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
def __init__(self, image_path, winname, size_level, scale):
self.image_path = image_path
self.winname = winname
self.accepted = True
self.masks_done = 0
self.mask = None
self.rr = 0
self.xx = 0
self.yy = 0
self.targetSize = moil.getColsRows(size_level, scale)
def __init__(self,
repo_base,
repo_name,
new_name,
size_level,
scale=0.75,
function=lambda x: x,
onlyMasked=True,
override=True):
self.old_repo = repo_base + repo_name + '/'
self.new_repo = repo_base + new_name + '/'
self.target_size = moil.getColsRows(size_level, scale)
self.onlyMasked = onlyMasked
self.override = override
self.function = function
base_path = '../'
image_size_level = 20
base_scale = 0.75
withMetricOrNo = 1
onlyWithMetric = False
onlyWithoutMetric = False
if withMetricOrNo == 1:
onlyWithMetric = True
if withMetricOrNo == 2:
onlyWithoutMetric = True
batch_size = 32
total_ep = 1
ep = 500
steps = 10
cols, rows = moil.getColsRows(level=image_size_level, base_scale=base_scale)
gray = True
if (gray):
mode = 0
channels_in = 1
color_mode = 'grayscale'
else:
mode = 1
channels_in = 3
color_mode = 'rgb'
# data augmentation
aug = dac.getAugmentationParams()
FeatureName = "Tarcza"
