diff --git a/advanced/databases/biowave/4.json b/advanced/databases/biowave/4.json
new file mode 100644
index 0000000000000000000000000000000000000000..a928cf223eff9c17d0a9b7e1a1ee90a649ddcdcf
--- /dev/null
+++ b/advanced/databases/biowave/4.json
@@ -0,0 +1,874 @@
+{
+ "root_folder": "/idiap/project/biowave/biowave_v1/data",
+ "description": "BIOWAVE Vein Database",
+ "protocols": [
+ {
+ "name": "Idiap_1_1_R_BEAT_test",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_BEAT_test",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_BEAT_test",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_BEAT_test",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_BEAT_test",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_BEAT_test",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_5_5_R_BEAT_test",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_BEAT_test",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_BEAT_test",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_BEAT_test",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_BEAT_test",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_BEAT_test",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_1_5_R_BEAT_test",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_R_BEAT_test",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_5_R_BEAT_test",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_R_BEAT_test",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_5_R_BEAT_test",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_R_BEAT_test",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_1_1_R",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_R",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_1_R",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_R",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_1_R",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_R",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_1_5_R",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_R",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_5_R",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_R",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_5_R",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_R",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_3_5_R",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_3_5_R",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_3_5_R",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_3_5_R",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_3_5_R",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_3_5_R",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_5_5_R",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_R",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_5_5_R",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_R",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_5_5_R",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_R",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_1_1_L",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_L",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_1_L",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_L",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_1_L",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_L",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_1_5_L",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_L",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_5_L",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_L",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_5_L",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_L",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_5_5_L",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_L",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_5_5_L",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_L",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_5_5_L",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_L",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_1_1_R_less",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_less",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_less",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_less",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_less",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_less",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_1_5_R_less",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_R_less",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_5_R_less",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_R_less",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_1_5_R_less",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_1_5_R_less",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_5_5_R_less",
+ "template": "advanced_vein_recognition_2/1",
+ "views": {
+ "train": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_less",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_less",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_less",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateView",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_less",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "View",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_less",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_1_1_R_annotations_BEAT_test",
+ "template": "advanced_vein_annotations/1",
+ "views": {
+ "train": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_BEAT_test",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_BEAT_test",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_BEAT_test",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_BEAT_test",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_R_BEAT_test",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_2_1_R_annotations_BEAT_test",
+ "template": "advanced_vein_annotations/1",
+ "views": {
+ "train": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_BEAT_test",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_BEAT_test",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_BEAT_test",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_BEAT_test",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_R_BEAT_test",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_1_1_R_annotations",
+ "template": "advanced_vein_annotations/1",
+ "views": {
+ "train": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_R",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_R",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_R",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_R",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_R",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_2_1_R_annotations",
+ "template": "advanced_vein_annotations/1",
+ "views": {
+ "train": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_R",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_R",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_R",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_R",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_R",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_1_1_L_annotations",
+ "template": "advanced_vein_annotations/1",
+ "views": {
+ "train": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_L",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_L",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_L",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_L",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_1_1_L",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "Idiap_2_1_L_annotations",
+ "template": "advanced_vein_annotations/1",
+ "views": {
+ "train": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_L",
+ "group": "world"
+ }
+ },
+ "dev_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_L",
+ "group": "dev",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "ViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_L",
+ "group": "dev",
+ "purpose": "probe"
+ }
+ },
+ "eval_templates": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_L",
+ "group": "eval",
+ "purpose": "enroll"
+ }
+ },
+ "eval_probes": {
+ "view": "TemplateViewAnnotations",
+ "parameters": {
+ "protocol": "Idiap_5_5_L",
+ "group": "eval",
+ "purpose": "probe"
+ }
+ }
+ }
+ },
+ {
+ "name": "annotation_benchmark",
+ "template": "advanced_annotation_benchmark/1",
+ "views": {
+ "annotations": {
+ "view": "AnnotationBenchmark",
+ "parameters": {
+ "protocol": "Idiap_1_1_R"
+ }
+ }
+ }
+ }
+ ],
+ "schema_version": 2
+}
\ No newline at end of file
diff --git a/advanced/databases/biowave/4.py b/advanced/databases/biowave/4.py
new file mode 100644
index 0000000000000000000000000000000000000000..fa4837a641853c28b2e4ca8197743c88ad04bd60
--- /dev/null
+++ b/advanced/databases/biowave/4.py
@@ -0,0 +1,497 @@
+###############################################################################
+# #
+# Copyright (c) 2018 Idiap Research Institute, http://www.idiap.ch/ #
+# Contact: beat.support@idiap.ch #
+# #
+# This file is part of the beat.examples module of the BEAT platform. #
+# #
+# Commercial License Usage #
+# Licensees holding valid commercial BEAT licenses may use this file in #
+# accordance with the terms contained in a written agreement between you #
+# and Idiap. For further information contact tto@idiap.ch #
+# #
+# Alternatively, this file may be used under the terms of the GNU Affero #
+# Public License version 3 as published by the Free Software and appearing #
+# in the file LICENSE.AGPL included in the packaging of this file. #
+# The BEAT platform is distributed in the hope that it will be useful, but #
+# WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY #
+# or FITNESS FOR A PARTICULAR PURPOSE. #
+# #
+# You should have received a copy of the GNU Affero Public License along #
+# with the BEAT platform. If not, see http://www.gnu.org/licenses/. #
+# #
+###############################################################################
+
+import os
+import numpy as np
+from collections import namedtuple
+
+from beat.backend.python.database import View as BaseView
+
+import bob.io.base
+import bob.io.image
+import bob.db.biowave_v1
+
+from PIL import Image, ImageDraw, ImageFilter
+
+
+#----------------------------------------------------------
+
+
+def construct_ROI_image(annotations):
+ """Adapted from bob.db.biowave_v1, because we want to separate it in two steps:
+ indexing and image construction"""
+
+ if len(annotations) > 0:
+ return bob.db.biowave_v1.utils.ManualRoiCut(annotations).roi_mask()
+ else:
+ return np.array([], np.uint8)
+
+
+#----------------------------------------------------------
+
+
+def construct_vein_image(annotations, center=False):
+ """Adapted from bob.db.biowave_v1, because we want to separate it in two steps:
+ indexing and image construction"""
+
+ if len(annotations) > 0:
+ im = Image.new('L', (480, 480), (0))
+ draw = ImageDraw.Draw(im)
+ if center:
+ xes_all = [point[1] for line in annotations for point in line]
+ yes_all = [point[0] for line in annotations for point in line]
+ for line in annotations:
+ xes = [point[1] - np.round(np.mean(xes_all)) + 239 for point in line]
+ yes = [point[0] - np.round(np.mean(yes_all)) + 239 for point in line]
+ for point in range(len(line) - 1):
+ draw.line((xes[point],yes[point], xes[point+1], yes[point+1]), fill=255, width = 5)
+ else:
+ for line in annotations:
+ xes = [point[1] for point in line]
+ yes = [point[0] for point in line]
+ for point in range(len(line) - 1):
+ draw.line((xes[point],yes[point], xes[point+1], yes[point+1]), fill=255, width = 5)
+ im = im.filter(ImageFilter.MedianFilter(5))
+ return np.array(np.array(im, dtype = bool), dtype = np.uint8)
+ else:
+ return np.array([], np.uint8)
+
+
+#----------------------------------------------------------
+
+
+def construct_alignment_annotations(annotations):
+ return [ dict(
+ x = np.int32(annotation[1]),
+ y = np.int32(annotation[0])
+ ) for annotation in annotations ]
+
+
+#----------------------------------------------------------
+
+
+class View(BaseView):
+ """Outputs:
+ - image: "{{ system_user.username }}/array_2d_uint8/1"
+ - client_id: "{{ system_user.username }}/uint64/1"
+
+ Several "image" are associated with a given "client_id".
+
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | image | | image | | image | | image | | image | | image |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ ----------------------------------------------- -----------------------------------------------
+ | client_id | | client_id |
+ ----------------------------------------------- -----------------------------------------------
+ """
+
+ def index(self, root_folder, parameters):
+ Entry = namedtuple('Entry', ['client_id', 'image'])
+
+ # Open the database and load the objects to provide via the outputs
+ db = bob.db.biowave_v1.Database()
+
+ objs = sorted(db.objects(protocol=parameters['protocol'],
+ groups=[parameters['group']],
+ purposes=parameters.get('purpose', None),
+ annotated_images=False,
+ imagedir=root_folder),
+ key=lambda x: (x.client_id, x.id))
+
+ return [ Entry(x.client_id, x.make_path(root_folder, '.png')) for x in objs ]
+
+
+ def get(self, output, index):
+ obj = self.objs[index]
+
+ if output == 'client_id':
+ return {
+ 'value': np.uint64(obj.client_id)
+ }
+
+ elif output == 'image':
+ return {
+ 'value': bob.io.base.load(obj.image)
+ }
+
+
+#----------------------------------------------------------
+
+
+class TemplateView(BaseView):
+ """Outputs:
+ - image: "{{ system_user.username }}/array_2d_uint8/1"
+ - model_id: "{{ system_user.username }}/text/1"
+ - client_id: "{{ system_user.username }}/uint64/1"
+
+ Several "image" are associated with a given "model_id".
+ Several "model_id" are associated with a given "client_id".
+
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | image | | image | | image | | image | | image | | image |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ ----------------------------------------------- -----------------------------------------------
+ | model_id | | model_id |
+ ----------------------------------------------- -----------------------------------------------
+ -----------------------------------------------------------------------------------------------
+ | client_id |
+ -----------------------------------------------------------------------------------------------
+
+ Note: for this particular database, there is only one "image"
+ per "model_id".
+ """
+
+ def index(self, root_folder, parameters):
+ Entry = namedtuple('Entry', ['client_id', 'model_id', 'image'])
+
+ # Open the database and load the objects to provide via the outputs
+ db = bob.db.biowave_v1.Database()
+
+ objs = sorted(db.objects(protocol=parameters['protocol'],
+ purposes=parameters['purpose'],
+ groups=[parameters['group']],
+ annotated_images=False,
+ imagedir=root_folder),
+ key=lambda x: (x.client_id, x.id))
+
+ return [ Entry(x.client_id, x.model_id.encode('utf-8'),
+ x.make_path(root_folder, '.png'))
+ for x in objs ]
+
+
+ def get(self, output, index):
+ obj = self.objs[index]
+
+ if output == 'client_id':
+ return {
+ 'value': np.uint64(obj.client_id)
+ }
+
+ elif output == 'model_id':
+ return {
+ 'text': str(obj.model_id)
+ }
+
+ elif output == 'image':
+ return {
+ 'value': bob.io.base.load(obj.image)
+ }
+
+
+#----------------------------------------------------------
+
+
+class ViewAnnotations(BaseView):
+ """Outputs:
+ - image: "{{ system_user.username }}/array_2d_uint8/1"
+ - vein_annotations: "{{ system_user.username }}/array_2d_uint8/1"
+ - ROI_annotations: "{{ system_user.username }}/array_2d_uint8/1"
+ - alignment_annotations: "{{ system_user.username }}/array_1d_coordinates/1"
+ - client_id: "{{ system_user.username }}/uint64/1"
+
+ One "vein_annotations" are associated with a given "image".
+ One "ROI_annotations" are associated with a given "image".
+ One "alignment_annotations" are associated with a given "image".
+ Several "image" are associated with a given "client_id".
+
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | image | | image | | image | | image |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | vein_annotations | | vein_annotations | | vein_annotations | | vein_annotations |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | ROI_annotations | | ROI_annotations | | ROI_annotations | | ROI_annotations |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | alignment_annotations | | alignment_annotations | | alignment_annotations | | alignment_annotations |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ --------------------------------------------------- ---------------------------------------------------
+ | client_id | | client_id |
+ --------------------------------------------------- ---------------------------------------------------
+ """
+
+ def index(self, root_folder, parameters):
+ Entry = namedtuple('Entry', ['client_id', 'alignment_annotations', 'ROI_annotations',
+ 'vein_annotations', 'image'])
+
+ # Open the database and load the objects to provide via the outputs
+ db = bob.db.biowave_v1.Database()
+
+ objs = sorted(db.objects(protocol=parameters['protocol'],
+ groups=[parameters['group']],
+ purposes=parameters.get('purpose', None),
+ annotated_images=True,
+ imagedir=root_folder),
+ key=lambda x: (x.client_id, x.id))
+
+ return [ Entry(x.client_id,
+ x.alignment_annotations(directory=root_folder),
+ x.roi_annotations(directory=root_folder),
+ x.vein_annotations(directory=root_folder),
+ x.make_path(root_folder, '.png'))
+ for x in objs ]
+
+
+ def get(self, output, index):
+ obj = self.objs[index]
+
+ if output == 'client_id':
+ return {
+ 'value': np.uint64(obj.client_id)
+ }
+
+ elif output == 'alignment_annotations':
+ return {
+ 'value': construct_alignment_annotations(obj.alignment_annotations)
+ }
+
+ elif output == 'ROI_annotations':
+ return {
+ 'value': construct_ROI_image(obj.ROI_annotations)
+ }
+
+ elif output == 'vein_annotations':
+ return {
+ 'value': construct_vein_image(obj.vein_annotations)
+ }
+
+ elif output == 'image':
+ return {
+ 'value': bob.io.base.load(obj.image)
+ }
+
+
+#----------------------------------------------------------
+
+
+class TemplateViewAnnotations(BaseView):
+ """Outputs:
+ - image: "{{ system_user.username }}/array_2d_uint8/1"
+ - vein_annotations: "{{ system_user.username }}/array_2d_uint8/1"
+ - ROI_annotations: "{{ system_user.username }}/array_2d_uint8/1"
+ - alignment_annotations: "{{ system_user.username }}/array_1d_coordinates/1"
+ - model_id: "{{ system_user.username }}/model_id/1"
+ - client_id: "{{ system_user.username }}/uint64/1"
+
+ One "vein_annotations" are associated with a given "image".
+ One "ROI_annotations" are associated with a given "image".
+ One "alignment_annotations" are associated with a given "image".
+ Several "image" are associated with a given "model_id".
+ Several "model_id" are associated with a given "client_id".
+
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | image | | image | | image | | image |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | vein_annotations | | vein_annotations | | vein_annotations | | vein_annotations |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | ROI_annotations | | ROI_annotations | | ROI_annotations | | ROI_annotations |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | alignment_annotations | | alignment_annotations | | alignment_annotations | | alignment_annotations |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ --------------------------------------------------- ---------------------------------------------------
+ | model_id | | model_id |
+ --------------------------------------------------- ---------------------------------------------------
+ -------------------------------------------------------------------------------------------------------
+ | client_id |
+ -------------------------------------------------------------------------------------------------------
+
+ Note: for this particular database, there is only one "image"
+ per "model_id".
+ """
+
+ def index(self, root_folder, parameters):
+ Entry = namedtuple('Entry', ['client_id', 'model_id', 'alignment_annotations',
+ 'ROI_annotations', 'vein_annotations', 'image'])
+
+ # Open the database and load the objects to provide via the outputs
+ db = bob.db.biowave_v1.Database()
+
+ objs = sorted(db.objects(protocol=parameters['protocol'],
+ groups=[parameters['group']],
+ purposes=parameters['purpose'],
+ annotated_images=True,
+ imagedir=root_folder),
+ key=lambda x: (x.client_id, x.model_id, x.id))
+
+ return [ Entry(x.client_id,
+ x.model_id.encode('utf-8'),
+ x.alignment_annotations(directory=root_folder),
+ x.roi_annotations(directory=root_folder),
+ x.vein_annotations(directory=root_folder),
+ x.make_path(root_folder, '.png'))
+ for x in objs ]
+
+
+ def get(self, output, index):
+ obj = self.objs[index]
+
+ if output == 'client_id':
+ return {
+ 'value': np.uint64(obj.client_id)
+ }
+
+ elif output == 'model_id':
+ return {
+ 'text': obj.model_id
+ }
+
+ elif output == 'alignment_annotations':
+ return {
+ 'value': construct_alignment_annotations(obj.alignment_annotations)
+ }
+
+ elif output == 'ROI_annotations':
+ return {
+ 'value': construct_ROI_image(obj.ROI_annotations)
+ }
+
+ elif output == 'vein_annotations':
+ return {
+ 'value': construct_vein_image(obj.vein_annotations)
+ }
+
+ elif output == 'image':
+ return {
+ 'value': bob.io.base.load(obj.image)
+ }
+
+
+#----------------------------------------------------------
+
+
+class AnnotationBenchmark(BaseView):
+ """Outputs:
+ - image: "{{ system_user.username }}/array_2d_uint8/1"
+ - vein_annotations: "{{ system_user.username }}/array_2d_uint8/1"
+ - ROI_annotations: "{{ system_user.username }}/array_2d_uint8/1"
+ - alignment_annotations: "{{ system_user.username }}/array_1d_coordinates/1"
+
+ One "vein_annotations" are associated with a given "image".
+ One "ROI_annotations" are associated with a given "image".
+ One "alignment_annotations" are associated with a given "image".
+
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | image | | image | | image | | image |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | vein_annotations | | vein_annotations | | vein_annotations | | vein_annotations |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | ROI_annotations | | ROI_annotations | | ROI_annotations | | ROI_annotations |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ ------------------------- ------------------------- ------------------------- -------------------------
+ | alignment_annotations | | alignment_annotations | | alignment_annotations | | alignment_annotations |
+ ------------------------- ------------------------- ------------------------- -------------------------
+ """
+
+ def index(self, root_folder, parameters):
+ Entry = namedtuple('Entry', ['alignment_annotations', 'ROI_annotations',
+ 'vein_annotations', 'image'])
+
+ # Open the database and load the objects to provide via the outputs
+ db = bob.db.biowave_v1.Database()
+
+ objs = sorted(db.objects(protocol=parameters['protocol'],
+ annotated_images=True,
+ imagedir=root_folder),
+ key=lambda x: x.id)
+
+ return [ Entry(x.alignment_annotations(directory=root_folder),
+ x.roi_annotations(directory=root_folder),
+ x.vein_annotations(directory=root_folder),
+ x.make_path(root_folder, '.png'))
+ for x in objs ]
+
+
+ def get(self, output, index):
+ obj = self.objs[index]
+
+ if output == 'alignment_annotations':
+ return {
+ 'value': construct_alignment_annotations(obj.alignment_annotations)
+ }
+
+ elif output == 'ROI_annotations':
+ return {
+ 'value': construct_ROI_image(obj.ROI_annotations)
+ }
+
+ elif output == 'vein_annotations':
+ return {
+ 'value': construct_vein_image(obj.vein_annotations)
+ }
+
+ elif output == 'image':
+ return {
+ 'value': bob.io.base.load(obj.image)
+ }
+
+
+#----------------------------------------------------------
+
+
+def setup_tests():
+ # Install a mock methods
+ def mock_load(root_folder):
+ return np.ndarray((10, 20), dtype=np.uint8)
+
+ bob.io.base.load = mock_load
+
+
+#----------------------------------------------------------
+
+
+# Test the behavior of the views (on fake data)
+if __name__ == '__main__':
+
+ setup_tests()
+
+ view = View()
+ view.objs = view.index(
+ root_folder='',
+ parameters=dict(
+ protocol="Idiap_1_1_R_BEAT_test",
+ group="world",
+ )
+ )
+ view.get('client_id', 0)
+ view.get('image', 0)
+
+
+ view = TemplateView()
+ view.objs = view.index(
+ root_folder='',
+ parameters=dict(
+ protocol="Idiap_1_1_R_BEAT_test",
+ group="dev",
+ purpose="enroll",
+ )
+ )
+ view.get('client_id', 0)
+ view.get('model_id', 0)
+ view.get('image', 0)
diff --git a/advanced/databases/biowave/4.rst b/advanced/databases/biowave/4.rst
new file mode 100644
index 0000000000000000000000000000000000000000..67429868f7d24aa105e309da653dea9a24c0ffbd
--- /dev/null
+++ b/advanced/databases/biowave/4.rst
@@ -0,0 +1 @@
+BIOWAVE Vein Database
\ No newline at end of file