Added a congig for the preproc, extracting BW-NIR-D 3x128x128 face from BATL DB

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

+#!/usr/bin/env python2
+# -*- coding: utf-8 -*-
+
+# =============================================================================
+# Import here:
+from bob.pad.face.preprocessor import VideoFaceCropAlignBlockPatch
+
+from bob.pad.face.preprocessor import FaceCropAlign
+
+from bob.bio.video.preprocessor import Wrapper
+
+from bob.bio.video.utils import FrameSelector
+
+from bob.pad.face.preprocessor.FaceCropAlign import auto_norm_image as _norm_func
+
+from bob.pad.face.preprocessor import BlockPatch
+
+
+# =============================================================================
+# names of the channels to process:
+_channel_names = ['color', 'infrared', 'depth']
+
+
+# =============================================================================
+# dictionary containing preprocessors for all channels:
+_preprocessors = {}
+
+"""
+Preprocessor to be used for Color channel.
+"""
+FACE_SIZE = 128  # The size of the resulting face
+RGB_OUTPUT_FLAG = False  # BW output
+USE_FACE_ALIGNMENT = True  # use annotations
+MAX_IMAGE_SIZE = None  # no limiting here
+FACE_DETECTION_METHOD = None  # use ANNOTATIONS
+MIN_FACE_SIZE = 50  # skip small faces
+
+_image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
+                                    rgb_output_flag = RGB_OUTPUT_FLAG,
+                                    use_face_alignment = USE_FACE_ALIGNMENT,
+                                    max_image_size = MAX_IMAGE_SIZE,
+                                    face_detection_method = FACE_DETECTION_METHOD,
+                                    min_face_size = MIN_FACE_SIZE)
+
+_frame_selector = FrameSelector(selection_style = "all")
+
+_preprocessor_rgb = Wrapper(preprocessor = _image_preprocessor,
+                            frame_selector = _frame_selector)
+
+_preprocessors[_channel_names[0]] = _preprocessor_rgb
+
+"""
+Preprocessor to be used for Infrared (or Thermal) channels:
+"""
+FACE_SIZE = 128  # The size of the resulting face
+RGB_OUTPUT_FLAG = False  # Gray-scale output
+USE_FACE_ALIGNMENT = True  # use annotations
+MAX_IMAGE_SIZE = None  # no limiting here
+FACE_DETECTION_METHOD = None  # use annotations
+MIN_FACE_SIZE = 50  # skip small faces
+NORMALIZATION_FUNCTION = _norm_func
+NORMALIZATION_FUNCTION_KWARGS = {}
+NORMALIZATION_FUNCTION_KWARGS = {'n_sigma':3.0, 'norm_method':'MAD'}
+
+_image_preprocessor_ir = FaceCropAlign(face_size = FACE_SIZE,
+                                    rgb_output_flag = RGB_OUTPUT_FLAG,
+                                    use_face_alignment = USE_FACE_ALIGNMENT,
+                                    max_image_size = MAX_IMAGE_SIZE,
+                                    face_detection_method = FACE_DETECTION_METHOD,
+                                    min_face_size = MIN_FACE_SIZE,
+                                    normalization_function = NORMALIZATION_FUNCTION,
+                                    normalization_function_kwargs = NORMALIZATION_FUNCTION_KWARGS)
+
+_preprocessor_ir = Wrapper(preprocessor = _image_preprocessor_ir,
+                               frame_selector = _frame_selector)
+
+_preprocessors[_channel_names[1]] = _preprocessor_ir
+
+"""
+Preprocessor to be used for Depth channel:
+"""
+FACE_SIZE = 128  # The size of the resulting face
+RGB_OUTPUT_FLAG = False  # Gray-scale output
+USE_FACE_ALIGNMENT = True  # use annotations
+MAX_IMAGE_SIZE = None  # no limiting here
+FACE_DETECTION_METHOD = None  # use annotations
+MIN_FACE_SIZE = 50  # skip small faces
+NORMALIZATION_FUNCTION = _norm_func
+NORMALIZATION_FUNCTION_KWARGS = {}
+NORMALIZATION_FUNCTION_KWARGS = {'n_sigma':6.0, 'norm_method':'MAD'}
+
+_image_preprocessor_d = FaceCropAlign(face_size = FACE_SIZE,
+                                    rgb_output_flag = RGB_OUTPUT_FLAG,
+                                    use_face_alignment = USE_FACE_ALIGNMENT,
+                                    max_image_size = MAX_IMAGE_SIZE,
+                                    face_detection_method = FACE_DETECTION_METHOD,
+                                    min_face_size = MIN_FACE_SIZE,
+                                    normalization_function = NORMALIZATION_FUNCTION,
+                                    normalization_function_kwargs = NORMALIZATION_FUNCTION_KWARGS)
+
+_preprocessor_d = Wrapper(preprocessor = _image_preprocessor_d,
+                               frame_selector = _frame_selector)
+
+_preprocessors[_channel_names[2]] = _preprocessor_d
+
+
+# =============================================================================
+# define parameters and an instance of the patch extractor:
+PATCH_SIZE = 128
+STEP = 1
+
+_block_patch_128x128 = BlockPatch(patch_size = PATCH_SIZE,
+                                  step = STEP,
+                                  use_annotations_flag = False)
+
+
+# =============================================================================
+"""
+Define an instance for extraction of one (**whole face**) multi-channel
+(BW-NIR-D) face patch of the size (3 x 128 x 128).
+"""
+video_face_crop_align_bw_ir_d_channels_3x128x128 = VideoFaceCropAlignBlockPatch(preprocessors = _preprocessors,
+                                                                                channel_names = _channel_names,
+                                                                                return_multi_channel_flag = False,
+                                                                                block_patch_preprocessor = _block_patch_128x128)
+