Scannet v2 数据集介绍以及子集下载展示

Scannet v2 数据集介绍以及子集下载展示

参考

scannet数据集简介和下载-优快云博客

scannet v2 数据集下载_scannetv2数据集_蓝羽飞鸟的博客-优快云博客

ScanNet数据集下载与导出颜色图、深度图、内参、位姿数据-优快云博客
simplerecon/data_scripts/scannet_wrangling_scripts at main · nianticlabs/simplerecon (github.com)

数据集简介

数据集Github地址 ScanNet/ScanNet (github.com)

ScanNet 是一个 RGB-D 视频数据集，包含 1500 多次扫描中的 250 万个视图，并使用 3D 相机姿势、表面重建和实例级语义分割进行注释 。 ScanNet V2数据集一共1.2T 。（但其实不用全下载，按照对应的任务有选择的下载）

RGB-D 传感器是一种特定类型的深度感应设备，与RGB（红色、绿色和蓝色）传感器相机配合使用。 它通过在每个像素的基础上使用深度信息（与传感器的距离相关）来增强传统图像，即RGBD = RGB + Depth Map。

子集

由于整份数据较大，有1.2T，作者提供了下载较小子集的选项scannet_frames_25k（约25,000帧，从完整数据集中大约每100帧进行二次采样）通过ScanNet数据下载，有5.6G，还有基准评估scannet_frames_test。

• scannet_frames_25k.zip ~5.6G，1513 份 scans（即 RGB-D 序列，这里简单当成 videos），包含训练集和测试集，训练集1201，验证集312
• scannet_frames_test.zip ~618mb ,100份，用作测试集

#下载scannet_frames_25k
python download_scannetv2.py -o data --preprocessed_frames 

#下载scannet_frames_test
python download_scannetv2.py -o data --test_frames_2d

scannet_frames_25k

scannet_frames_test

下载脚本 download_scannetv2.py

#coding:utf-8
#!/usr/bin/env python
# Downloads ScanNet public data release
# Run with ./download-scannet.py (or python download-scannet.py on Windows)
# -*- coding: utf-8 -*-
import argparse
import os
import urllib.request      #(for python3)
# import urllib
import tempfile

BASE_URL = 'http://kaldir.vc.in.tum.de/scannet/'
TOS_URL = BASE_URL + 'ScanNet_TOS.pdf'
FILETYPES = ['.sens', '.txt',
             '_vh_clean.ply', '_vh_clean_2.ply',
             '_vh_clean.segs.json', '_vh_clean_2.0.010000.segs.json',
             '.aggregation.json', '_vh_clean.aggregation.json',
             '_vh_clean_2.labels.ply',
             '_2d-instance.zip', '_2d-instance-filt.zip',
             '_2d-label.zip', '_2d-label-filt.zip']
FILETYPES_TEST = ['.sens', '.txt', '_vh_clean.ply', '_vh_clean_2.ply']
PREPROCESSED_FRAMES_FILE = ['scannet_frames_25k.zip', '5.6GB']
TEST_FRAMES_FILE = ['scannet_frames_test.zip', '610MB']
LABEL_MAP_FILES = ['scannetv2-labels.combined.tsv', 'scannet-labels.combined.tsv']
RELEASES = ['v2/scans', 'v1/scans']
RELEASES_TASKS = ['v2/tasks', 'v1/tasks']
RELEASES_NAMES = ['v2', 'v1']
RELEASE = RELEASES[0]
RELEASE_TASKS = RELEASES_TASKS[0]
RELEASE_NAME = RELEASES_NAMES[0]
LABEL_MAP_FILE = LABEL_MAP_FILES[0]
RELEASE_SIZE = '1.2TB'
V1_IDX = 1


def get_release_scans(release_file):
    scan_lines = urllib.request.urlopen(release_file)
    # scan_lines = urllib.urlopen(release_file)
    scans = []
    for scan_line in scan_lines:
        scan_id = scan_line.decode('utf8').rstrip('\n')
        scans.append(scan_id)
    return scans


def download_release(release_scans, out_dir, file_types, use_v1_sens):
    if len(release_scans) == 0