Limit max tracks via track-local queues

sleap/config/pipeline_form.yaml

@@ -376,28 +376,39 @@ inference:
   none:
 
   flow:
-    - type: text
-      text: '<b>Pre-tracker data cleaning</b>:'
-    - name: tracking.target_instance_count
-      label: Target Number of Instances Per Frame
-      type: optional_int
-      none_label: No target
-      default_disabled: true
-      range: 1,100
-      default: 1
-    - name: tracking.pre_cull_to_target
-      label: Cull to Target Instance Count
-      type: bool
-      default: false
-    - name: tracking.pre_cull_iou_threshold
-      label: Cull using IoU Threshold
-      type: double
-      default: 0.8
+    # - type: text
+    #   text: '<b>Pre-tracker data cleaning</b>:'
+    # - name: tracking.target_instance_count
+    #   label: Target Number of Instances Per Frame
+    #   type: optional_int
+    #   none_label: No target
+    #   default_disabled: true
+    #   range: 1,100
+    #   default: 1
+    # - name: tracking.pre_cull_to_target
+    #   label: Cull to Target Instance Count
+    #   type: bool
+    #   default: false
+    # - name: tracking.pre_cull_iou_threshold
+    #   label: Cull using IoU Threshold
+    #   type: double
+    #   default: 0.8
     - type: text
       text: '<b>Tracking with optical flow</b>:<br />
       This tracker "shifts" instances from previous frames using optical flow
       before matching instances in each frame to the <i>shifted</i> instances from
       prior frames.'
+    # - name: tracking.max_tracking
+    #   label: Limit max number of tracks
+    #   type: bool
+      default: false
+    - name: tracking.max_tracks
+      label: Max number of tracks
+      type: optional_int
+      none_label: No limit
+      default_disabled: true
+      range: 1,100
+      default: 1
     - name: tracking.similarity
       label: Similarity Method
       type: list
@@ -422,10 +433,10 @@ inference:
       none_label: Use max (non-robust)
       range: 0,1
       default: 0.95
-    - name: tracking.save_shifted_instances
-      label: Save shifted instances
-      type: bool
-      default: false
+    # - name: tracking.save_shifted_instances
+    #   label: Save shifted instances
+    #   type: bool
+    #   default: false
     - type: text
       text: '<b>Kalman filter-based tracking</b>:<br />
       Uses the above tracking options to track instances for an initial
@@ -449,27 +460,38 @@ inference:
       default: false
 
   simple:
+    # - type: text
+    #   text: '<b>Pre-tracker data cleaning</b>:'
+    # - name: tracking.target_instance_count
+    #   label: Target Number of Instances Per Frame
+    #   type: optional_int
+    #   none_label: No target
+    #   default_disabled: true
+    #   range: 1,100
+    #   default: 1
+    # - name: tracking.pre_cull_to_target
+    #   label: Cull to Target Instance Count
+    #   type: bool
+    #   default: false
+    # - name: tracking.pre_cull_iou_threshold
+    #   label: Cull using IoU Threshold
+    #   type: double
+    #   default: 0.8
     - type: text
-      text: '<b>Pre-tracker data cleaning</b>:'
-    - name: tracking.target_instance_count
-      label: Target Number of Instances Per Frame
+      text: '<b>Tracking</b>:<br />
+        This tracker assigns track identities by matching instances from prior
+        frames to instances on subsequent frames.'
+    # - name: tracking.max_tracking
+    #   label: Limit max number of tracks
+    #   type: bool
+    #   default: false
+    - name: tracking.max_tracks
+      label: Max number of tracks
       type: optional_int
-      none_label: No target
+      none_label: No limit
       default_disabled: true
       range: 1,100
       default: 1
-    - name: tracking.pre_cull_to_target
-      label: Cull to Target Instance Count
-      type: bool
-      default: false
-    - name: tracking.pre_cull_iou_threshold
-      label: Cull using IoU Threshold
-      type: double
-      default: 0.8
-    - type: text
-      text: '<b>Tracking</b>:<br />
-        This tracker assigns track identities by matching instances from prior
-        frames to instances on subsequent frames.'
     - name: tracking.similarity
       label: Similarity Method
       type: list

sleap/gui/learning/runners.py

@@ -224,6 +224,7 @@ def make_predict_cli_call(
 
         optional_items_as_nones = (
             "tracking.target_instance_count",
+            "tracking.max_tracks",
             "tracking.kf_init_frame_count",
             "tracking.robust",
             "max_instances",
@@ -233,6 +234,16 @@ def make_predict_cli_call(
             if key in self.inference_params and self.inference_params[key] is None:
                 del self.inference_params[key]
 
+        # Setting max_tracks to True means we want to use the max_tracking mode.
+        if "tracking.max_tracks" in self.inference_params:
+            self.inference_params["tracking.max_tracking"] = True
+
+            # Hacky:  Update the tracker name to include "maxtracks" suffix.
+            if self.inference_params["tracking.tracker"] in ("simple", "flow"):
+                self.inference_params["tracking.tracker"] = (
+                    self.inference_params["tracking.tracker"] + "maxtracks"
+                )
+
         # --tracking.kf_init_frame_count enables the kalman filter tracking
         # so if not set, then remove other (unused) args
         if "tracking.kf_init_frame_count" not in self.inference_params:
@@ -241,6 +252,7 @@ def make_predict_cli_call(
 
         bool_items_as_ints = (
             "tracking.pre_cull_to_target",
+            "tracking.max_tracking",
             "tracking.post_connect_single_breaks",
             "tracking.save_shifted_instances",
         )

sleap/nn/inference.py

@@ -68,7 +68,7 @@
 )
 from sleap.nn.utils import reset_input_layer
 from sleap.io.dataset import Labels
-from sleap.util import frame_list
+from sleap.util import frame_list, make_scoped_dictionary
 from sleap.instance import PredictedInstance, LabeledFrame
 
 from tensorflow.python.framework.convert_to_constants import (
@@ -4773,8 +4773,7 @@ def load_model(
             be performed.
         tracker_window: Number of frames of history to use when tracking. No effect when
             `tracker` is `None`.
-        tracker_max_instances: If not `None`, discard instances beyond this count when
-            tracking. No effect when `tracker` is `None`.
+        tracker_max_instances: If not `None`, create at most this many tracks.
         disable_gpu_preallocation: If `True` (the default), initialize the GPU and
             disable preallocation of memory. This is necessary to prevent freezing on
             some systems with low GPU memory and has negligible impact on performance.
@@ -4863,11 +4862,18 @@ def unpack_sleap_model(model_path):
     )
     predictor.verbosity = progress_reporting
     if tracker is not None:
+        use_max_tracker = tracker_max_instances is not None
+        if use_max_tracker and not tracker.endswith("maxtracks"):
+            # Append maxtracks to the tracker name to use the right tracker variants.
+            tracker += "maxtracks"
+
         predictor.tracker = Tracker.make_tracker_by_name(
             tracker=tracker,
             track_window=tracker_window,
             post_connect_single_breaks=True,
-            clean_instance_count=tracker_max_instances,
+            max_tracking=use_max_tracker,
+            max_tracks=tracker_max_instances,
+            # clean_instance_count=tracker_max_instances,
         )
 
     # Remove temp dirs.
@@ -5335,7 +5341,7 @@ def _make_tracker_from_cli(args: argparse.Namespace) -> Optional[Tracker]:
     Returns:
         An instance of `Tracker` or `None` if tracking method was not specified.
     """
-    policy_args = sleap.util.make_scoped_dictionary(vars(args), exclude_nones=True)
+    policy_args = make_scoped_dictionary(vars(args), exclude_nones=True)
     if "tracking" in policy_args:
         tracker = Tracker.make_tracker_by_name(**policy_args["tracking"])
         return tracker