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Commit dd4a6679 authored by Samuel GAIST's avatar Samuel GAIST
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[advanced][databases][biowave] Add new version following V2 implementation

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advanced/databases/biowave/4.json 0 → 100644
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{
"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
advanced/databases/biowave/4.py 0 → 100644
+ 497
− 0
View file @ dd4a6679
###############################################################################
# #
# 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)
advanced/databases/biowave/4.rst 0 → 100644
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View file @ dd4a6679
BIOWAVE Vein Database
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