jeonghyo.k
3946ff6a25
- prediction/image/ FastAPI 서버 Docker 환경 구성 - Dockerfile: PyTorch 2.1 + CUDA 12.1 기반 GPU 이미지 - docker-compose.yml: GPU 할당 + 데이터 볼륨 마운트 - requirements.txt: 서버 의존성 목록 - .env.example: 환경변수 템플릿 - DOCKER_USAGE.md: 빌드/실행/API 사용법 문서 - Dockerfile에 .dockerignore 제외 폴더 mkdir -p 추가 - .gitignore: prediction/image 결과물 및 모델 가중치(.pth) 제외 추가 - dbInsert_csv.py, dbInsert_shp.py 삭제 (미사용 DB 로직) - api.py: dbInsert import 및 주석 처리된 DB 호출 코드 제거 - aerialRouter.ts: req.params 타입 오류 수정
46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import argparse
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import os
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import os.path as osp
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import oss2
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ACCESS_KEY_ID = os.getenv('OSS_ACCESS_KEY_ID', None)
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ACCESS_KEY_SECRET = os.getenv('OSS_ACCESS_KEY_SECRET', None)
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BUCKET_NAME = 'openmmlab'
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ENDPOINT = 'https://oss-accelerate.aliyuncs.com'
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def parse_args():
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parser = argparse.ArgumentParser(description='Upload models to OSS')
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parser.add_argument('model_zoo', type=str, help='model_zoo input')
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parser.add_argument(
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'--dst-folder',
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type=str,
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default='mmsegmentation/v0.5',
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help='destination folder')
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args = parser.parse_args()
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return args
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def main():
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args = parse_args()
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model_zoo = args.model_zoo
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dst_folder = args.dst_folder
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bucket = oss2.Bucket(
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oss2.Auth(ACCESS_KEY_ID, ACCESS_KEY_SECRET), ENDPOINT, BUCKET_NAME)
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for root, dirs, files in os.walk(model_zoo):
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for file in files:
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file_path = osp.relpath(osp.join(root, file), model_zoo)
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print(f'Uploading {file_path}')
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oss2.resumable_upload(bucket, osp.join(dst_folder, file_path),
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osp.join(model_zoo, file_path))
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bucket.put_object_acl(
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osp.join(dst_folder, file_path), oss2.OBJECT_ACL_PUBLIC_READ)
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if __name__ == '__main__':
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main()
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