def has_attr(self, attr):
return is_valid_path(self.attrs, attr)
def generator(batch_queue):
""" Yields data batches from a queue.
Inputs:
batch_queue - Queue containing tuples of image pairs and labels.
"""
while True:
yield batch_queue.get(True, None)
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Train appearance feature extraction CNN " +
"for reidentification task")
parser.add_argument("model_dir",
type=lambda x: is_valid_path(parser, x),
help="Directory containing reidentification data")
parser.add_argument("--feature_vector_length",
type=int,
default=500,
help="Size of output feature vector")
parser.add_argument(
"--holdout_fraction",
type=float,
default=0.1,
help="Fraction of total number of pairs to use for verification")
parser.add_argument("--dropout_fraction",
type=float,
default=0.1,
help="Fraction for use in dropout layer.")
parser.add_argument("--num_epochs",