train.py
def parse_args():
    """
    Returns an argument parser object for image segmentation training script.
    """
    parser = argparse.ArgumentParser(description='Trains adapted U-Net for image segmentation when provided with directories of images and corresponding masks.')
    parser.add_argument('--images_dir', '-i', help='Path to directory containing images.', required=True)
    parser.add_argument('--masks_dir', '-m', help='Path to directory containing masks. Each element of an image-mask pair should have the same basename (regardless of extension).', required=True)
    parser.add_argument('--num_classes', help='Number of classes in segmentation task. 1 for binary segmentation.', default=1, type=int)
    parser.add_argument('--checkpoint', help='Checkpoint directory to write to (or restore from).', default='model_checkpoint', type=str)
    parser.add_argument('--restore_from_checkpoint', help='Boolean: whether or not to restore from checkpoint.', default=False, type=bool)
    parser.add_argument('--log_dir', help='Logging directory for tensorboard', default='logs/')
    parser.add_argument('--seed', help='Random seed', default=0, type=int)
    parser.add_argument('--batch_size', help='Training batch size', default=16, type=int)
    parser.add_argument('--epochs', help='Number of training epochs', default=50, type=int)
    parser.add_argument('--eval_interval', help='Training steps per evaluation', default=10, type=int)
    return parser.parse_args()

    Returns an argument parser object for image segmentation training script.
    
Returns an argument parser object for image segmentation training script.
Returns an argument parser object for image segmentation training script .
def parse_args():
    parser = argparse.ArgumentParser(description='Trains adapted U-Net for image segmentation when provided with directories of images and corresponding masks.')
    parser.add_argument('--images_dir', '-i', help='Path to directory containing images.', required=True)
    parser.add_argument('--masks_dir', '-m', help='Path to directory containing masks. Each element of an image-mask pair should have the same basename (regardless of extension).', required=True)
    parser.add_argument('--num_classes', help='Number of classes in segmentation task. 1 for binary segmentation.', default=1, type=int)
    parser.add_argument('--checkpoint', help='Checkpoint directory to write to (or restore from).', default='model_checkpoint', type=str)
    parser.add_argument('--restore_from_checkpoint', help='Boolean: whether or not to restore from checkpoint.', default=False, type=bool)
    parser.add_argument('--log_dir', help='Logging directory for tensorboard', default='logs/')
    parser.add_argument('--seed', help='Random seed', default=0, type=int)
    parser.add_argument('--batch_size', help='Training batch size', default=16, type=int)
    parser.add_argument('--epochs', help='Number of training epochs', default=50, type=int)
    parser.add_argument('--eval_interval', help='Training steps per evaluation', default=10, type=int)
    return parser.parse_args()
def parse_args ( ) : parser = argparse . ArgumentParser ( description = 'Trains adapted U-Net for image segmentation when provided with directories of images and corresponding masks.' ) parser . add_argument ( '--images_dir' , '-i' , help = 'Path to directory containing images.' , required = True ) parser . add_argument ( '--masks_dir' , '-m' , help = 'Path to directory containing masks. Each element of an image-mask pair should have the same basename (regardless of extension).' , required = True ) parser . add_argument ( '--num_classes' , help = 'Number of classes in segmentation task. 1 for binary segmentation.' , default = 1 , type = int ) parser . add_argument ( '--checkpoint' , help = 'Checkpoint directory to write to (or restore from).' , default = 'model_checkpoint' , type = str ) parser . add_argument ( '--restore_from_checkpoint' , help = 'Boolean: whether or not to restore from checkpoint.' , default = False , type = bool ) parser . add_argument ( '--log_dir' , help = 'Logging directory for tensorboard' , default = 'logs/' ) parser . add_argument ( '--seed' , help = 'Random seed' , default = 0 , type = int ) parser . add_argument ( '--batch_size' , help = 'Training batch size' , default = 16 , type = int ) parser . add_argument ( '--epochs' , help = 'Number of training epochs' , default = 50 , type = int ) parser . add_argument ( '--eval_interval' , help = 'Training steps per evaluation' , default = 10 , type = int ) return parser . parse_args ( )
Returns an argument parser object for image segmentation training script.
Returns an argument parser object for image segmentation training script .
"""
    Returns an argument parser object for image segmentation training script.
    """