Use the best linear SVM classifier trained and tested on Dataset6. i.e. px100m80, so tile size is 100x100 pixles (80x80) meters. Use the vocabulary size and mode (Detection/Grid) which produced the best validation results.
[x] Function to generate tile image(s) from random location(s) of a class mask, such that at least 80% the pixels from the tile belong to the desired class. See nonSlumTiling.m
[x] Script to and generate 10 random tiles per class
[x] Publish
[x] Script to test the tile class label prediction using the best pre-trained imageCategoryClassifier on the 10 random tiles from each class
Use the best linear SVM classifier trained and tested on Dataset6. i.e. px100m80, so tile size is 100x100 pixles (80x80) meters. Use the vocabulary size and mode (Detection/Grid) which produced the best validation results.
[x] Function to generate tile image(s) from random location(s) of a class mask, such that at least 80% the pixels from the tile belong to the desired class. See
nonSlumTiling.m[x] Script to and generate 10 random tiles per class
[x] Publish
[x] Script to test the tile class label prediction using the best pre-trained
imageCategoryClassifieron the 10 random tiles from each class[x] Run the prediction script
[x] Publish