def mask2poly(predicted_mask, threashold, x_scaler, y_scaler):
polygons = extra_functions.mask2polygons_layer(
predicted_mask[0] > threashold, epsilon=0, min_area=10)
polygons = shapely.affinity.scale(polygons,
xfact=1.0 / x_scaler,
yfact=1.0 / y_scaler,
origin=(0, 0, 0))
return shapely.wkt.dumps(polygons)
def mask2poly(predicted_mask, x_scaler, y_scaler):
polygons = extra_functions.mask2polygons_layer(predicted_mask,
epsilon=0,
min_area=1000)
polygons = MultiPolygon(
[x for x in polygons if 270000 < x.area < 300000 or x.area < 90000])
polygons = shapely.affinity.scale(polygons,
xfact=1.0 / x_scaler,
yfact=1.0 / y_scaler,
origin=(0, 0, 0))
return shapely.wkt.dumps(polygons)
def mask2poly(predicted_mask, x_scaler, y_scaler):
if mask_channel == 7:
min_area = 100
elif mask_channel == 6:
min_area = 5000
else:
min_area = 10
polygons = extra_functions.mask2polygons_layer(predicted_mask, epsilon=0, min_area=min_area)
if image_id == '6100_0_2' and mask_channel == 1:
polygons = polygons.buffer(0.5)
polygons = shapely.affinity.scale(polygons, xfact=1.0 / x_scaler, yfact=1.0 / y_scaler, origin=(0, 0, 0))
return shapely.wkt.dumps(polygons)
def mask2poly(predicted_mask, threshold):
polygons = extra_functions.mask2polygons_layer(
predicted_mask[0] > threshold, epsilon=1, min_area=5.0)
return polygons