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"