MengHsir commited on
upload 3RScan 数据集
Browse files- 3DSGG/3RScan/auto_download.sh +4 -0
- 3DSGG/3RScan/down.sh +13 -0
- 3DSGG/3RScan/download_3RScan.py +144 -0
- 3DSGG/3RScan/下载页面.md +5 -0
3DSGG/3RScan/auto_download.sh
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#!/bin/bash
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echo "确认下载3RScan数据集(约94GB)..."
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# 使用printf来模拟用户输入
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printf "\n" | python 3DSGG/3RScan/download_3RScan.py -o /data1/qinghao/SGG_data/3RScan_data
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3DSGG/3RScan/down.sh
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# 创建一个新的自动下载脚本
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cat > 3DSGG/3RScan/auto_download.sh << 'EOF'
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#!/bin/bash
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echo "确认下载3RScan数据集(约94GB)..."
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# 使用printf来模拟用户输入
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printf "\n" | python 3DSGG/3RScan/download_3RScan.py -o /data1/qinghao/SGG_data/3RScan_data
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EOF
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# 给脚本执行权限
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chmod +x 3DSGG/3RScan/auto_download.sh
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# 运行自动下载脚本
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./3DSGG/3RScan/auto_download.sh
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3DSGG/3RScan/download_3RScan.py
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#!/usr/bin/env python
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# Downloads 3RScan public data release
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# The data is released under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License.
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# Some useful info: Each scan is identified by a unique ID listed here:
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# http://campar.in.tum.de/public_datasets/3RScan/scans.txt or https://github.com/WaldJohannaU/3RScan/tree/master/splits
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#
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# Script usage:
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# - To download the entire 3RScan release: download.py -o [directory in which to download]
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# - To download a specific scan (e.g., 19eda6f4-55aa-29a0-8893-8eac3a4d8193): download.py -o [directory in which to download] --id 19eda6f4-55aa-29a0-8893-8eac3a4d8193
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# - To download the tfrecords: download.py -o [directory in which to download] --type=tfrecords
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# - The corresponding metadata file is here: http://campar.in.tum.de/public_datasets/3RScan/3RScan.json
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# - 3D semantic scene graphs for 3RScan are available for download on our project page https://3dssg.github.io
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import sys
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import argparse
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import os
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if sys.version_info.major >= 3 and sys.version_info.minor >= 6:
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import urllib.request as urllib
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else:
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import urllib
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import tempfile
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import re
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BASE_URL = 'http://campar.in.tum.de/public_datasets/3RScan/'
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DATA_URL = BASE_URL + 'Dataset/'
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TOS_URL = 'http://campar.in.tum.de/public_datasets/3RScan/3RScanTOU.pdf'
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TEST_FILETYPES = ['mesh.refined.v2.obj', 'mesh.refined.mtl', 'mesh.refined_0.png', 'sequence.zip']
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# We only provide semantic annotations for the train and validation scans as well as the for the
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# reference scans in the test set.
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FILETYPES = TEST_FILETYPES + ['labels.instances.annotated.v2.ply', 'mesh.refined.0.010000.segs.v2.json', 'semseg.v2.json']
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RELEASE = 'release_scans.txt'
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HIDDEN_RELEASE = 'test_rescans.txt'
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RELEASE_SIZE = '~94GB'
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id_reg = re.compile(r"[a-z0-9]{8}-[a-z0-9]{4}-[a-z0-9]{4}-[a-z0-9]{4}-[a-z0-9]{12}")
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def get_scans(scan_file):
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scan_lines = urllib.urlopen(scan_file)
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scans = []
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for scan_line in scan_lines:
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scan_line = scan_line.decode('utf8').rstrip('\n')
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match = id_reg.search(scan_line)
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if match:
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scan_id = match.group()
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scans.append(scan_id)
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return scans
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def download_release(release_scans, out_dir, file_types):
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print('Downloading 3RScan release to ' + out_dir + '...')
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for scan_id in release_scans:
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scan_out_dir = os.path.join(out_dir, scan_id)
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download_scan(scan_id, scan_out_dir, file_types)
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print('Downloaded 3RScan release.')
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def download_file(url, out_file):
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print(url)
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out_dir = os.path.dirname(out_file)
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if not os.path.isdir(out_dir):
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os.makedirs(out_dir)
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if not os.path.isfile(out_file):
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print('\t' + url + ' > ' + out_file)
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fh, out_file_tmp = tempfile.mkstemp(dir=out_dir)
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f = os.fdopen(fh, 'w')
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f.close()
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urllib.urlretrieve(url, out_file_tmp)
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os.rename(out_file_tmp, out_file)
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else:
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print('WARNING: skipping download of existing file ' + out_file)
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def download_scan(scan_id, out_dir, file_types):
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print('Downloading 3RScan scan ' + scan_id + ' ...')
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if not os.path.isdir(out_dir):
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os.makedirs(out_dir)
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for ft in file_types:
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url = DATA_URL + '/' + scan_id + '/' + ft
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out_file = out_dir + '/' + ft
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download_file(url, out_file)
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print('Downloaded scan ' + scan_id)
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def download_tfrecord(url, out_dir, file):
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if not os.path.isdir(out_dir):
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os.makedirs(out_dir)
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out_file = os.path.join(out_dir, file)
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download_file(url + '/' + file, out_file)
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def main():
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parser = argparse.ArgumentParser(description='Downloads 3RScan public data release.')
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parser.add_argument('-o', '--out_dir', required=True, help='directory in which to download')
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parser.add_argument('--id', help='specific scan id to download')
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parser.add_argument('--type', help='specific file type to download')
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args = parser.parse_args()
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print('By pressing any key to continue you confirm that you have agreed to the 3RScan terms of use as described at:')
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print(TOS_URL)
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print('***')
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print('Press any key to continue, or CTRL-C to exit.')
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release_scans = get_scans(BASE_URL + RELEASE)
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test_scans = get_scans(BASE_URL + HIDDEN_RELEASE)
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file_types = FILETYPES;
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file_types_test = TEST_FILETYPES;
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if args.type: # download file type
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file_type = args.type
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if file_type == 'tfrecords':
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download_tfrecord(BASE_URL, args.out_dir, 'val-scans.tfrecords')
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download_tfrecord(BASE_URL, args.out_dir, 'train-scans.tfrecords')
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return
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elif file_type not in FILETYPES:
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print('ERROR: Invalid file type: ' + file_type)
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return
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file_types = [file_type]
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if file_type not in TEST_FILETYPES:
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file_types_test = []
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else:
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file_types_test = [file_type]
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if args.id: # download single scan
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scan_id = args.id
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if scan_id not in release_scans and scan_id not in test_scans:
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print('ERROR: Invalid scan id: ' + scan_id)
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else:
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out_dir = os.path.join(args.out_dir, scan_id)
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if scan_id in release_scans:
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download_scan(scan_id, out_dir, file_types)
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elif scan_id in test_scans:
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download_scan(scan_id, out_dir, file_types_test)
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else: # download entire release
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if len(file_types) == len(FILETYPES):
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print('WARNING: You are downloading the entire 3RScan release which requires ' + RELEASE_SIZE + ' of space.')
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else:
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print('WARNING: You are downloading all 3RScan scans of type ' + file_types[0])
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print('Note that existing scan directories will be skipped. Delete partially downloaded directories to re-download.')
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print('***')
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print('Press any key to continue, or CTRL-C to exit.')
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key = input('')
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download_release(release_scans, args.out_dir, file_types)
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download_release(test_scans, args.out_dir, file_types_test)
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if __name__ == "__main__": main()
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3DSGG/3RScan/下载页面.md
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提交表格后跳转地址:https://gist.github.com/WaldJohannaU/55f5e35992ea91157b789b15eac4d432#file-download-3rscan-L142
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