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PointCloud using Potree

About LAS Files

LAS (LASer) is a file format designed for the interchange of 3-dimensional point cloud data, primarily from LiDAR (Light Detection and Ranging) systems. It is an open, binary format that stores point cloud data efficiently.

Key Features of LAS Files:

  • Versions: LAS 1.0 through 1.4, with 1.4 being the latest and most feature-rich.
  • Structure:
    • Header: Contains metadata about the file, including version, point data format, coordinate system, and bounds.
    • Variable Length Records (VLRs): Optional records for extended information like coordinate system details.
    • Point Data Records: The core data, each containing position (X, Y, Z), intensity, return information, classification, and more.
  • Common Attributes:
    • Position: X, Y, Z coordinates (scaled and offset).
    • Intensity: Strength of the laser return.
    • Return Number: Which return this point represents (useful for vegetation analysis).
    • Classification: Point type (ground, vegetation, building, etc.).
    • GPS Time: Timestamp for each point.
    • RGB: Color values for photogrammetric data.
  • Compression: LAZ is the compressed version of LAS, reducing file size significantly while maintaining full compatibility.

In this project, LAS/LAZ files are the primary input format for point cloud processing and visualization.

For Potree

1. Clone and Build Potree from GitHub

https://github.com/potree/potree.git

2.Install dependencies

cd potree
npm install

For PotreeConverter:

1. Clone and Build PotreeConverter from GitHub

git clone https://github.com/potree/PotreeConverter.git
cd PotreeConverter

2.Install Dependencies:

sudo apt install cmake gdal-bin libboost-all-dev

3. Build PotreeConverter

mkdir build
cd build
cmake ..
make
sudo make install

4. If not installed proper.(from PotreeConverter folder)

1. Install required dependencies

sudo apt update
sudo apt install -y \
cmake \
g++ \
make \
libboost-all-dev \
libgdal-dev \
libtbb-dev \
libeigen3-dev



2.Clean old build completely

rm -rf build
mkdir build
cd build

3.Configure with CMake

cmake ..

4. Build PotreeConverter

make -j$(nproc)

5.Verify executable exists

find . -name "PotreeConverter"

Create Folder and add .las file in it.

Run command for Converting .las file:(from build folder)

./PotreeConverter \
/mnt/c/Users/ASUS/Documents/PointCloud/data/Philadelphia_100.las \
-o /mnt/c/Users/ASUS/Documents/PointCloud/potree/pointclouds/output


Start a local web server from potree folder:

python3 -m http.server 1234

If port is busy.

1.Find the process:

lsof -i :1234

2. Kill it:

kill PID

3. Run Finally:

python3 -m http.server 1234


About

PointCloud Visualization using Potree is a web-based 3D visualization project that enables interactive exploration of large-scale point cloud datasets directly in the browser. The project uses the Potree WebGL renderer to efficiently render millions of points captured from LiDAR scans or 3D mapping technologies.

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