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
104 lines
5.1 KiB
Python
104 lines
5.1 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from .builder import DATASETS
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from .custom import CustomDataset
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@DATASETS.register_module()
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class PascalContextDataset(CustomDataset):
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"""PascalContext dataset.
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In segmentation map annotation for PascalContext, 0 stands for background,
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which is included in 60 categories. ``reduce_zero_label`` is fixed to
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False. The ``img_suffix`` is fixed to '.jpg' and ``seg_map_suffix`` is
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fixed to '.png'.
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Args:
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split (str): Split txt file for PascalContext.
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"""
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CLASSES = ('background', 'aeroplane', 'bag', 'bed', 'bedclothes', 'bench',
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'bicycle', 'bird', 'boat', 'book', 'bottle', 'building', 'bus',
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'cabinet', 'car', 'cat', 'ceiling', 'chair', 'cloth',
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'computer', 'cow', 'cup', 'curtain', 'dog', 'door', 'fence',
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'floor', 'flower', 'food', 'grass', 'ground', 'horse',
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'keyboard', 'light', 'motorbike', 'mountain', 'mouse', 'person',
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'plate', 'platform', 'pottedplant', 'road', 'rock', 'sheep',
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'shelves', 'sidewalk', 'sign', 'sky', 'snow', 'sofa', 'table',
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'track', 'train', 'tree', 'truck', 'tvmonitor', 'wall', 'water',
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'window', 'wood')
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PALETTE = [[120, 120, 120], [180, 120, 120], [6, 230, 230], [80, 50, 50],
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[4, 200, 3], [120, 120, 80], [140, 140, 140], [204, 5, 255],
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[230, 230, 230], [4, 250, 7], [224, 5, 255], [235, 255, 7],
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[150, 5, 61], [120, 120, 70], [8, 255, 51], [255, 6, 82],
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[143, 255, 140], [204, 255, 4], [255, 51, 7], [204, 70, 3],
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[0, 102, 200], [61, 230, 250], [255, 6, 51], [11, 102, 255],
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[255, 7, 71], [255, 9, 224], [9, 7, 230], [220, 220, 220],
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[255, 9, 92], [112, 9, 255], [8, 255, 214], [7, 255, 224],
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[255, 184, 6], [10, 255, 71], [255, 41, 10], [7, 255, 255],
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[224, 255, 8], [102, 8, 255], [255, 61, 6], [255, 194, 7],
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[255, 122, 8], [0, 255, 20], [255, 8, 41], [255, 5, 153],
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[6, 51, 255], [235, 12, 255], [160, 150, 20], [0, 163, 255],
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[140, 140, 140], [250, 10, 15], [20, 255, 0], [31, 255, 0],
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[255, 31, 0], [255, 224, 0], [153, 255, 0], [0, 0, 255],
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[255, 71, 0], [0, 235, 255], [0, 173, 255], [31, 0, 255]]
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def __init__(self, split, **kwargs):
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super(PascalContextDataset, self).__init__(
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img_suffix='.jpg',
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seg_map_suffix='.png',
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split=split,
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reduce_zero_label=False,
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**kwargs)
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assert self.file_client.exists(self.img_dir) and self.split is not None
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@DATASETS.register_module()
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class PascalContextDataset59(CustomDataset):
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"""PascalContext dataset.
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In segmentation map annotation for PascalContext, 0 stands for background,
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which is included in 60 categories. ``reduce_zero_label`` is fixed to
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False. The ``img_suffix`` is fixed to '.jpg' and ``seg_map_suffix`` is
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fixed to '.png'.
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Args:
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split (str): Split txt file for PascalContext.
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"""
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CLASSES = ('aeroplane', 'bag', 'bed', 'bedclothes', 'bench', 'bicycle',
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'bird', 'boat', 'book', 'bottle', 'building', 'bus', 'cabinet',
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'car', 'cat', 'ceiling', 'chair', 'cloth', 'computer', 'cow',
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'cup', 'curtain', 'dog', 'door', 'fence', 'floor', 'flower',
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'food', 'grass', 'ground', 'horse', 'keyboard', 'light',
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'motorbike', 'mountain', 'mouse', 'person', 'plate', 'platform',
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'pottedplant', 'road', 'rock', 'sheep', 'shelves', 'sidewalk',
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'sign', 'sky', 'snow', 'sofa', 'table', 'track', 'train',
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'tree', 'truck', 'tvmonitor', 'wall', 'water', 'window', 'wood')
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PALETTE = [[180, 120, 120], [6, 230, 230], [80, 50, 50], [4, 200, 3],
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[120, 120, 80], [140, 140, 140], [204, 5, 255], [230, 230, 230],
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[4, 250, 7], [224, 5, 255], [235, 255, 7], [150, 5, 61],
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[120, 120, 70], [8, 255, 51], [255, 6, 82], [143, 255, 140],
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[204, 255, 4], [255, 51, 7], [204, 70, 3], [0, 102, 200],
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[61, 230, 250], [255, 6, 51], [11, 102, 255], [255, 7, 71],
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[255, 9, 224], [9, 7, 230], [220, 220, 220], [255, 9, 92],
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[112, 9, 255], [8, 255, 214], [7, 255, 224], [255, 184, 6],
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[10, 255, 71], [255, 41, 10], [7, 255, 255], [224, 255, 8],
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[102, 8, 255], [255, 61, 6], [255, 194, 7], [255, 122, 8],
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[0, 255, 20], [255, 8, 41], [255, 5, 153], [6, 51, 255],
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[235, 12, 255], [160, 150, 20], [0, 163, 255], [140, 140, 140],
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[250, 10, 15], [20, 255, 0], [31, 255, 0], [255, 31, 0],
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[255, 224, 0], [153, 255, 0], [0, 0, 255], [255, 71, 0],
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[0, 235, 255], [0, 173, 255], [31, 0, 255]]
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def __init__(self, split, **kwargs):
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super(PascalContextDataset59, self).__init__(
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img_suffix='.jpg',
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seg_map_suffix='.png',
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split=split,
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reduce_zero_label=True,
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**kwargs)
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assert self.file_client.exists(self.img_dir) and self.split is not None
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