def create_masks(bldg_footprints_shp=BUILDING_SHAPEFILE): '''Create masks for images in a directory given the building footprints shapefile Args: bldg_footprints_shp: building footprint shapefile ''' files = files_absolute_path(INPUT_PATH) with fiona.open(bldg_footprints_shp, "r") as shapefile: geoms = [feature["geometry"] for feature in shapefile] for file in files: out_file = get_outfile(file, MASK_BASE_PATH) mask, mask_meta = create_one_mask(file, geoms) save_mask(out_file, mask, mask_meta)
for file in file_list: with rasterio.open(file, 'r') as ds: image = ds.read() # read all raster values image_meta = ds.meta.copy() H = image.shape[1] W = image.shape[2] image_meta.update({ "driver": "GTiff", "height": H, "width": W, "transform": ds.transform, "count": 1 }) prediction = make_prediction_cropped(unet_model, image, initial_size=(224, 224), final_size=(224 - 20, 224 - 20), num_masks=1, num_channels=3) predicted_mask = pred_mask(prediction, 0.5) # Post-processing image_denoise = grow(predicted_mask, 10) image_grow = denoise(image_denoise, 30) # Save predicted mask out_file = get_outfile(file, OUTPUT_PREDICTED_MASK) save_mask(out_file, image_grow, image_meta)
def menu_save(self, info): file_name = get_outfile(folder_name='.bmcs', file_name='') file_ = save_file(file_name=file_name) if file_: pickle.dump(info.object.root, open(file_, 'wb'), 1)
def menu_open(self, info): file_name = get_outfile(folder_name='.bmcs', file_name='') file_ = open_file(file_name=file_name) if file_: info.object.root = pickle.load(open(file_, 'rb'))