Added entry point for VideoSparseCoding preprocessor amd initial version of...

Added entry point for VideoSparseCoding preprocessor amd initial version of VideoHistOfSparseCodes extractor

bob/pad/face/config/preprocessor/video_sparse_coding.py

+#!/usr/bin/env python
+
+from bob.pad.face.preprocessor import VideoSparseCoding
+
+
+#=======================================================================================
+# Define instances here:
+
+BLOCK_SIZE = 5
+BLOCK_LENGTH = 10
+MIN_FACE_SIZE = 50
+NORM_FACE_SIZE = 64
+DICTIONARY_FILE_NAMES = ["/idiap/user/onikisins/Projects/ODIN/Python/scripts/test_scripts/data/dictionary_front.hdf5",
+                         "/idiap/user/onikisins/Projects/ODIN/Python/scripts/test_scripts/data/dictionary_hor.hdf5",
+                         "/idiap/user/onikisins/Projects/ODIN/Python/scripts/test_scripts/data/dictionary_vert.hdf5"]
+FRAME_STEP = 10
+
+preprocessor = VideoSparseCoding(gblock_size = BLOCK_SIZE,
+                                 block_length = BLOCK_LENGTH,
+                                 min_face_size = MIN_FACE_SIZE,
+                                 norm_face_size = NORM_FACE_SIZE,
+                                 dictionary_file_names = DICTIONARY_FILE_NAMES,
+                                 frame_step = FRAME_STEP)
\ No newline at end of file

bob/pad/face/extractor/VideoHistOfSparseCodes.py

+#!/usr/bin/env python2
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Sep 27 11:33:45 2017
+
+@author: Olegs Nikisins
+"""
+
+#==============================================================================
+# Import what is needed here:
+
+from bob.bio.base.extractor import Extractor
+
+import numpy as np
+
+import bob.bio.video
+
+from bob.pad.face.extractor import ImageQualityMeasure
+
+#==============================================================================
+# Main body:
+
+class VideoHistOfSparseCodes(Extractor, object):
+    """
+    This class is designed to extract histograms of sparse codes.
+
+    **Parameters:**
+
+    ``method`` : :py:class:`str`
+        A method to use in the histogram computation. Two options are available:
+        "mean" and "hist". Default: "mean".
+    """
+
+    #==========================================================================
+    def __init__(self,
+                 method = "mean"):
+
+        super(VideoHistOfSparseCodes, self).__init__(method = method)
+
+        self.method = method
+
+        # extractor to process a single image/frame:
+        extractor = ImageQualityMeasure()
+
+        # This extractor is used only to write and read the feature vectors.
+        self.video_extractor = bob.bio.video.extractor.Wrapper(extractor)
+
+
+    #==========================================================================
+    def comp_hist_of_sparse_codes(self, frames, method):
+        """
+        Compute the histograms of sparse codes.
+        """
+
+        histograms = []
+
+        for frame_data in frames:
+
+            frame = frame_data[1]
+
+            if method == "mean":
+
+                frame_codes = np.mean(frame, axis=1)
+
+            if method == "hist":
+
+                frame_codes = np.mean(frame!=0, axis=1)
+
+            for idx, row in enumerate(frame_codes):
+
+                frame_codes[idx,:] = row/np.sum(row)
+
+            hist = frame_codes.flatten()
+
+            histograms.append(hist)
+
+        return histograms
+
+
+    #==========================================================================
+    def convert_sparse_codes_to_frame_container(self, list_of_arrays):
+        """
+        Convert an input list of arrays into Frame Container.
+
+        **Parameters:**
+
+        ``list_of_arrays`` : [:py:class:`numpy.ndarray`]
+            A list of arrays.
+
+        **Returns:**
+
+        ``frame_container`` : FrameContainer
+            FrameContainer containing the feature vectors.
+        """
+
+        frame_container = bob.bio.video.FrameContainer() # initialize the FrameContainer
+
+        for idx, item in enumerate(list_of_arrays):
+
+            frame_container.add(idx, item) # add frame to FrameContainer
+
+        return frame_container
+
+
+    #==========================================================================
+    def __call__(self, frames):
+        """
+        Extract feature vectors.
+
+        **Parameters:**
+
+        ``frames`` : FrameContainer or string.
+            Data stored in the FrameContainer,
+            see ``bob.bio.video.utils.FrameContainer`` for further details.
+
+        **Returns:**
+
+        ``frame_container`` : FrameContainer
+            Histograms of sparse codes stored in the FrameContainer.
+        """
+
+        histograms = self.comp_hist_of_sparse_codes(frames, self.method)
+
+        frame_container = self.convert_sparse_codes_to_frame_container(histograms)
+
+        return frame_container
+
+
+    #==========================================================================
+    def write_feature(self, frames, file_name):
+        """
+        Writes the given data (that has been generated using the __call__ function of this class) to file.
+        This method overwrites the write_data() method of the Extractor class.
+
+        **Parameters:**
+
+        ``frames`` :
+            Data returned by the __call__ method of the class.
+
+        ``file_name`` : :py:class:`str`
+            Name of the file.
+        """
+
+        self.video_extractor.write_feature(frames, file_name)
+
+
+    #==========================================================================
+    def read_feature(self, file_name):
+        """
+        Reads the preprocessed data from file.
+        This method overwrites the read_data() method of the Extractor class.
+
+        **Parameters:**
+
+        ``file_name`` : :py:class:`str`
+            Name of the file.
+
+        **Returns:**
+
+        ``frames`` : :py:class:`bob.bio.video.FrameContainer`
+            Frames stored in the frame container.
+        """
+
+        frames = self.video_extractor.read_feature(file_name)
+
+        return frames

bob/pad/face/preprocessor/__init__.py

 from .VideoFaceCrop import VideoFaceCrop
 from .ImageFaceCrop import ImageFaceCrop
 from .FrameDifference import FrameDifference
+from .VideoSparseCoding import VideoSparseCoding
 
 
 def __appropriate__(*args):
@@ -25,5 +26,7 @@ __appropriate__(
     VideoFaceCrop,
     ImageFaceCrop,
     FrameDifference,
+    VideoSparseCoding,
 )
 __all__ = [_ for _ in dir() if not _.startswith('_')]
+

setup.py

@@ -103,6 +103,9 @@ setup(
         # registered preprocessors:
         'bob.pad.preprocessor': [
             'empty-preprocessor = bob.pad.face.config.preprocessor.filename:empty_preprocessor', # no preprocessing
+
+            # The sparse coding based preprocessors
+            'sparse-coding-preprocessor = bob.pad.face.config.preprocessor.video_sparse_coding:preprocessor',
             ],
 
         # registered preprocessors: