How to use segmentmytiff

Segment (georeferenced) raster data in an interactive fashion. Retrain models in seconds. Only small amounts of labeled data necessary because of our use of pretrained base models as feature extractors.

The project setup is documented in project_setup.md.

Installation

To install segmentmytiff from GitHub repository, do:

git clone [email protected]:DroneML/segmentmytiff.git
cd segmentmytiff
python -m pip install .

Train a feature extraction model

To train a feature extraction model run the script "train_model.py" in this repo:

python ./src/segmentmytiff/utils/train_model.py -r ../monochrome_flair_1_toy_dataset_flat/ --train_set_limit 10

This assumes a 'flat', grayscale, version of the FLAIR1 dataset is present at the selected root location.

root
- train
    - input
        - IMG_061946_0.tif
        - IMG_061946_1.tif
        - ...
    - labels
        - MSK_061946_0.tif
        - ...    

Use the script 'monochromize.py' to create greyscale (single band) tifs for every multiband tif in a source folder:

python ./src/segmentmytiff/utils/monochromize.py -i ../flair_1_toy_dataset/ -o ../monochrome_flair_1_toy_dataset/

Credits

This package was created with Copier and the NLeSC/python-template.