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'))
