OSM buildings noisy labels dataset

<p>This dataset contains tile imagery from the OpenStreetMap project alongside label masks for buildings from OpenStreetMap.&nbsp; Besides the original clean label set, additional noisy label sets for random noise, removed and added buildings are provided.</p> <p>The purpose of this dataset is to provide training data for analysing the impact of noisy labels on the performance of models for semantic segmentation in Earth observation.</p> <p>The code for downloading and creating the datasets as well as for performing some preliminary analyses is also provided, however it is necessary to have access to a tile server where OpenStreetMap tiles can be downloaded in sufficient amounts.</p> <p>To reproduce the dataset and perform analysis on it, do the following:</p> <ul> <li>unzip data.zip and code.zip</li> <li>create the folder structure from data</li> <li>Build and activate a python environment from environment.yml</li> <li>Insert the url of a suitable tile server for OSM tiles in line 76 of utils.py</li> <li>Execute download_OSM_dataset.py to download OSM image tiles alongside OSM labels</li> <li>Execute create_noisy_labels.py for the OSM dataset to create noisy label sets</li> <li>Divide the images and labels into train and test data. split_data.py can be used as a baseline for this, but pathnames have to be adjusted and the corresponding directories have to be created first.</li> <li>Call train_model.py to train a model on the data. Specify the data size and the label set by giving command line arguments as shown in train_model.sh</li> </ul> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p>