Add setup_trainer

crabs/tracker/track_video.py

@@ -7,6 +7,7 @@
 from pathlib import Path
 
 import cv2
+import lightning
 import numpy as np
 import torch
 import torchvision.transforms.v2 as transforms
@@ -16,6 +17,7 @@
 from crabs.detector.utils.detection import (
     log_mlflow_metadata_as_info,
     set_mlflow_run_name,
+    setup_mlflow_logger,
 )
 from crabs.tracker.evaluate_tracker import TrackerEvaluate
 from crabs.tracker.sort import Sort
@@ -73,6 +75,33 @@ def __init__(self, args: argparse.Namespace) -> None:
         # Log MLflow information to screen
         log_mlflow_metadata_as_info(self)
 
+    def setup_trainer(self):
+        """Set up trainer object with logging for testing."""
+        # Setup logger
+        mlf_logger = setup_mlflow_logger(
+            experiment_name=self.experiment_name,
+            run_name=self.run_name,
+            mlflow_folder=self.mlflow_folder,
+            cli_args=self.args,
+        )
+
+        # Add trained model section to MLflow hyperparameters
+        mlf_logger.log_hyperparams(
+            {
+                "trained_model/experiment_name": self.trained_model_expt_name,
+                "trained_model/run_name": self.trained_model_run_name,
+                "trained_model/ckpt_file": Path(self.trained_model_path).name,
+            }
+        )
+
+        # Add other unlogged information from init?
+
+        # Return trainer linked to logger
+        return lightning.Trainer(
+            accelerator=self.accelerator,  # lightning accelerators
+            logger=mlf_logger,
+        )
+
     def setup(self):
         """Load tracking config, trained model and input video path."""
         with open(self.config_file) as f:
@@ -334,10 +363,11 @@ def tracking_parse_args(args):
     parser.add_argument(
         "--experiment_name",
         type=str,
+        default="Inference",
         help=(
             "Name of the experiment in MLflow, under which the current run "
             "will be logged. "
-            "By default: <trained_model_mlflow_experiment_name>_evaluation."
+            "By default: Inference."
         ),
     )
     parser.add_argument(