[advanced][databases][xm2vts] Add new version following V2 implementation

advanced/databases/xm2vts/5.json

+{
+    "description": "The XM2VTS Database of Faces",
+    "root_folder": "/idiap/resource/database/xm2vtsdb/images",
+    "protocols": [
+        {
+            "name": "lp1",
+            "template": "advanced_face_recognition/1",
+            "views": {
+                "train": {
+                    "view": "Train",
+                    "parameters": {
+                        "protocol": "lp1"
+                    }
+                },
+                "dev_templates": {
+                    "view": "Templates",
+                    "parameters": {
+                        "protocol": "lp1",
+                        "group": "dev"
+                    }
+                },
+                "dev_probes": {
+                    "view": "Probes",
+                    "parameters": {
+                        "protocol": "lp1",
+                        "group": "dev"
+                    }
+                },
+                "test_templates": {
+                    "view": "Templates",
+                    "parameters": {
+                        "protocol": "lp1",
+                        "group": "eval"
+                    }
+                },
+                "test_probes": {
+                    "view": "Probes",
+                    "parameters": {
+                        "protocol": "lp1",
+                        "group": "eval"
+                    }
+                }
+            }
+        },
+        {
+            "name": "lp2",
+            "template": "advanced_face_recognition/1",
+            "views": {
+                "train": {
+                    "view": "Train",
+                    "parameters": {
+                        "protocol": "lp2"
+                    }
+                },
+                "dev_templates": {
+                    "view": "Templates",
+                    "parameters": {
+                        "protocol": "lp2",
+                        "group": "dev"
+                    }
+                },
+                "dev_probes": {
+                    "view": "Probes",
+                    "parameters": {
+                        "protocol": "lp2",
+                        "group": "dev"
+                    }
+                },
+                "test_templates": {
+                    "view": "Templates",
+                    "parameters": {
+                        "protocol": "lp2",
+                        "group": "eval"
+                    }
+                },
+                "test_probes": {
+                    "view": "Probes",
+                    "parameters": {
+                        "protocol": "lp2",
+                        "group": "eval"
+                    }
+                }
+            }
+        },
+        {
+            "name": "darkened-lp1",
+            "template": "advanced_face_recognition/1",
+            "views": {
+                "train": {
+                    "view": "Train",
+                    "parameters": {
+                        "protocol": "darkened-lp1"
+                    }
+                },
+                "dev_templates": {
+                    "view": "Templates",
+                    "parameters": {
+                        "protocol": "darkened-lp1",
+                        "group": "dev"
+                    }
+                },
+                "dev_probes": {
+                    "view": "Probes",
+                    "parameters": {
+                        "protocol": "darkened-lp1",
+                        "group": "dev"
+                    }
+                },
+                "test_templates": {
+                    "view": "Templates",
+                    "parameters": {
+                        "protocol": "darkened-lp1",
+                        "group": "eval"
+                    }
+                },
+                "test_probes": {
+                    "view": "Probes",
+                    "parameters": {
+                        "protocol": "darkened-lp1",
+                        "group": "eval"
+                    }
+                }
+            }
+        },
+        {
+            "name": "darkened-lp2",
+            "template": "advanced_face_recognition/1",
+            "views": {
+                "train": {
+                    "view": "Train",
+                    "parameters": {
+                        "protocol": "darkened-lp2"
+                    }
+                },
+                "dev_templates": {
+                    "view": "Templates",
+                    "parameters": {
+                        "protocol": "darkened-lp2",
+                        "group": "dev"
+                    }
+                },
+                "dev_probes": {
+                    "view": "Probes",
+                    "parameters": {
+                        "protocol": "darkened-lp2",
+                        "group": "dev"
+                    }
+                },
+                "test_templates": {
+                    "view": "Templates",
+                    "parameters": {
+                        "protocol": "darkened-lp2",
+                        "group": "eval"
+                    }
+                },
+                "test_probes": {
+                    "view": "Probes",
+                    "parameters": {
+                        "protocol": "darkened-lp2",
+                        "group": "eval"
+                    }
+                }
+            }
+        }
+    ],
+    "schema_version": 2
+}
\ No newline at end of file

advanced/databases/xm2vts/5.py

+###############################################################################
+#                                                                             #
+# 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 numpy as np
+from collections import namedtuple
+
+from beat.backend.python.database import View
+
+import bob.io.base
+import bob.io.image
+import bob.db.xm2vts
+
+
+#----------------------------------------------------------
+
+
+class Train(View):
+    """Outputs:
+        - image: "{{ system_user.username }}/array_3d_uint8/1"
+        - eye_centers: "{{ system_user.username }}/eye_positions/1"
+        - file_id: "{{ system_user.username }}/uint64/1"
+        - client_id: "{{ system_user.username }}/uint64/1"
+
+    One "file_id" is associated with a given "image".
+    One "eye_centers" is associated with a given "image".
+    Several "image" are associated with a given "client_id".
+
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    |    image    | |    image    | |    image    | |    image    | |    image    | |    image    |
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    | eye_centers | | eye_centers | | eye_centers | | eye_centers | | eye_centers | | eye_centers |
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    |   file_id   | |   file_id   | |   file_id   | |   file_id   | |   file_id   | |   file_id   |
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    ----------------------------------------------- -----------------------------------------------
+    |                   client_id                 | |                   client_id                 |
+    ----------------------------------------------- -----------------------------------------------
+    """
+
+    def index(self, root_folder, parameters):
+        Entry = namedtuple('Entry', ['client_id', 'file_id', 'eye_centers', 'image'])
+
+        # Open the database and load the objects to provide via the outputs
+        db = bob.db.xm2vts.Database()
+
+        objs = sorted(db.objects(protocol=parameters['protocol'],
+                                 groups='world'),
+                      key=lambda x: (x.client_id, x.id))
+
+        return [ Entry(x.client_id, x.id, db.annotations(x), x.make_path(root_folder, '.ppm'))
+                 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 == 'file_id':
+            return {
+                'value': np.uint64(obj.file_id)
+            }
+
+        elif output == 'eye_centers':
+            return {
+                'left': {
+                    'y': np.int32(obj.eye_centers['leye'][0]),
+                    'x': np.int32(obj.eye_centers['leye'][1]),
+                },
+                'right': {
+                    'y': np.int32(obj.eye_centers['reye'][0]),
+                    'x': np.int32(obj.eye_centers['reye'][1]),
+                }
+            }
+
+        elif output == 'image':
+            return {
+                'value': bob.io.base.load(obj.image)
+            }
+
+
+#----------------------------------------------------------
+
+
+class Templates(View):
+    """Outputs:
+        - image: "{{ system_user.username }}/array_3d_uint8/1"
+        - eye_centers: "{{ system_user.username }}/eye_positions/1"
+        - file_id: "{{ system_user.username }}/uint64/1"
+        - template_id: "{{ system_user.username }}/uint64/1"
+        - client_id: "{{ system_user.username }}/uint64/1"
+
+    One "file_id" is associated with a given "image".
+    One "eye_centers" is associated with a given "image".
+    Several "image" are associated with a given "template_id".
+    Several "template_id" are associated with a given "client_id".
+
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    |    image    | |    image    | |    image    | |    image    | |    image    | |    image    |
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    | eye_centers | | eye_centers | | eye_centers | | eye_centers | | eye_centers | | eye_centers |
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    |   file_id   | |   file_id   | |   file_id   | |   file_id   | |   file_id   | |   file_id   |
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    ----------------------------------------------- -----------------------------------------------
+    |                  template_id                | |                  template_id                |
+    ----------------------------------------------- -----------------------------------------------
+    -----------------------------------------------------------------------------------------------
+    |                                          client_id                                          |
+    -----------------------------------------------------------------------------------------------
+
+    Note: for this particular database, there is only one "template_id"
+    per "client_id".
+    """
+
+    def index(self, root_folder, parameters):
+        Entry = namedtuple('Entry', ['client_id', 'template_id', 'file_id', 'eye_centers', 'image'])
+
+        # Open the database and load the objects to provide via the outputs
+        db = bob.db.xm2vts.Database()
+
+        template_ids = db.model_ids(protocol=parameters['protocol'],
+                                    groups=parameters['group'])
+
+        entries = []
+
+        for template_id in template_ids:
+            objs = db.objects(protocol=parameters['protocol'],
+                              groups=parameters['group'],
+                              purposes='enroll',
+                              model_ids=[template_id])
+
+            entries.extend([ Entry(x.client_id, template_id, x.id, db.annotations(x),
+                                   x.make_path(root_folder, '.ppm'))
+                             for x in objs ])
+
+        return sorted(entries, key=lambda x: (x.client_id, x.template_id, x.file_id))
+
+
+    def get(self, output, index):
+        obj = self.objs[index]
+
+        if output == 'client_id':
+            return {
+                'value': np.uint64(obj.client_id)
+            }
+
+        elif output == 'template_id':
+            return {
+                'value': np.uint64(obj.template_id)
+            }
+
+        elif output == 'file_id':
+            return {
+                'value': np.uint64(obj.file_id)
+            }
+
+        elif output == 'eye_centers':
+            return {
+                'left': {
+                    'y': np.int32(obj.eye_centers['leye'][0]),
+                    'x': np.int32(obj.eye_centers['leye'][1]),
+                },
+                'right': {
+                    'y': np.int32(obj.eye_centers['reye'][0]),
+                    'x': np.int32(obj.eye_centers['reye'][1]),
+                }
+            }
+
+        elif output == 'image':
+            return {
+                'value': bob.io.base.load(obj.image)
+            }
+
+
+#----------------------------------------------------------
+
+
+class Probes(View):
+    """Outputs:
+        - image: "{{ system_user.username }}/array_3d_uint8/1"
+        - eye_centers: "{{ system_user.username }}/eye_positions/1"
+        - file_id: "{{ system_user.username }}/uint64/1"
+        - probe_id: "{{ system_user.username }}/uint64/1"
+        - client_id: "{{ system_user.username }}/uint64/1"
+        - template_ids: "{{ system_user.username }}/array_1d_uint64/1"
+
+    One "file_id" is associated with a given "image".
+    One "eye_centers" is associated with a given "image".
+    One "probe_id" is associated with a given "image".
+    Several "image" are associated with a given "client_id".
+    Several "client_id" are associated with a given "template_ids".
+
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    |    image    | |    image    | |    image    | |    image    | |    image    | |    image    |
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    | eye_centers | | eye_centers | | eye_centers | | eye_centers | | eye_centers | | eye_centers |
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    |   file_id   | |   file_id   | |   file_id   | |   file_id   | |   file_id   | |   file_id   |
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    |   probe_id  | |   probe_id  | |   probe_id  | |   probe_id  | |   probe_id  | |   probe_id  |
+    --------------- --------------- --------------- --------------- --------------- ---------------
+    ----------------------------------------------- -----------------------------------------------
+    |                   client_id                 | |                   client_id                 |
+    ----------------------------------------------- -----------------------------------------------
+    -----------------------------------------------------------------------------------------------
+    |                                        template_ids                                         |
+    -----------------------------------------------------------------------------------------------
+    """
+
+    def index(self, root_folder, parameters):
+        Entry = namedtuple('Entry', ['template_ids', 'client_id', 'probe_id', 'file_id',
+                                     'eye_centers', 'image'])
+
+        # Open the database and load the objects to provide via the outputs
+        db = bob.db.xm2vts.Database()
+
+        template_ids = sorted(db.model_ids(protocol=parameters['protocol'],
+                                           groups=parameters['group']))
+
+
+        template_probes = {}
+        for template_id in template_ids:
+            objs = sorted(db.objects(protocol=parameters['protocol'],
+                                     groups=parameters['group'],
+                                     purposes='probe',
+                                     model_ids=[template_id]),
+                           key=lambda x: (x.client_id, x.id))
+
+            template_probes[template_id] = [ p.id for p in objs ]
+
+
+        objs = sorted(db.objects(protocol=parameters['protocol'],
+                                 groups=parameters['group'],
+                                 purposes='probe'),
+                      key=lambda x: (x.client_id, x.id))
+
+        entries = []
+        for obj in objs:
+            templates = [ template_id for template_id in template_ids
+                                      if obj.id in template_probes[template_id] ]
+
+            entries.append( Entry(templates, obj.client_id, obj.id, obj.id,
+                                  db.annotations(obj), obj.make_path(root_folder, '.ppm')) )
+
+        return sorted(entries, key=lambda x: (len(x.template_ids), x.template_ids,
+                                              x.client_id, x.probe_id))
+
+
+    def get(self, output, index):
+        obj = self.objs[index]
+
+        if output == 'template_ids':
+            return {
+                'value': np.uint64(obj.template_ids)
+            }
+
+        elif output == 'client_id':
+            return {
+                'value': np.uint64(obj.client_id)
+            }
+
+        elif output == 'probe_id':
+            return {
+                'value': np.uint64(obj.probe_id)
+            }
+
+        elif output == 'file_id':
+            return {
+                'value': np.uint64(obj.file_id)
+            }
+
+        elif output == 'eye_centers':
+            return {
+                'left': {
+                    'y': np.int32(obj.eye_centers['leye'][0]),
+                    'x': np.int32(obj.eye_centers['leye'][1]),
+                },
+                'right': {
+                    'y': np.int32(obj.eye_centers['reye'][0]),
+                    'x': np.int32(obj.eye_centers['reye'][1]),
+                }
+            }
+
+        elif output == 'image':
+            return {
+                'value': bob.io.base.load(obj.image)
+            }
+
+
+#----------------------------------------------------------
+
+
+def setup_tests():
+    # Install a mock load function for the images
+    def mock_load(root_folder):
+        return np.ndarray((3, 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 = Train()
+    view.objs = view.index(
+        root_folder='',
+        parameters=dict(
+            protocol='lp1',
+        )
+    )
+    view.get('client_id', 0)
+    view.get('file_id', 0)
+    view.get('eye_centers', 0)
+    view.get('image', 0)
+
+
+    view = Templates()
+    view.objs = view.index(
+        root_folder='',
+        parameters=dict(
+            protocol='lp1',
+            group='dev',
+        )
+    )
+    view.get('client_id', 0)
+    view.get('template_id', 0)
+    view.get('file_id', 0)
+    view.get('eye_centers', 0)
+    view.get('image', 0)
+
+
+    view = Probes()
+    view.objs = view.index(
+        root_folder='',
+        parameters=dict(
+            protocol='lp1',
+            group='dev',
+        )
+    )
+    view.get('template_ids', 0)
+    view.get('client_id', 0)
+    view.get('probe_id', 0)
+    view.get('file_id', 0)
+    view.get('eye_centers', 0)
+    view.get('image', 0)

advanced/databases/xm2vts/5.rst

+The XM2VTS Database of Faces
\ No newline at end of file