simplify max_tracks tracker

docs/guides/cli.md

@@ -36,7 +36,7 @@ optional arguments:
 
 ```none
 usage: sleap-train [-h] [--video-paths VIDEO_PATHS] [--val_labels VAL_LABELS]
-                   [--test_labels TEST_LABELS] [--tensorboard] [--save_viz] 
+                   [--test_labels TEST_LABELS] [--tensorboard] [--save_viz]
                    [--keep_viz] [--zmq] [--run_name RUN_NAME] [--prefix PREFIX]
                    [--suffix SUFFIX]
                    training_job_path [labels_path]
@@ -124,7 +124,7 @@ usage: sleap-track [-h] [-m MODELS] [--frames FRAMES] [--only-labeled-frames] [-
                    [--verbosity {none,rich,json}] [--video.dataset VIDEO.DATASET] [--video.input_format VIDEO.INPUT_FORMAT]
                    [--video.index VIDEO.INDEX] [--cpu | --first-gpu | --last-gpu | --gpu GPU] [--max_edge_length_ratio MAX_EDGE_LENGTH_RATIO]
                    [--dist_penalty_weight DIST_PENALTY_WEIGHT] [--batch_size BATCH_SIZE] [--open-in-gui] [--peak_threshold PEAK_THRESHOLD]
-                   [-n MAX_INSTANCES] [--tracking.tracker TRACKING.TRACKER] [--tracking.max_tracking TRACKING.MAX_TRACKING]
+                   [-n MAX_INSTANCES] [--tracking.tracker TRACKING.TRACKER]
                    [--tracking.max_tracks TRACKING.MAX_TRACKS] [--tracking.target_instance_count TRACKING.TARGET_INSTANCE_COUNT]
                    [--tracking.pre_cull_to_target TRACKING.PRE_CULL_TO_TARGET] [--tracking.pre_cull_iou_threshold TRACKING.PRE_CULL_IOU_THRESHOLD]
                    [--tracking.post_connect_single_breaks TRACKING.POST_CONNECT_SINGLE_BREAKS]
@@ -187,10 +187,8 @@ optional arguments:
                         Limit maximum number of instances in multi-instance models. Not available for ID models. Defaults to None.
   --tracking.tracker TRACKING.TRACKER
                         Options: simple, flow, simplemaxtracks, flowmaxtracks, None (default: None)
-  --tracking.max_tracking TRACKING.MAX_TRACKING
-                        If true then the tracker will cap the max number of tracks. (default: False)
   --tracking.max_tracks TRACKING.MAX_TRACKS
-                        Maximum number of tracks to be tracked by the tracker. (default: None)
+                        Maximum number of tracks to be tracked by the tracker. No limit if None or -1. (default: None)
   --tracking.target_instance_count TRACKING.TARGET_INSTANCE_COUNT
                         Target number of instances to track per frame. (default: 0)
   --tracking.pre_cull_to_target TRACKING.PRE_CULL_TO_TARGET
@@ -264,13 +262,13 @@ sleap-track -m "models/my_model" --tracking.tracker simple -o "output_prediction
 **5. Inference with max tracks limit:**
 
 ```none
-sleap-track -m "models/my_model" --tracking.tracker simplemaxtracks --tracking.max_tracking 1 --tracking.max_tracks 4 -o "output_predictions.slp" "input_video.mp4"
+sleap-track -m "models/my_model" --tracking.tracker simple --tracking.max_tracks 4 -o "output_predictions.slp" "input_video.mp4"
 ```
 
 **6. Re-tracking without pose inference:**
 
 ```none
-sleap-track --tracking.tracker simplemaxtracks --tracking.max_tracking 1 --tracking.max_tracks 4 -o "retracked.slp" "input_predictions.slp"
+sleap-track --tracking.tracker simple --tracking.max_tracks 4 -o "retracked.slp" "input_predictions.slp"
 ```
 
 **7. Select GPU for pose inference:**

sleap/config/pipeline_form.yaml

@@ -521,10 +521,6 @@ inference:
       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

sleap/gui/learning/runners.py

@@ -204,7 +204,6 @@ def make_predict_cli_call(
 
         # Make path where we'll save predictions (if not specified)
         if output_path is None:
-
             if self.labels_filename:
                 # Make a predictions directory next to the labels dataset file
                 predictions_dir = os.path.join(
@@ -239,15 +238,12 @@ 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"
-                )
+        # Compatibility with using the "maxtracks" suffix to the tracker name.
+        if "tracking.tracker" in self.inference_params:
+            compat_trackers = ("simplemaxtracks", "flowmaxtracks")
+            if self.inference_params["tracking.tracker"] in compat_trackers:
+                tname = self.inference_params["tracking.tracker"][: -len("maxtracks")]
+                self.inference_params["tracking.tracker"] = tname
 
         # --tracking.kf_init_frame_count enables the kalman filter tracking
         # so if not set, then remove other (unused) args
@@ -257,10 +253,11 @@ 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",
             "tracking.oks_score_weighting",
+            "tracking.prefer_reassigning_track",
+            "tracking.allow_reassigning_track",
         )
 
         for key in bool_items_as_ints:
@@ -303,10 +300,8 @@ def predict_subprocess(
 
         # Run inference CLI capturing output.
         with subprocess.Popen(cli_args, stdout=subprocess.PIPE) as proc:
-
             # Poll until finished.
             while proc.poll() is None:
-
                 # Read line.
                 line = proc.stdout.readline()
                 line = line.decode().rstrip()
@@ -635,7 +630,6 @@ def run_gui_training(
 
     for config_info in config_info_list:
         if config_info.dont_retrain:
-
             if not config_info.has_trained_model:
                 raise ValueError(
                     "Config is set to not retrain but no trained model found: "
@@ -849,7 +843,6 @@ def train_subprocess(
     success = False
 
     with tempfile.TemporaryDirectory() as temp_dir:
-
         # Write a temporary file of the TrainingJob so that we can respect
         # any changed made to the job attributes after it was loaded.
         temp_filename = datetime.now().strftime("%y%m%d_%H%M%S") + "_training_job.json"

sleap/nn/inference.py

@@ -4947,16 +4947,10 @@ 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,
-            max_tracking=use_max_tracker,
             max_tracks=tracker_max_instances,
             # clean_instance_count=tracker_max_instances,
         )