Rename loggers from YOLOv8 to Ultralytics (#16784)

Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

ultralytics/utils/callbacks/clearml.py

@@ -68,9 +68,9 @@ def on_pretrain_routine_start(trainer):
             PatchedMatplotlib.update_current_task(None)
         else:
             task = Task.init(
-                project_name=trainer.args.project or "YOLOv8",
+                project_name=trainer.args.project or "Ultralytics",
                 task_name=trainer.args.name,
-                tags=["YOLOv8"],
+                tags=["Ultralytics"],
                 output_uri=True,
                 reuse_last_task_id=False,
                 auto_connect_frameworks={"pytorch": False, "matplotlib": False},

ultralytics/utils/callbacks/comet.py

@@ -15,7 +15,7 @@ try:
     # Ensures certain logging functions only run for supported tasks
     COMET_SUPPORTED_TASKS = ["detect"]
 
-    # Names of plots created by YOLOv8 that are logged to Comet
+    # Names of plots created by Ultralytics that are logged to Comet
     EVALUATION_PLOT_NAMES = "F1_curve", "P_curve", "R_curve", "PR_curve", "confusion_matrix"
     LABEL_PLOT_NAMES = "labels", "labels_correlogram"
 
@@ -31,8 +31,8 @@ def _get_comet_mode():
 
 
 def _get_comet_model_name():
-    """Returns the model name for Comet from the environment variable 'COMET_MODEL_NAME' or defaults to 'YOLOv8'."""
-    return os.getenv("COMET_MODEL_NAME", "YOLOv8")
+    """Returns the model name for Comet from the environment variable COMET_MODEL_NAME or defaults to 'Ultralytics'."""
+    return os.getenv("COMET_MODEL_NAME", "Ultralytics")
 
 
 def _get_eval_batch_logging_interval():
@@ -110,7 +110,7 @@ def _fetch_trainer_metadata(trainer):
 
 def _scale_bounding_box_to_original_image_shape(box, resized_image_shape, original_image_shape, ratio_pad):
     """
-    YOLOv8 resizes images during training and the label values are normalized based on this resized shape.
+    YOLO resizes images during training and the label values are normalized based on this resized shape.
 
     This function rescales the bounding box labels to the original image shape.
     """

ultralytics/utils/callbacks/mlflow.py

@@ -71,7 +71,7 @@ def on_pretrain_routine_end(trainer):
     mlflow.set_tracking_uri(uri)
 
     # Set experiment and run names
-    experiment_name = os.environ.get("MLFLOW_EXPERIMENT_NAME") or trainer.args.project or "/Shared/YOLOv8"
+    experiment_name = os.environ.get("MLFLOW_EXPERIMENT_NAME") or trainer.args.project or "/Shared/Ultralytics"
     run_name = os.environ.get("MLFLOW_RUN") or trainer.args.name
     mlflow.set_experiment(experiment_name)
 

ultralytics/utils/callbacks/neptune.py

@@ -52,7 +52,11 @@ def on_pretrain_routine_start(trainer):
     """Callback function called before the training routine starts."""
     try:
         global run
-        run = neptune.init_run(project=trainer.args.project or "YOLOv8", name=trainer.args.name, tags=["YOLOv8"])
+        run = neptune.init_run(
+            project=trainer.args.project or "Ultralytics",
+            name=trainer.args.name,
+            tags=["Ultralytics"],
+        )
         run["Configuration/Hyperparameters"] = {k: "" if v is None else v for k, v in vars(trainer.args).items()}
     except Exception as e:
         LOGGER.warning(f"WARNING ⚠️ NeptuneAI installed but not initialized correctly, not logging this run. {e}")

ultralytics/utils/callbacks/wb.py

@@ -109,7 +109,7 @@ def _log_plots(plots, step):
 
 def on_pretrain_routine_start(trainer):
     """Initiate and start project if module is present."""
-    wb.run or wb.init(project=trainer.args.project or "YOLOv8", name=trainer.args.name, config=vars(trainer.args))
+    wb.run or wb.init(project=trainer.args.project or "Ultralytics", name=trainer.args.name, config=vars(trainer.args))
 
 
 def on_fit_epoch_end(trainer):