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odmax extracts still images from GoPro 360 camera types, including GNSS location and time information

Project description

ODMax

ODMax is a utility to extract still frames from 360-degree video platforms such as GoPro or Insta. ODMax preserves the geoghraphical information in videos and adds the geolocation to stills so that they can be used for geospatial applications such as geospatial photogrammetry with OpenDroneMap, or Streetview applications.

We are seeking funding for the following frequently requested functionalities:

  • seamless processing via command-line to WebODM instances
  • seamless processing to streetview products
  • filtering options such as cloud masking, vegetation segmentation or other features
  • variable frame interval detection, based on feature changes (currently a fixed frame interval must be set)

If you wish to fund this or other work on features, please contact us at info@rainbowsensing.com.

note: For instructions how to get Anaconda (with lots of pre-installed libraries) or Miniconda (light weight) installed, please go to https://docs.conda.io/projects/conda/en/latest/

manual: A full manual with examples can be found on https://odmax.readthedocs.io/

compatibility: At this moment ODMax works with GoPro videos. It may or may not work with other 360 degree camera brands and models but this has not been tested.

Installation

To get started with ODMax, we recommend to setup a python virtual environment. We recommend using a Miniconda or Anaconda environment as this will ease installation, and will allow you to use all functionalities without any trouble. Especially geographical plotting with cartopy can be difficult to get installed. With a conda environment this is solved. We have also conveniently packaged all dependencies for you. In the subsections below, you can find specific instructions.

Installation for direct use

If you simply want to add ODMax to an existing python installation or virtual environment, then follow these instructions.

First activate the environment you want ODMax to be installed in (if you don't care about virtual environments, then simply skip this step)

Then install ODMax as follows:

pip install odmax

That's it! You are good to go!

Installation from code base

To install ODMax from scratch in a new virtual environment from the code base, go through these steps. Logical cases when you wish to install from the code base are:

  • You wish to have the very latest non-released version
  • You wish to develop on the code
  • You want to use our pre-packaged conda environment with all dependencies to setup a good virtual environment

First, clone the code with git and move into the cloned folder.

git clone https://github.com/localdevices/ODMax.git
cd ODMax

If you want, setup a virtual environment as follows:

conda env create -f environment.yml

Now install the ODMax package. If you want to develop ODMax please type

pip install -e .

If you just want to use the lates ODMax code base (without the option to develop on the code) type:

pip install .

That's it, you are good to go.

Installation of exiftool for metadata extraction

Especially for photogrammetry or 360 streetview applications, it is essential to have time stamps and geographical coordinates embedded in the extracted stills. ODMax automatically extracts such information from 360-video files if these are recorded by the device used. In order to do this, ODMax requires exiftool to be installed and available on the path. To install exiftool in Windows, please follow the download and installation instructions for Windows on https://exiftool.org/install.html. For Linux, you can also follow the download and installation instructions, or simply acquire a stable version from the package manager of your installed distribution.

Using ODMax

To use ODMax, go to a command line and type

odmax --help

This will provide an overview of the most up-to-date command line options. Alternatively, use our jupyter notebook examples to see common use cases on command-line as well as directly in the API.

Acknowledgement

The development of ODMax has been supported by the Australian National University - Research School of Biology through funding provided by the National Collaborative Research Infrastructure Strategy (NCRIS), Australian Plant Phenomics Facility (APPF), and the Australian Scalabel Drone Cloud (ASDC).

License

ODMax is licensed under AGPL Version 3 (see LICENSE file).

ODMax uses the following libraries and software with said licenses. py360convert is not being maintained actively, therefore the py360convert code has been integrated into the ODMax code base.

Package Version License
numpy 1.21.4 BSD License
opencv-python-headless 4.5.4.60 MIT License
gpxpy 1.5.0 Apache License, Version 2.0
tqdm 4.62.3 MIT License; Mozilla Public License 2.0 (MPL 2.0)
piexif 1.1.3 MIT License
matplotlib 3.5.1 Python Software Foundation License
geopandas 0.10.2 BSD License
pandas 1.3.5 BSD License
Pillow 8.4.0 Historical Permission Notice and Disclaimer (HPND)
py360convert 0.1.0 MIT License

Project organisation

.
├── README.md
├── LICENSE
├── setup.py            <- setup script compatible with pip
├── environment.yml     <- YML-file for setting up a conda environment with dependencies
├── docs                <- Sphinx documentation source code
    ├── ...             <- Sphinx source code files
├── examples            <- Small example files used in notebooks
    ├── ...             <- individual .jpg and .mp4 files
├── notebooks           <- Jupyter notebooks with examples how to use the API
    ├── ...             <- individual Jupyter notebooks
├── odmax               <- odmax library and CLI
    ├── ...             <- odmax functions and CLI main function .py files

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