OpenDroneMap/ODM

An open source command line toolkit for processing aerial drone imagery. ODM turns simple 2D images into:

• Classified Point Clouds
• 3D Textured Models
• Georeferenced Orthorectified Imagery
• Georeferenced Digital Elevation Models

The application is available for Windows, Mac and Linux and it works from the command line, making it ideal for power users, scripts and for integration with other software.

If you would rather not type commands in a shell and are looking for a friendly user interface, check out OpenDroneMap Desktop.

Quickstart

The easiest way to run ODM is via docker. To install docker, see docs.docker.com. Once you have docker installed and working, you can get ODM by running from a Command Prompt / Terminal:

docker pull opendronemap/odm

Run ODM by placing some images (JPEGs, TIFFs or DNGs) in a folder named “images” (for example C:\Users\youruser\datasets\project\images or /home/youruser/datasets/project/images) and simply run from a Command Prompt / Terminal:

# Windows
docker run -ti --rm -v c:/Users/youruser/datasets:/datasets opendronemap/odm --project-path /datasets project

# Mac/Linux
docker run -ti --rm -v /home/youruser/datasets:/datasets opendronemap/odm --project-path /datasets project

You can pass additional parameters by appending them to the command:

docker run -ti --rm -v /datasets:/datasets opendronemap/odm --project-path /datasets project [--additional --parameters --here]

For example, to generate a DSM (--dsm) and increase the orthophoto resolution (--orthophoto-resolution 2) :

docker run -ti --rm -v /datasets:/datasets opendronemap/odm --project-path /datasets project --dsm --orthophoto-resolution 2

Viewing Results

When the process finishes, the results will be organized as follows:

|-- images/
    |-- img-1234.jpg
    |-- ...
|-- opensfm/
    |-- see mapillary/opensfm repository for more info
|-- odm_meshing/
    |-- odm_mesh.ply                    # A 3D mesh
|-- odm_texturing/
    |-- odm_textured_model.obj          # Textured mesh
    |-- odm_textured_model_geo.obj      # Georeferenced textured mesh
|-- odm_georeferencing/
    |-- odm_georeferenced_model.laz     # LAZ format point cloud
|-- odm_orthophoto/
    |-- odm_orthophoto.tif              # Orthophoto GeoTiff

You can use the following free and open source software to open the files generated in ODM:

• .tif (GeoTIFF): QGIS
• .laz (Compressed LAS): CloudCompare
• .obj (Wavefront OBJ), .ply (Stanford Triangle Format): MeshLab

Note: Opening the .tif files generated by ODM in programs such as Photoshop or GIMP might not work (they are GeoTIFFs, not plain TIFFs). Use QGIS instead.

API

ODM can be made accessible from a network via NodeODM.

Documentation

See http://docs.opendronemap.org for tutorials and more guides.

Forum

We have a vibrant community forum. You can search it for issues you might be having with ODM and you can post questions there. We encourage users of ODM to participate in the forum and to engage with fellow drone mapping users.

Windows Setup

ODM can be installed natively on Windows. Just download the latest setup from the releases page. After opening the ODM Console you can process datasets by typing:

run C:\Users\youruser\datasets\project  [--additional --parameters --here]

GPU Acceleration

ODM has support for doing SIFT feature extraction on a GPU, which is about 2x faster than the CPU on a typical consumer laptop. To use this feature, you need to use the opendronemap/odm:gpu docker image instead of opendronemap/odm and you need to pass the --gpus all flag:

docker run -ti --rm -v c:/Users/youruser/datasets:/datasets --gpus all opendronemap/odm:gpu --project-path /datasets project --feature-type sift

Note: opendronemap/odm:gpu is the latest GPU release. To pin a release, use opendronemap/odm:<version>-gpu (for example opendronemap/odm:3.6.1-gpu); for the latest development build, use opendronemap/odm:edge-gpu.

When you run ODM, if the GPU is recognized, in the first few lines of output you should see:

[INFO]    Writing exif overrides
[INFO]    Maximum photo dimensions: 4000px
[INFO]    Found GPU device: Intel(R) OpenCL HD Graphics
[INFO]    Using GPU for extracting SIFT features

The SIFT GPU implementation is CUDA-based, so should work with most NVIDIA graphics cards of the GTX 9xx Generation or newer.

If you have an NVIDIA card, you can test that docker is recognizing the GPU by running:

docker run --rm --gpus all nvidia/cuda:10.0-base nvidia-smi

If you see an output that looks like this:

Fri Jul 24 18:51:55 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.82       Driver Version: 440.82       CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |

You're in good shape!

See https://github.com/NVIDIA/nvidia-docker and https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker for information on docker/NVIDIA setup.

Video Support

Starting from version 3.0.4, ODM can automatically extract images from video files (.mp4, .mov, .lrv, .ts). Just place one or more video files into the images folder and run the program as usual. Subtitles files (.srt) with GPS information are also supported. Place .srt files in the images folder, making sure that the filenames match. For example, my_video.mp4 ==> my_video.srt (case-sensitive).

Developers

Help improve our software! We welcome contributions from everyone, whether to add new features, improve speed, fix existing bugs or add support for more cameras. Check our code of conduct, the contributing guidelines and how decisions are made.

Installation and first run

Dependencies

Install pixi, (or use the devcontainer):

MSVC and the Windows SDK come from a host install of Visual Studio 2022 or Build Tools (conda-forge Windows native notes):

• Desktop development with C++
• Windows 10/11 SDK

Build and test

pixi install --locked
pixi run build
pixi run test
pixi run smoke

Process a dataset

Process a dataset (from the repo root, with a pixi shell or pixi run):

pixi run odm -- --project-path ~/datasets mydataset
# or, after: eval "$(pixi shell-hook)"
./run.py --project-path ~/datasets mydataset

GPU builds use the gpu environment: pixi install -e gpu && pixi run -e gpu build.

Advanced

Build Docker images from source

CPU image (matches CI):

pixi run docker-build

GPU image:

pixi run docker-build -- --gpu

These stamp the image with the OCI labels (revision, version, created) and tag it opendronemap/odm:edge (:edge-gpu) on master, or opendronemap/odm:<branch> off master. Pass a custom tag or extra docker build flags after --, e.g. pixi run docker-build -- -t my_odm_image --no-cache.

If you have questions, join the developer's chat at https://community.opendronemap.org/c/developers-chat/21

1. Try to keep commits clean and simple
2. Submit a pull request with detailed changes and test results
3. Have fun!

Credits

ODM makes use of several libraries and other awesome open source projects to perform its tasks. Among them we'd like to highlight:

• OpenSfM
• OpenMVS
• PDAL
• Entwine
• MVS Texturing
• GRASS GIS
• GDAL
• PoissonRecon

Citation

OpenDroneMap Authors ODM - A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. OpenDroneMap/ODM GitHub Page 2020; https://github.com/OpenDroneMap/ODM

Trademark

See Trademark Guidelines