Added the patch reshaping and normalization utils

bob/pad/face/utils/patch_utils.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Jan 18 17:39:42 2019
+
+@author: Olegs Nikisins
+"""
+
+# =============================================================================
+# Import what is needed here:
+
+import numpy as np
+
+
+# =============================================================================
+# Main body:
+
+def reshape_flat_patches(patches, patch_reshape_parameters = None):
+    """
+    Reshape a set of flattened patches into original dimensions, 2D or 3D
+
+    **Parameters:**
+
+    ``patches`` : 2D :py:class:`numpy.ndarray`
+        An array containing flattened patches. The dimensions are:
+        ``num_patches x len_of_flat_patch``
+
+    ``patch_reshape_parameters`` : [int] or None
+        The parameters to be used for patch reshaping. The loaded patch is
+        vectorized. Example:
+        ``patch_reshape_parameters = [4, 8, 8]``, then the patch of the
+        size (256,) will be reshaped to (4,8,8) dimensions. Only 2D and 3D
+        patches are supported.
+        Default: None.
+
+    **Returns:**
+
+    ``patches_3d`` : [2D or 3D :py:class:`numpy.ndarray`]
+        A list of patches converted to the original dimensions.
+    """
+
+    patches_3d = []
+
+    for patch in patches:
+
+        if patch_reshape_parameters is not None:
+
+            if len(patch_reshape_parameters)==2:
+
+                patch = patch.reshape(patch_reshape_parameters[0],
+                                      patch_reshape_parameters[1]) # reshape the patch
+
+            elif len(patch_reshape_parameters)==3:
+
+                patch = patch.reshape(patch_reshape_parameters[0],
+                                      patch_reshape_parameters[1],
+                                      patch_reshape_parameters[2]) # reshape the patch
+
+        patches_3d.append(patch)
+
+    return patches_3d
+
+
+# =============================================================================
+def mean_std_patch_norm(patches, channel_means = None, channel_stds = None):
+    """
+    Apply mean-std normalization to the patches channel-wise.
+
+    **Parameters:**
+
+    ``patches`` : [2D or 3D :py:class:`numpy.ndarray`]
+        A list of patches converted to the original dimensions.
+
+    ``channel_means`` : [float] or None
+        The channel-wise mean values to be used for mean-std normalization
+        of the patches. Only normalization of 3D patches is currently
+        supported.
+        Default: None.
+
+    ``channel_stds`` : [float] or None
+        The channel-wise std values to be used for mean-std normalization
+        of the patches. Only normalization of 3D patches is currently
+        supported.
+        Default: None.
+
+    **Returns:**
+
+    ``patches_norm_3d`` : [2D or 3D :py:class:`numpy.ndarray`]
+        A list of patches normalized channel-wise.
+    """
+
+    patches_norm_3d = []
+
+    for patch in patches:
+
+        if channel_means is not None: # if normalization parameters are given
+
+            patch = patch.astype(np.float) # convert to float for normalization
+
+            if len(patch.shape) == 3: # Only normalization of 3D patches is currently handled
+
+                for idx, patch_channel in enumerate(patch): # for all channels
+
+                    patch[idx,:,:] = (patch_channel - channel_means[idx]) / channel_stds[idx]
+
+        patches_norm_3d.append(patch)
+
+    return patches_norm_3d
+
+