HIRISE Image Data, Information, Preprocessing and Models
This is a python tool that is used to to query,filter,pre-process and download HIRISE
images from NASA's Planetray Data System(PDS) and University of Arizona's HiWish Databse
and extract hidden patterns and features in the images over 10 preprocessing methods including,
tiling, remove blank space, grayscalimg, dynamic resizing, and multiple dimesnion reduction
methods including principal component analysis, UMAP and t-SNE.
The images can be encoded using convolutional autoencoders, InceptionV3 and Xception networks and
finally the using can call 36 different combination models to cluster the pre-process images as
desired.
For Mac, Windows or Linux users:
pip install HIRISEimgs
To use on colab :
!pip install HIRISEimgs
For developer who wish to download and use the code locally, download the HIRISE_api folder
or use the command cd HIRISE_api to enter into the codebase.
Next, following the steps listed below
- Upgrade your pip environment
pip install --upgrade pip
- Install Requirements
pip install -r requirements.txt
- Install all modules
pip install -e .
Please refer the example workflow in the examples folder. The doumentation can further help you understand the current cope of the package functionalities.
You can open an issue for support.
Contribute using Github Flow. Create a branch, add commits, and open a pull request.
The documentation is dynamically updated using Sphinx and can be accessed in the pdf version or the html version in the docs folder.
MIT License, for more details click here
Initial Release 1.0.0