An open source command line toolkit for processing aerial drone imagery
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ODM Logo

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 WebODM.


The easiest way to run ODM on is via docker. To install docker, see Once you have docker installed and working, you can run ODM by placing some images (JPEGs or TIFFs) 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.


ODM can be made accessible from a network via NodeODM.


See for tutorials and more guides.


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

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 and for information on docker/NVIDIA setup.

Native Install (Ubuntu 21.04)

You can run ODM natively on Ubuntu 21.04 (although we don't recommend it):

git clone
cd ODM
bash install

You can then process datasets with ./ /datasets/odm_data_aukerman

Native Install (MacOS)

You can run ODM natively on Intel/ARM MacOS.

First install:

  • Xcode 13 (not 14, there's currently a bug)
  • Homebrew

Then Run:

git clone
cd ODM
bash install

You can then process datasets with ./ /datasets/odm_data_aukerman

This could be improved in the future. Helps us create a Homebrew formula.

Updating a native installation

When updating to a newer version of native ODM, it is recommended that you run:

bash reinstall

to ensure all the dependent packages and modules get updated.

Build Docker Images From Source

If you want to rebuild your own docker image (if you have changed the source code, for example), from the ODM folder you can type:

docker build -t my_odm_image --no-cache .

When building your own Docker image, if image size is of importance to you, you should use the --squash flag, like so:

docker build --squash -t my_odm_image .

This will clean up intermediate steps in the Docker build process, resulting in a significantly smaller image (about half the size).

Experimental flags need to be enabled in Docker to use the --squash flag. To enable this, insert the following into the file /etc/docker/daemon.json:

   "experimental": true

After this, you must restart docker.

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 ==> (case-sensitive).


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

For Linux users, the easiest way to modify the software is to make sure docker is installed, clone the repository and then run from a shell:

$ DATA=/path/to/datasets ./

Where /path/to/datasets is a directory where you can place test datasets (it can also point to an empty directory if you don't have test datasets).

Run configure to set up the required third party libraries:

(odmdev) [user:/code] master+* ± bash reinstall

You can now make changes to the ODM source. When you are ready to test the changes you can simply invoke:

(odmdev) [user:/code] master+* ± ./ --project-path /datasets mydataset

Stop dev container

 docker  stop odmdev

To come back to dev environement

change your_username to your username

docker start odmdev
docker exec -ti odmdev bash
su your_username

If you have questions, join the developer's chat at

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


The dev environment makes use of opendronemap/nodeodm by default. You may want to run docker pull opendronemap/nodeodm before running ./ to avoid using an old cached version.

In order to make a clean build, remove ~/.odm-dev-home and ODM/.setupdevenv.


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


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;


See Trademark Guidelines