Input and output data (images + boulder labels, model setup, model weights and more) for the manuscript "Automatic characterization of boulders on planetary surfaces from high-resolution satellite images"

File 1: raw_data_BOULDERING.zip

Size: 8.8 GB

Summary: It contains all of the rasters (planetary images) and labeled boulders (raw data):

a boulder-mapping file, which is the manually digitized outline of boulders.

a ROM file (stands for Region of Mapping), which depicts the image patches on which the boulder mapping has been conducted.

a global-tiles file, which shows all of the image patches within a raster.

There are multiple locations/images per planetary body.

Structure:

.
└── raw_data/
├── earth/
│ └── image_name/
│   ├── shp/
│   │ ├── -ROM.shp
│   │ ├── -boulder-mapping.shp
│   │ └── -global-tiles.shp
│   └── raster/
│     └── .tif
├── mars/
│ └── image_name/
│   ├── shp/
│   │ ├── -ROM.shp
│   │ ├── -boulder-mapping.shp
│   │ └── -global-tiles.shp
│   └── raster/
│     └── .tif
└── moon/
  └── image_name/
    ├── shp/
    │ ├── -ROM.shp
    │ ├── -boulder-mapping.shp
    │ └── -global-tiles.shp
    └── raster/
      └── .tif

File 2: best_model.zip

Size: 624.7 MB

Summary:

This zip file contains all of the inputs and outputs required/obtained from the training of the BoulderNet Mask R-CNN model (model setup, augmentation pipeline, model weights, log during training, logged metrics):

augmentation_pipeline.json (required as inputs for the training of the algorithm to apply augmentations). See https://github.com/astroNils and the MLtools repository for more information.

Base-RCNN-FPN.yaml (base model setup file).

config.yaml (complete model setup file, merge of the base and Mars-Moon-Earth setup file).

Mars-MoonEarth-v050...yaml (model setup file).

log.txt (log during training of the algorithm).

model_0055999.pth (model weights at second last saving step)

model_0063999.pth (model weights at last saving step)

We advice the use of model weights model_0055999.pth (to avoid slight overfitting).

File 3: Apr2023-Mars-Moon-Earth-mask-5px.zip (pre-processed input images)

Size: 252.8 MB

Summary:

This zip files contains the input data (images and boulder outlines) for the train, validation and test datasets. See https://github.com/astroNils and the MLtools repository for more information in how-to-use the different files.

The json folder contains json files that can be given as input (as a custom dataset) to the Detectron2 platform. The only differences between the two files is how the bounding boxes around masks have been generated. We advised to use "Apr2023-Mars-Moon-Earth-mask-5px.json".

The pkl folder and pickle file includes some informations about the 950 image patches in our boulder dataset.

The pre-processing folder contains all of the training, validation and test image patches and corresponding shapefiles.

The shapefile folder is actually empty (it should not be there!).

Structure:

.
└── preprocessed_inputs/
  ├── json
  ├── pkl
  ├── preprocessing/
  │   ├── train/
  │   │   ├── images
  │   │   └── labels
  │   ├── validation/
  │   │   ├── images
  │   │   └── labels
  │   └── test/
  │       ├── images
  │       └── labels
  └── shp