From 036e437585a39c8e0df502d3a57de5958b7ff06d Mon Sep 17 00:00:00 2001
From: Amir Mohammadi <183.amir@gmail.com>
Date: Mon, 3 Apr 2017 17:17:11 +0200
Subject: [PATCH] Use preprocessing and extraction logic from bob.bio.base
---
bob/pad/base/test/dummy/extractor.py | 3 +
bob/pad/base/tools/FileSelector.py | 30 +++++----
bob/pad/base/tools/algorithm.py | 2 +-
bob/pad/base/tools/extractor.py | 95 +++++++++++++++-------------
bob/pad/base/tools/preprocessor.py | 85 +++++++++++++------------
5 files changed, 119 insertions(+), 96 deletions(-)
diff --git a/bob/pad/base/test/dummy/extractor.py b/bob/pad/base/test/dummy/extractor.py
index 8e65a74..39959a5 100644
--- a/bob/pad/base/test/dummy/extractor.py
+++ b/bob/pad/base/test/dummy/extractor.py
@@ -18,4 +18,7 @@ class DummyExtractor(Extractor):
assert (data in _data)
return data + 1.0
+ def train(self, training_data, extractor_file):
+ pass
+
extractor = DummyExtractor()
diff --git a/bob/pad/base/tools/FileSelector.py b/bob/pad/base/tools/FileSelector.py
index 201877f..d011e78 100644
--- a/bob/pad/base/tools/FileSelector.py
+++ b/bob/pad/base/tools/FileSelector.py
@@ -99,17 +99,22 @@ class FileSelector(object):
return [realpaths, attackpaths]
# List of files that will be used for all files
- def original_data_list(self, groups=None):
- """Returns the the joint list of original (real and attack) file names."""
- return self.database.original_file_names(self.database.all_files(groups=groups))
-
- def original_data_list_files(self, groups=None):
- """Returns the joint list of original (real and attack) data files that can be used for preprocessing."""
+ def original_data_list(self, groups = None):
+ """Returns the list of original ``PadFile`` objects that can be used for preprocessing."""
files = self.database.all_files(groups=groups)
if len(files) != 2:
fileset = files
else:
fileset = files[0]+files[1]
+ return fileset
+
+ def original_directory_and_extension(self):
+ """Returns the directory and extension of the original files."""
+ return self.database.original_directory, self.database.original_extension
+
+ def original_data_list_files(self, groups=None):
+ """Returns the joint list of original (real and attack) data files that can be used for preprocessing."""
+ fileset = self.original_data_list(groups=groups)
return fileset, self.database.original_directory, self.database.original_extension
def preprocessed_data_list(self, groups=None):
@@ -125,12 +130,15 @@ class FileSelector(object):
return self.get_paths(self.database.all_files(groups=groups), "projected")
# Training lists
- def training_list(self, directory_type, step):
- """Returns the tuple of lists (real, attacks) of features that should be used for projector training.
- The directory_type might be any of 'preprocessed', 'extracted', or 'projected'.
- The step might by any of 'train_extractor', 'train_projector', or 'train_enroller'.
+ def training_list(self, directory_type, step, combined=False):
+ """
+ Returns a list of lists (real, attacks) or just list of all real and
+ attack features depending on combined that should be used for projector
+ training. The directory_type might be any of 'preprocessed',
+ 'extracted', or 'projected'. The step might by any of
+ 'train_extractor', 'train_projector', or 'train_enroller'.
"""
- return self.get_paths(self.database.training_files(step), directory_type, False)
+ return self.get_paths(self.database.training_files(step), directory_type, combined)
def toscore_objects(self, group):
"""Returns the File objects used to compute the raw scores."""
diff --git a/bob/pad/base/tools/algorithm.py b/bob/pad/base/tools/algorithm.py
index 0bd4cc3..6a52b9b 100644
--- a/bob/pad/base/tools/algorithm.py
+++ b/bob/pad/base/tools/algorithm.py
@@ -52,7 +52,7 @@ def train_projector(algorithm, extractor, allow_missing_files=False, force=False
# train projector
logger.info("- Projection: loading training data")
train_files = fs.training_list('extracted', 'train_projector')
- train_features = read_features(train_files, extractor)
+ train_features = read_features(train_files, extractor, True, allow_missing_files)
logger.info("- Projection: training projector '%s' using %d training files: ", fs.projector_file,
len(train_files))
diff --git a/bob/pad/base/tools/extractor.py b/bob/pad/base/tools/extractor.py
index f67783a..b48872e 100644
--- a/bob/pad/base/tools/extractor.py
+++ b/bob/pad/base/tools/extractor.py
@@ -16,6 +16,7 @@ logger = logging.getLogger("bob.pad.base")
from .FileSelector import FileSelector
from bob.bio.base import utils
from .preprocessor import read_preprocessed_data
+from bob.bio.base.tools.extractor import read_features
def train_extractor(extractor, preprocessor, allow_missing_files=False, force=False):
@@ -41,7 +42,6 @@ def train_extractor(extractor, preprocessor, allow_missing_files=False, force=Fa
force : bool
If given, the extractor file is regenerated, even if it already exists.
"""
-
if not extractor.requires_training:
logger.warn(
"The train_extractor function should not have been called, since the extractor does not need training.")
@@ -52,17 +52,25 @@ def train_extractor(extractor, preprocessor, allow_missing_files=False, force=Fa
# the file to write
if utils.check_file(fs.extractor_file, force,
extractor.min_extractor_file_size):
- logger.info("- Extraction: extractor '%s' already exists.", fs.extractor_file)
+ logger.info("- Extraction: extractor '%s' already exists.",
+ fs.extractor_file)
else:
bob.io.base.create_directories_safe(os.path.dirname(fs.extractor_file))
# read training files
- train_files = fs.training_list('preprocessed', 'train_extractor')
- train_data = read_preprocessed_data(train_files, preprocessor)
- logger.info("- Extraction: training extractor '%s' using %d training files:", fs.extractor_file,
- len(train_files))
+ train_files = fs.training_list(
+ 'preprocessed', 'train_extractor', combined=~extractor.split_training_data_by_client)
+ train_data = read_preprocessed_data(
+ train_files, preprocessor, extractor.split_training_data_by_client, allow_missing_files)
+ if extractor.split_training_data_by_client:
+ logger.info("- Extraction: training extractor '%s' using %d classes:",
+ fs.extractor_file, len(train_files))
+ else:
+ logger.info("- Extraction: training extractor '%s' using %d training files:",
+ fs.extractor_file, len(train_files))
# train model
extractor.train(train_data, fs.extractor_file)
+
def extract(extractor, preprocessor, groups=None, indices=None, allow_missing_files=False, force=False):
"""Extracts features from the preprocessed data using the given extractor.
@@ -87,6 +95,9 @@ def extract(extractor, preprocessor, groups=None, indices=None, allow_missing_fi
If specified, only the features for the given index range ``range(begin, end)`` should be extracted.
This is usually given, when parallel threads are executed.
+ allow_missing_files : bool
+ If set to ``True``, preprocessed data files that are not found are silently ignored.
+
force : bool
If given, files are regenerated, even if they already exist.
"""
@@ -97,7 +108,7 @@ def extract(extractor, preprocessor, groups=None, indices=None, allow_missing_fi
feature_files = fs.feature_list(groups=groups)
# select a subset of indices to iterate
- if indices != None:
+ if indices is not None:
index_range = range(indices[0], indices[1])
logger.info("- Extraction: splitting of index range %s" % str(indices))
else:
@@ -106,44 +117,42 @@ def extract(extractor, preprocessor, groups=None, indices=None, allow_missing_fi
logger.info("- Extraction: extracting %d features from directory '%s' to directory '%s'", len(index_range),
fs.directories['preprocessed'], fs.directories['extracted'])
for i in index_range:
- data_file = str(data_files[i])
- feature_file = str(feature_files[i])
-
- if not utils.check_file(feature_file, force, 1000):
+ data_file = data_files[i]
+ feature_file = feature_files[i]
+
+ if not os.path.exists(data_file) and preprocessor.writes_data:
+ if allow_missing_files:
+ logger.debug(
+ "... Cannot find preprocessed data file %s; skipping", data_file)
+ continue
+ else:
+ logger.error(
+ "Cannot find preprocessed data file %s", data_file)
+
+ if not utils.check_file(feature_file, force,
+ extractor.min_feature_file_size):
+ logger.debug(
+ "... Extracting features for data file '%s'", data_file)
+ # create output directory before reading the data file (is
+ # sometimes required, when relative directories are specified,
+ # especially, including a .. somewhere)
+ bob.io.base.create_directories_safe(os.path.dirname(feature_file))
# load data
data = preprocessor.read_data(data_file)
# extract feature
- try:
- logger.info("- Extraction: extracting from file: %s", data_file)
- feature = extractor(data)
- except ValueError:
- logger.warn("WARNING: empty data in file %s", data_file)
- feature = 0
- # write feature
- if feature is not None:
- bob.io.base.create_directories_safe(os.path.dirname(feature_file))
- extractor.write_feature(feature, feature_file)
-
-
-def read_features(file_names, extractor):
- """read_features(file_names, extractor) -> extracted
+ feature = extractor(data)
- Reads the extracted features from ``file_names`` using the given ``extractor``.
+ if feature is None:
+ if allow_missing_files:
+ logger.debug(
+ "... Feature extraction for data file %s failed; skipping", data_file)
+ continue
+ else:
+ raise RuntimeError(
+ "Feature extraction of file '%s' was not successful", data_file)
- **Parameters:**
-
- file_names : [[str], [str]]
- A list of lists of file names (real, attack) to be read.
-
- extractor : py:class:`bob.bio.base.extractor.Extractor` or derived
- The extractor, used for reading the extracted features.
-
- **Returns:**
-
- extracted : [object] or [[object]]
- The list of extracted features, in the same order as in the ``file_names``.
- """
- real_files = file_names[0]
- attack_files = file_names[1]
- return [[extractor.read_feature(str(f)) for f in real_files],
- [extractor.read_feature(str(f)) for f in attack_files]]
+ # write feature
+ extractor.write_feature(feature, feature_file)
+ else:
+ logger.debug(
+ "... Skipping preprocessed data '%s' since feature file '%s' exists", data_file, feature_file)
diff --git a/bob/pad/base/tools/preprocessor.py b/bob/pad/base/tools/preprocessor.py
index 4df9476..0a4784f 100644
--- a/bob/pad/base/tools/preprocessor.py
+++ b/bob/pad/base/tools/preprocessor.py
@@ -11,10 +11,11 @@ import os
import logging
-logger = logging.getLogger("bob.pad.base")
-
from .FileSelector import FileSelector
from bob.bio.base import utils
+from bob.bio.base.tools import read_preprocessed_data
+
+logger = logging.getLogger("bob.pad.base")
def preprocess(preprocessor, groups=None, indices=None, allow_missing_files=False, force=False):
@@ -26,7 +27,7 @@ def preprocess(preprocessor, groups=None, indices=None, allow_missing_files=Fals
**Parameters:**
- preprocessor : py:class:`bob.bio.base.preprocessor.Preprocessor` or derived.
+ preprocessor : py:class:`bob.bio.base.preprocessor.Preprocessor` or derived
The preprocessor, which should be applied to all data.
groups : some of ``('train', 'dev', 'eval')`` or ``None``
@@ -36,42 +37,58 @@ def preprocess(preprocessor, groups=None, indices=None, allow_missing_files=Fals
If specified, only the data for the given index range ``range(begin, end)`` should be preprocessed.
This is usually given, when parallel threads are executed.
+ allow_missing_files : bool
+ If set to ``True``, files for which the preprocessor returns ``None`` are silently ignored.
+
force : bool
If given, files are regenerated, even if they already exist.
"""
+ if not preprocessor.writes_data:
+ # The preprocessor does not write anything, so no need to call it
+ logger.info(
+ "Skipping preprocessing as preprocessor does not write any data")
+ return
+
# the file selector object
fs = FileSelector.instance()
# get the file lists
- data_files, original_directory, original_extension = fs.original_data_list_files(groups=groups)
+ data_files = fs.original_data_list(groups=groups)
+ original_directory, original_extension = fs.original_directory_and_extension()
preprocessed_data_files = fs.preprocessed_data_list(groups=groups)
- # read annotation files
- annotation_list = fs.annotation_list(groups=groups)
-
# select a subset of keys to iterate
if indices is not None:
index_range = range(indices[0], indices[1])
- logger.info("- Preprocessing: splitting of index range %s", str(indices))
+ logger.info(
+ "- Preprocessing: splitting of index range %s", str(indices))
else:
index_range = range(len(data_files))
- logger.info("- Preprocessing: processing %d data files from directory '%s' to directory '%s'", len(index_range),
- fs.directories['original'], fs.directories['preprocessed'])
+ logger.info("- Preprocessing: processing %d data files from directory '%s' to directory '%s'",
+ len(index_range), fs.directories['original'], fs.directories['preprocessed'])
+ # read annotation files
+ annotation_list = fs.annotation_list(groups=groups)
# iterate over the selected files
for i in index_range:
- preprocessed_data_file = str(preprocessed_data_files[i])
+ preprocessed_data_file = preprocessed_data_files[i]
file_object = data_files[i]
- file_name = file_object.make_path(original_directory, original_extension)
+ file_name = file_object.make_path(
+ original_directory, original_extension)
# check for existence
- if not utils.check_file(preprocessed_data_file, force, 1000):
- logger.info("... Processing original data file '%s'", file_name)
- data = preprocessor.read_original_data(file_object, original_directory, original_extension)
- # create output directory before reading the data file (is sometimes required, when relative directories are specified, especially, including a .. somewhere)
- bob.io.base.create_directories_safe(os.path.dirname(preprocessed_data_file))
+ if not utils.check_file(preprocessed_data_file, force,
+ preprocessor.min_preprocessed_file_size):
+ logger.debug("... Processing original data file '%s'", file_name)
+ data = preprocessor.read_original_data(
+ file_object, original_directory, original_extension)
+ # create output directory before reading the data file (is
+ # sometimes required, when relative directories are specified,
+ # especially, including a .. somewhere)
+ bob.io.base.create_directories_safe(
+ os.path.dirname(preprocessed_data_file))
# get the annotations; might be None
annotations = fs.get_annotations(annotation_list[i])
@@ -79,31 +96,17 @@ def preprocess(preprocessor, groups=None, indices=None, allow_missing_files=Fals
# call the preprocessor
preprocessed_data = preprocessor(data, annotations)
if preprocessed_data is None:
- logger.error("Preprocessing of file '%s' was not successful", file_name)
- continue
+ if allow_missing_files:
+ logger.debug(
+ "... Processing original data file '%s' was not successful", file_name)
+ continue
+ else:
+ raise RuntimeError(
+ "Preprocessing of file '%s' was not successful", file_name)
# write the data
preprocessor.write_data(preprocessed_data, preprocessed_data_file)
-
-def read_preprocessed_data(file_names, preprocessor):
- """read_preprocessed_data(file_names, preprocessor, split_by_client = False) -> preprocessed
-
- Reads the preprocessed data from ``file_names`` using the given preprocessor.
- If ``split_by_client`` is set to ``True``, it is assumed that the ``file_names`` are already sorted by client.
-
- **Parameters:**
-
- file_names : [str] or [[str]]
- A list of names of files to be read.
- If ``split_by_client = True``, file names are supposed to be split into groups.
-
- preprocessor : py:class:`bob.bio.base.preprocessor.Preprocessor` or derived
- The preprocessor, which can read the preprocessed data.
-
- **Returns:**
-
- preprocessed : [object] or [[object]]
- The list of preprocessed data, in the same order as in the ``file_names``.
- """
- return [preprocessor.read_data(str(f)) for f in file_names]
+ else:
+ logger.debug("... Skipping original data file '%s' since preprocessed data '%s' exists",
+ file_name, preprocessed_data_file)
--
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