def get_train_windows(scene, chip_size):
train_windows = []
extent = scene.raster_source.get_extent()
stride = chip_size
windows = extent.get_windows(chip_size, stride)
if scene.aoi_polygons:
windows = Box.filter_by_aoi(windows, scene.aoi_polygons)
for window in windows:
chip = scene.raster_source.get_chip(window)
if np.sum(chip.ravel()) > 0:
train_windows.append(window)
return train_windows
def filter_windows(windows):
if scene.aoi_polygons:
windows = Box.filter_by_aoi(windows, scene.aoi_polygons)
filt_windows = []
for w in windows:
label_arr = label_source.get_labels(w).get_label_arr(w)
null_inds = (
label_arr.ravel() == class_config.get_null_class_id())
if not np.all(null_inds):
filt_windows.append(w)
windows = filt_windows
return windows
def filter_windows(windows):
if scene.aoi_polygons:
windows = Box.filter_by_aoi(windows, scene.aoi_polygons)
return windows
