From ddbb1251c46916cd7f8b8a1f30fe528cfeb54de0 Mon Sep 17 00:00:00 2001
From: Tiago Freitas Pereira <tiagofrepereira@gmail.com>
Date: Tue, 31 Oct 2017 16:48:16 +0100
Subject: [PATCH] Removing LFW tfrecord generator
---
.../tensorflow/script/lfw_db_to_tfrecords.py | 109 ------------------
setup.py | 1 -
2 files changed, 110 deletions(-)
delete mode 100755 bob/learn/tensorflow/script/lfw_db_to_tfrecords.py
diff --git a/bob/learn/tensorflow/script/lfw_db_to_tfrecords.py b/bob/learn/tensorflow/script/lfw_db_to_tfrecords.py
deleted file mode 100755
index 91dc27b1..00000000
--- a/bob/learn/tensorflow/script/lfw_db_to_tfrecords.py
+++ /dev/null
@@ -1,109 +0,0 @@
-#!/usr/bin/env python
-
-"""Script that converts bob.db.lfw database to TF records
-
-Usage:
- %(prog)s <data-path> <output-file> [--extension=<arg> --protocol=<arg> --data-type=<arg> --verbose]
- %(prog)s --help
- %(prog)s --version
-
-Options:
- -h --help show this help message and exit
- <data-path> Path that contains the features
- --extension=<arg> Default feature extension [default: .hdf5]
- --protocol=<arg> One of the LFW protocols [default: view1]
- --data-type=<arg> TFRecord data type [default: uint8]
-
-
-The possible protocol options are the following:
- 'view1', 'fold1', 'fold2', 'fold3', 'fold4', 'fold5', 'fold6', 'fold7', 'fold8', 'fold9', 'fold10'
-
-More details about our interface to LFW database can be found in
-https://www.idiap.ch/software/bob/docs/bob/bob.db.lfw/master/index.html.
-
-
-"""
-
-import tensorflow as tf
-from bob.io.base import create_directories_safe
-from bob.bio.base.utils import load, read_config_file
-from bob.core.log import setup, set_verbosity_level
-import bob.db.lfw
-import os
-import bob.io.image
-import bob.io.base
-import numpy
-
-logger = setup(__name__)
-
-
-def _bytes_feature(value):
- return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
-
-
-def _int64_feature(value):
- return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))
-
-def file_to_label(client_ids, f):
- return client_ids[str(f.client_id)]
-
-def get_pairs(all_pairs, match=True):
-
- enroll = []
- probe = []
- for p in all_pairs:
- if p.is_match == match:
- enroll.append(p.enroll_file)
- probe.append(p.probe_file)
-
- return enroll, probe
-
-
-def main(argv=None):
- from docopt import docopt
- args = docopt(__doc__, version='')
-
- data_path = args['<data-path>']
- output_file = args['<output-file>']
- extension = args['--extension']
- protocol = args['--protocol']
- data_type = args['--data-type']
-
- # Sets-up logging
- if args['--verbose']:
- verbosity = 2
- set_verbosity_level(logger, verbosity)
-
- # Loading LFW models
- database = bob.db.lfw.Database()
- enroll, probe = get_pairs(database.pairs(protocol=protocol), match=True)
- #client_ids = list(set([f.client_id for f in all_pairs]))
-
- client_ids = list(set([f.client_id for f in enroll] + [f.client_id for f in probe]))
- client_ids = dict(zip(client_ids, range(len(client_ids))))
-
- create_directories_safe(os.path.dirname(output_file))
-
- n_files = len(enroll)
- with tf.python_io.TFRecordWriter(output_file) as writer:
- for e, p, i in zip(enroll, probe, range(len(enroll)) ):
- logger.info('Processing pair %d out of %d', i + 1, n_files)
-
- if os.path.exists(e.make_path(data_path, extension)) and os.path.exists(p.make_path(data_path, extension)):
- for f in [e, p]:
- path = f.make_path(data_path, extension)
- data = bob.io.image.to_matplotlib(bob.io.base.load(path)).astype(data_type)
- data = data.tostring()
-
- feature = {'data': _bytes_feature(data),
- 'label': _int64_feature(file_to_label(client_ids, f)),
- 'key': _bytes_feature(str(f.path)),
- }
-
- example = tf.train.Example(features=tf.train.Features(feature=feature))
- writer.write(example.SerializeToString())
- else:
- logger.debug("... Processing original data file '{0}' was not successful".format(path))
-
-if __name__ == '__main__':
- main()
diff --git a/setup.py b/setup.py
index 58a11fcd..1ee1774b 100755
--- a/setup.py
+++ b/setup.py
@@ -50,7 +50,6 @@ setup(
'bob_tf_compute_statistics.py = bob.learn.tensorflow.script.compute_statistics:main',
'bob_tf_db_to_tfrecords = bob.learn.tensorflow.script.db_to_tfrecords:main',
'bob_tf_load_and_debug.py = bob.learn.tensorflow.script.load_and_debug:main',
- 'bob_tf_lfw_db_to_tfrecords.py = bob.learn.tensorflow.script.lfw_db_to_tfrecords:main',
'bob_tf_train_generic = bob.learn.tensorflow.script.train_generic:main',
'bob_tf_eval_generic = bob.learn.tensorflow.script.eval_generic:main',
'bob_tf_predict_generic = bob.learn.tensorflow.script.predict_generic:main',
--
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