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