为了实现三维重建，我们采用colmap和meshlab两个软件相结合进行操作。首先，安装colmap需使用docker容器，用户需下载镜像，并创建一个容器进行配置。接着，通过特定命令启动和进入容器，从而运行colmap。具体操作如下：执行"colmap -h" 和"colmap gui"命令，以打开colmap界面。进行三维建模时，点击file菜单，新...
安装colmap：推荐通过docker镜像方式，首先下载对应镜像，接着通过创建容器并配置host图形界面，执行启动和进入容器的命令。启动colmap可通过命令行输入colmap -h或colmap gui打开界面。meshlab的安装则直接在host上进行，启动时直接运行meshlab命令。在colmap中，进行三维建模时，从New Project开始，设置database...
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需要说明的是，colmap在特征提取完成之后还进行了几何验证，剔除误匹配点。几何验证通过估计E、H、F矩阵...
$ colmap help Usage: colmap [command] [options] Documentation: https://colmap.github.io/ Example usage: colmap help [ -h, --help ] colmap gui colmap gui -h [ --help ] colmap automatic_reconstructor -h [ --help ] colmap automatic_reconstructor --image_path IMAGES --workspace_path ...
https://github.com/colmap/colmap/blob/ff8842e7d9e985bd0dd87169f61d5aaeb309ab32/src/colmap/sensor/models.h#L197 // Simple Pinhole camera model. // f, c
VerifierWorker (src/colmap/controllers/feature_matching_utils.h) VerifierWorker的Run中读取特征点和描述子,然后计算EstimateTwoViewGeometry。 FeatureMatcherWorker (src/colmap/controllers/feature_matching_utils.h) FeatureMatcherWorker的Run中,创建CreateSiftFeatureMatcher(src/colmap/feature/sift.cc),根据参数guided...
$ sudo sh cuda_8.0.61_375.26_linux.run --override --silent --toolkit # 安装的cuda在/usr/local/cuda下⾯ # 安装cdDNN $ cd /usr/local/cuda # cuDNN放在这个⽬录下解压 $ tar -xzvf cudnn-8.0-linux-x64-v6.0.tgz $ sudo cp cuda/include/cudnn.h /usr/local/cuda/include $ ...
{ 'img_name': 'IMG_20221210_112836.jpg', 'intrinsics': array([1567.46842128, 1567.11882971, 1000., 745.5 ]), 'H': 1491, 'W': 2000, 'w2c': tensor([[-0.5214, 0.5889, -0.6175, 0.6818], [-0.7234, 0.0787, 0.6859, -3.2761], [ 0.4526, 0.8043, 0.3850...
#include<stdio.h> // Colmap函数的定义 voidcolmap(unsignedchar*data,intchannels,intsamples,intmap[][2]); intmain(){ // 假设有一个Ogg文件的数据 unsignedcharoggData[]={0x00,0x01,0x02,0x03,0x04,0x05,0x06,0x07}; intchannels=2; intsamples=4; // 假设有一个映射表 intmap[][2]={{...