\ub7ec\ub9ac \ubaa9\uc801\n\n- **\uc6b4\uc804\uc790\uc758 \ub208\uc774 \uac10\uacbc\ub294\uac00\ub97c \uc774\uc9c4 \ubd84\ub958**\n- **\ub208\uc744 \uac10\uc740 \uc2dc\uac04\uc774 \uba87 \ucd08\uc778\uc9c0 \uc815\ub7c9 \ubd84\uc11d**\n- **\uc0ac\ud68c\uc801 \ud6a8\uacfc**: \uc0ac\uace0 \uc608\ubc29 AI \uad6c\ud604 \uac00\ub2a5\n- **\uae30\uc220 \ud559\uc2b5 \ud6a8\uacfc**: \uc2e4\uc2dc\uac04 \uc601\uc0c1 \ucc98\ub9ac, \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130 \ubd84\uc11d, Vision \uae30\ubc18 \ubd84\ub958 \ub4f1 \uc0b0\uc5c5 \uc801\uc6a9\ub825 \ub192\uc740 \uc2e4\uc804\ud615 \uacbd\ud5d8\n\n### \ud83d\udc68\u200d\ud83d\udcbb \uac1c\ubc1c \ud300\n\n| \uc774\ub984 | \uc5ed\ud560 | GitHub |\n| ---------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------ |\n| **\uae40\uc9c4\ud604** | AIHub \uae30\ubc18 \ub525\ub7ec\ub2dd \ubaa8\ub378 \uc124\uacc4 \ubc0f \uc801\uc678\uc120 \ub525\ub7ec\ub2dd \ub77c\ubca8 \uc815\ub9ac, PyTorch GPU \ub9ac\uc11c\uce58, \uc801\uc678\uc120 \ubaa8\ub378 \uad6c\ud604 \ubc0f \ud559\uc2b5, \uc624\ub958 \ub514\ubc84\uae45 \uc9c0\uc6d0 | [@JinhyeonK](https://github.com/JinhyeonK) |\n| **\uae40\ud638\ud0c1** | \uc804\ucc98\ub9ac \ubaa8\ub4c8 \uad6c\ucd95 \ubc0f \uad6c\uc870 \uae30\ud68d, \uc88c\ud45c \uae30\ubc18 \ub208 \uac10\uae40 \ud310\ubcc4 \uc54c\uace0\ub9ac\uc998 \uad6c\ud604, \ub525\ub7ec\ub2dd \ubaa8\ub378 \ud559\uc2b5 \ubc0f \ud1b5\ud569, \uc0c1\uc18d \uad6c\uc870 \uc815\ub9ac \ubc0f \ud328\ud0a4\uc9c0\ud654 \uc8fc\ub3c4 | [@kimhotac](https://github.com/kimhotac) |\n| **\ubc15\uc900\uaddc** | OpenCV \uae30\ubc18 \uc811\uadfc\ubc95 \uac1c\ubc1c, \ub514\ub809\ud1a0\ub9ac \uc815\ub9ac \ubc0f \uad6c\uc870 \ud328\ud0a4\uc9c0\ud654, \uc878\uc74c \uac80\ucd9c \ubaa8\ub4c8 \uad6c\ud604, PyPI \ub77c\uc774\ube0c\ub7ec\ub9ac \ubc30\ud3ec \uc8fc\ub3c4 | [@ParkJunGyu26](https://github.com/ParkJunGyu26) |\n| **\uc548\uc2b9\ud604** | Mediapipe \uae30\ubc18 \uc88c\ud45c \ucd94\ucd9c \ubc0f \ub208 \uac10\uae40 \ud310\ubcc4 \uc54c\uace0\ub9ac\uc998 \uad6c\ud604, Kaggle \ub370\uc774\ud130 \uae30\ubc18 \ub525\ub7ec\ub2dd \ubaa8\ub378 \uac1c\ubc1c \ubc0f \ucd5c\uc801\ud654, PyTorch GPU \ud658\uacbd \uc138\ud305 \ubc0f \uc801\uc678\uc120 \ubaa8\ub378 \ud559\uc2b5 \ucc38\uc5ec | [@asho227](https://github.com/asho227) |\n| **\uc724\uc120\uc544** | \ub370\uc774\ud130 \uc218\uc9d1 \ubc0f \uba38\uc2e0\ub7ec\ub2dd \ubaa8\ub378 (SVM, XGBoost, RandomForest) \uac1c\ubc1c \uc804\ubc18 \uc218\ud589, \ubaa8\ub378 \ucd5c\uc801\ud654 \ubc0f \uc801\uc6a9 | [@dotoriysa](https://github.com/dotoriysa) |\n\n## \ud83d\udee0\ufe0f \uac1c\ubc1c\uc790 \uac00\uc774\ub4dc\n\n### \ub85c\uceec \uac1c\ubc1c \uc124\uc815\n\n```bash\n# \uc800\uc7a5\uc18c \ud074\ub860\ngit clone https://github.com/kimhotac/sleepy-driver-detector.git\ncd sleepy-driver-detector\n\n# \uac1c\ubc1c \uc758\uc874\uc131 \uc124\uce58\npip install -e .[dev]\n\n# \ud14c\uc2a4\ud2b8 \uc2e4\ud589\npytest tests/\n\n# \ucf54\ub4dc \ud3ec\ub9f7\ud305\nblack sleepy_driver/\nflake8 sleepy_driver/\n```\n\n### \ud328\ud0a4\uc9c0 \ube4c\ub4dc\n\n```bash\n# \ube4c\ub4dc \ub3c4\uad6c \uc124\uce58\npip install build twine\n\n# \ud328\ud0a4\uc9c0 \ube4c\ub4dc\npython -m build\n\n# PyPI \uc5c5\ub85c\ub4dc (\uad00\ub9ac\uc790\ub9cc)\ntwine upload dist/*\n```\n\n## \ud83e\udd1d \uae30\uc5ec\ud558\uae30\n\n1. [Fork \uc800\uc7a5\uc18c](https://github.com/kimhotac/sleepy-driver-detector/fork)\n2. \uae30\ub2a5 \ube0c\ub79c\uce58 \uc0dd\uc131 (`git checkout -b feature/amazing-feature`)\n3. \ubcc0\uacbd\uc0ac\ud56d \ucee4\ubc0b (`git commit -m 'Add amazing feature'`)\n4. \ube0c\ub79c\uce58 \ud478\uc2dc (`git push origin feature/amazing-feature`)\n5. Pull Request \uc0dd\uc131\n\n## \ud83d\udcc4 \ub77c\uc774\uc120\uc2a4\n\n\uc774 \ud504\ub85c\uc81d\ud2b8\ub294 MIT \ub77c\uc774\uc120\uc2a4 \ud558\uc5d0 \ubc30\ud3ec\ub429\ub2c8\ub2e4. \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 [LICENSE](LICENSE) \ud30c\uc77c\uc744 \ucc38\uc870\ud558\uc138\uc694.\n\n## \ud83d\ude4f \uac10\uc0ac\uc758 \ub9d0\n\n- [MediaPipe](https://mediapipe.dev/) - \uc5bc\uad74 \ub79c\ub4dc\ub9c8\ud06c \uac10\uc9c0\n- [OpenCV](https://opencv.org/) - \ucef4\ud4e8\ud130 \ube44\uc804 \ub77c\uc774\ube0c\ub7ec\ub9ac\n- [PyTorch](https://pytorch.org/) - \ub525\ub7ec\ub2dd \ud504\ub808\uc784\uc6cc\ud06c\n- [scikit-learn](https://scikit-learn.org/) - \uba38\uc2e0\ub7ec\ub2dd \ub77c\uc774\ube0c\ub7ec\ub9ac\n\n## \ud83c\udd98 \uc9c0\uc6d0 \ubc0f \ubb38\uc758\n\n- \ud83d\udcd6 **\ubb38\uc11c**: [GitHub README](https://github.com/kimhotac/sleepy-driver-detector#readme)\n- \ud83d\udc1b **\ubc84\uadf8 \ub9ac\ud3ec\ud2b8**: [GitHub Issues](https://github.com/kimhotac/sleepy-driver-detector/issues)\n- \ud83d\udcac **\ub514\uc2a4\ucee4\uc158**: [GitHub Discussions](https://github.com/kimhotac/sleepy-driver-detector/discussions)\n- \ud83d\udce7 **\uc774\uba54\uc77c**: junju404@naver.com (\ubc15\uc900\uaddc)\n\n---\n\n**\u26a0\ufe0f \uc8fc\uc758\uc0ac\ud56d**: \uc774 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub294 \ubcf4\uc870 \ub3c4\uad6c\ub85c\ub9cc \uc0ac\uc6a9\ud558\uc138\uc694. \uc2e4\uc81c \uc6b4\uc804 \uc2dc\uc5d0\ub294 \ud56d\uc0c1 \uc548\uc804\uc744 \ucd5c\uc6b0\uc120\uc73c\ub85c \ud558\uace0, \uc878\uc74c\uc744 \ub290\ub07c\uba74 \uc989\uc2dc \uc548\uc804\ud55c \uacf3\uc5d0 \uc815\ucc28\ud558\uc5ec \ud734\uc2dd\uc744 \ucde8\ud558\uc138\uc694.\n",
"bugtrack_url": null,
"license": "MIT License\n \n Copyright (c) 2025 SleepyDriver Team\n \n Permission is hereby granted, free of charge, to any person obtaining a copy\n of this software and associated documentation files (the \"Software\"), to deal\n in the Software without restriction, including without limitation the rights\n to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n copies of the Software, and to permit persons to whom the Software is\n furnished to do so, subject to the following conditions:\n \n The above copyright notice and this permission notice shall be included in all\n copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n SOFTWARE.\n ",
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"split_keywords": [
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