Initial implementation of a PoseTraining Group

spec/ndx-pose.extensions.yaml

@@ -1,4 +1,33 @@
 groups:
+- neurodata_type_def: Skeleton
+  neurodata_type_inc: NWBDataInterface
+  default_name: Skeleton
+  doc: Group that holds node and edge data for defining parts of a pose and their
+    connections to one another.
+  attributes:
+  - name: id
+    dtype: text
+    doc: Unique ID associated with the skeleton.
+  datasets:
+  - name: nodes
+    dtype: text
+    dims:
+    - num_body_parts
+    shape:
+    - null
+    doc: Array of body part names corresponding to the names of the PoseEstimationSeries
+      objects or PoseTraining objects.
+  - name: edges
+    dtype: uint8
+    dims:
+    - num_edges
+    - nodes_index, nodes_index
+    shape:
+    - null
+    - 2
+    doc: Array of pairs of indices corresponding to edges between nodes. Index values
+      correspond to row indices of the 'nodes' dataset. Index values use 0-indexing.
+    quantity: '?'
 - neurodata_type_def: PoseEstimationSeries
   neurodata_type_inc: SpatialSeries
   doc: Estimated position (x, y) or (x, y, z) of a body part over time.
@@ -92,27 +121,88 @@ groups:
       dtype: text
       doc: Version string of the software tool used.
       required: false
-  - name: nodes
+  groups:
+  - neurodata_type_inc: PoseEstimationSeries
+    doc: Estimated position data for each body part.
+    quantity: '*'
+  links:
+  - target_type: Skeleton
+    doc: Layout of body part locations and connections.
+- neurodata_type_def: TrainingFrame
+  neurodata_type_inc: NWBDataInterface
+  default_name: TrainingFrame
+  doc: Group that holds ground-truth position data for all instances of a skeleton in a single frame.
+  attributes:
+  - name: annotator
     dtype: text
-    dims:
-    - num_body_parts
-    shape:
-    - null
-    doc: Array of body part names corresponding to the names of the PoseEstimationSeries
-      objects within this group.
+    doc: Name of annotator who labeled the TrainingFrame.
+    required: false
+  groups:
+  - neurodata_type_inc: Instance
+    doc: Position data for a single instance of a skeleton in a single training frame.
+    quantity: '*'
+  - name: source_video
+    neurodata_type_inc: ImageSeries
+    doc: Path to original video file and frame used.
     quantity: '?'
-  - name: edges
+    attributes:
+    - name: frame_index
+      dtype: uint8
+      doc: Frame index of TrainingFrame in original video file.
+      required: true
+  - name: source_frame
+    neurodata_type_inc: Images
+    doc: Collection of images used for training (stored internally or externally).
+    quantity: 1
+    attributes:
+    - name: images_index
+      dtype: uint8
+      doc: Index of TrainingFrame in collection of frames stored in Images.
+      required: true
+- neurodata_type_def: Instance
+  neurodata_type_inc: NWBDataInterface
+  default_name: Instance
+  doc: Group that holds ground-truth pose data for single subject in a single frame.
+  attributes:
+  - name: id
     dtype: uint8
+    doc: ID used to differentiate instances.
+    required: false
+  datasets:
+  - name: node_locations
+    dtype: float
     dims:
-    - num_edges
-    - nodes_index, nodes_index
+    - - num_body_parts
+      - x, y
+    - - num_body_parts
+      - x, y, z
+    shape:
+    - - null
+      - 2
+    - - null
+      - 3
+    doc: Locations (x, y) or (x, y, z) of nodes for single skeleton instance in single frame.
+  - name: node_visibility
+    dtype: bool
+    dims:
+    - num_body_parts
     shape:
     - null
-    - 2
-    doc: Array of pairs of indices corresponding to edges between nodes. Index values
-      correspond to row indices of the 'nodes' dataset. Index values use 0-indexing.
+    doc: Markers for node visibility where true corresponds to a visible node and
+      false corresponds to an occluded node.
     quantity: '?'
+  links:
+  - target_type: Skeleton
+    doc: Layout of body part locations and connections.
+- neurodata_type_def: PoseTraining
+  neurodata_type_inc: NWBDataInterface
+  default_name: PoseTraining
+  doc: Group that holds images, ground-truth annotations, and metadata for training
+    a pose estimator.
   groups:
-  - neurodata_type_inc: PoseEstimationSeries
-    doc: Estimated position data for each body part.
+  - neurodata_type_inc: Skeleton
+    doc: Skeleton used in project where each skeleton corresponds to a unique morphology.
+    quantity: '*'
+  - neurodata_type_inc: TrainingFrame
+    doc: Frames and ground-truth annotations for training a pose estimator.
     quantity: '*'

spec/ndx-pose.namespace.yaml

@@ -3,10 +3,14 @@ namespaces:
   - Ryan Ly
   - Ben Dichter
   - Alexander Mathis
+  - Liezl Maree
+  - Chris Brozdowski
   contact:
   - rly@lbl.gov
   - bdichter@lbl.gov
   - alexander.mathis@epfl.ch
+  - lmaree@salk.edu
+  - cbroz@datajoint.com
   doc: NWB extension to store pose estimation data
   name: ndx-pose
   schema:

src/spec/create_extension_spec.py

@@ -10,13 +10,47 @@ def main():
         doc='NWB extension to store pose estimation data',
         name='ndx-pose',
         version='0.1.1',
-        author=['Ryan Ly', 'Ben Dichter', 'Alexander Mathis'],
-        contact=['rly@lbl.gov', 'bdichter@lbl.gov', 'alexander.mathis@epfl.ch'],
+        author=['Ryan Ly', 'Ben Dichter', 'Alexander Mathis', 'Liezl Maree', 'Chris Brozdowski'],
+        contact=['rly@lbl.gov', 'bdichter@lbl.gov', 'alexander.mathis@epfl.ch', 'lmaree@salk.edu', 'cbroz@datajoint.com'],
     )
 
     ns_builder.include_type('SpatialSeries', namespace='core')
     ns_builder.include_type('NWBDataInterface', namespace='core')
 
+    skeleton = NWBGroupSpec(
+        neurodata_type_def='Skeleton',
+        neurodata_type_inc='NWBDataInterface',
+        doc='Group that holds node and edge data for defining parts of a pose and their connections to one another.',
+        default_name='Skeleton',
+        attributes=[
+            NWBAttributeSpec(
+                name='id',
+                doc='Unique ID associated with the skeleton.',
+                dtype='text',
+            ),
+        ],
+        datasets=[
+            NWBDatasetSpec(
+                name='nodes',
+                doc=('Array of body part names corresponding to the names of the PoseEstimationSeries objects or '
+                     'PoseTraining objects.'),
+                dtype='text',
+                dims=['num_body_parts'],
+                shape=[None],
+                quantity=1,
+            ),
+            NWBDatasetSpec(
+                name='edges',
+                doc=("Array of pairs of indices corresponding to edges between nodes. Index values correspond to row "
+                     "indices of the 'nodes' dataset. Index values use 0-indexing."),
+                dtype='uint8',
+                dims=['num_edges', 'nodes_index, nodes_index'],
+                shape=[None, 2],
+                quantity='?',
+            ),
+        ]
+    )
+
     pose_estimation_series = NWBGroupSpec(
         neurodata_type_def='PoseEstimationSeries',
         neurodata_type_inc='SpatialSeries',
@@ -72,6 +106,13 @@ def main():
                 quantity='*',
             ),
         ],
+        links=[
+            NWBLinkSpec(
+                doc='Layout of body part locations and connections.',
+                target_type='Skeleton',
+                quantity=1
+            ),
+        ],
         datasets=[
             NWBDatasetSpec(
                 name='description',
@@ -123,24 +164,6 @@ def main():
                     ),
                 ],
             ),
-            NWBDatasetSpec(
-                name='nodes',
-                doc=('Array of body part names corresponding to the names of the PoseEstimationSeries objects within '
-                     'this group.'),
-                dtype='text',
-                dims=['num_body_parts'],
-                shape=[None],
-                quantity='?',
-            ),
-            NWBDatasetSpec(
-                name='edges',
-                doc=("Array of pairs of indices corresponding to edges between nodes. Index values correspond to row "
-                     "indices of the 'nodes' dataset. Index values use 0-indexing."),
-                dtype='uint8',
-                dims=['num_edges', 'nodes_index, nodes_index'],
-                shape=[None, 2],
-                quantity='?',
-            ),
         ],
         # TODO: collections of multiple links is currently buggy in PyNWB/HDMF
         # links=[
@@ -152,7 +175,114 @@ def main():
         # ],
     )
 
-    new_data_types = [pose_estimation_series, pose_estimation]
+    training_frame = NWBGroupSpec(
+        neurodata_type_def='TrainingFrame',
+        neurodata_type_inc='NWBDataInterface',
+        doc='Group that holds ground-truth position data for all instances of a skeleton in a single frame.',
+        default_name='TrainingFrame',
+        groups=[
+            NWBGroupSpec(
+                neurodata_type_inc='Instance',
+                doc='Position data for a single instance of a skeleton in a single training frame.',
+                quantity='*',
+            ),
+            NWBGroupSpec(
+                name='source_video',
+                doc='Path to original video file and frame used.',
+                quantity='?',
+                attributes=[
+                    NWBAttributeSpec(
+                        name='path',
+                        doc='Path to original video file.',
+                        dtype='text',
+                        required=False,
+                    ),
+                    NWBAttributeSpec(
+                        name='frame_index',
+                        doc='Frame index of TrainingFrame in original video file.',
+                        dtype='uint8',
+                        required=False,
+                    ),
+                ],
+            ),
+            NWBGroupSpec(
+                neurodata_type_inc='Image',
+                name='source_frame',
+                doc='Image frame used for training (stored either internally or externally).',
+                quantity='1',
+            ),
+        ],
+        attributes=[
+            NWBAttributeSpec(
+                name='annotator',
+                doc='Name of annotator who labeled the TrainingFrame.',
+                dtype='text',
+                required=False,
+            ),
+        ],
+    )
+
+    instance = NWBGroupSpec(
+        neurodata_type_def='Instance',
+        neurodata_type_inc='NWBDataInterface',
+        doc='Group that holds ground-truth pose data for a single instance of a skeleton in a single frame.',
+        default_name='Instance',
+        links=[
+            NWBLinkSpec(
+                doc='Layout of body part locations and connections.',
+                target_type='Skeleton',
+                quantity=1
+            ),
+        ],
+        attributes=[
+            NWBAttributeSpec(
+                name='id',
+                doc='ID used to differentiate skeleton instances.',
+                dtype='uint8',
+                required=False,
+            ),
+        ],
+        datasets=[
+            NWBDatasetSpec(
+                name='node_locations',
+                doc=('Locations (x, y) or (x, y, z) of nodes for single instance in single frame.'),
+                dtype='float',
+                dims=[['num_body_parts', 'x, y'], ['num_body_parts', 'x, y, z']],
+                shape=[[None, 2], [None, 3]],
+                quantity=1,
+            ),
+            NWBDatasetSpec(
+                name='node_visibility',
+                doc=('Markers for node visibility where true corresponds to a visible node and false corresponds to '
+                'an occluded node.'),
+                dtype='bool',
+                dims=['num_body_parts'],
+                shape=[None],
+                quantity='?',
+            ),
+        ],
+    )
+
+    pose_training = NWBGroupSpec(
+        neurodata_type_def='PoseTraining',
+        neurodata_type_inc='NWBDataInterface',
+        doc='Group that holds images, ground-truth annotations, and metadata for training a pose estimator.',
+        default_name='PoseTraining',
+        groups=[
+            NWBGroupSpec(
+                neurodata_type_inc='Skeleton',
+                doc='Skeleton used in project where each skeleton corresponds to a unique morphology.',
+                quantity='*',
+            ),
+            NWBGroupSpec(
+                neurodata_type_inc='TrainingFrame',
+                doc='Frames and ground-truth annotations for training a pose estimator.',
+                quantity='*',
+            ),
+        ],
+    )
+
+    new_data_types = [skeleton, pose_estimation_series, pose_estimation, training_frame, instance, pose_training]
 
     # export the spec to yaml files in the spec folder
     output_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..', 'spec'))