def createExitModel(ModelName, gray=True, preprocessFunc=lambda x: x):
FeatureName = "Wyjscie"
TrainModeName = FeatureName + ModelName
image_size_level = 5
base_scale = 1.0
cols, rows = moil.getColsRows(level=image_size_level,
base_scale=base_scale)
if (gray):
mode = 0
channels_in = 1
color_mode = 'grayscale'
else:
mode = 1
channels_in = 3
color_mode = 'rgb'
filters = 8
weights_path = "../../weights/unet" + TrainModeName
var_filename = "../../weights/var" + TrainModeName + ".txt"
Mod = md.Models(rows,
cols,
mode=mode,
channels=channels_in,
weights_path=weights_path,
var_filename=var_filename,
read_func=moil.read_and_size,
preprocessFunc=preprocessFunc)
Mod.get_model(filters=filters)
Mod.load_weights()
return Mod
width_shift_range=aug['width_shift_range'],
height_shift_range=aug['height_shift_range'],
zoom_range=aug['zoom_range'],
shear_range=aug['shear_range'],
rescale=aug['rescale'],
fill_mode=aug['fill_mode'])
train_generator = f.flow_from_directory_extension(directory=path,
batch_size=batch_size,
color_mode=color_mode,
class_mode=class_mode,
target_size=(rows, cols))
Mod = md.Models(rows,
cols,
mode=mode,
channels=channels_in,
show_function=show_function,
read_func=read_function,
validate_path_provider_func=validate_path_provider_func,
validate_start_path=validate_start_path,
weights_path=weights_path,
var_filename=var_filename)
# model creation
model = Mod.get_model(filters=filters, le=learn_rate, decay=decay_rate)
weights_loaded = False
if load_weights:
weights_loaded = Mod.load_weights()
if not weights_loaded:
Mod.save_weights()
Mod.plot_loss(500)
Mod.check_performance(train_generator, times=check_perf_times)