feat(autoware_ml): add t4segmetric

autoware_ml/hooks/__init__.py

@@ -6,6 +6,8 @@
     PytorchTrainingProfilerHook,
     PytorchValidationProfilerHook,
 )
+from .t4_seg_logger_hook import T4SegLoggerHook
+from .t4_seg_tensorboard_hook import T4SegTensorboardHook
 
 __all__ = [
     "MomentumInfoHook",
@@ -14,4 +16,6 @@
     "PytorchValidationProfilerHook",
     "LossScaleInfoHook",
     "LoggerHook",
+    "T4SegLoggerHook",
+    "T4SegTensorboardHook",
 ]

autoware_ml/hooks/t4_seg_logger_hook.py

@@ -0,0 +1,13 @@
+from mmengine.registry import HOOKS
+
+from .logger_hook import LoggerHook
+
+
+@HOOKS.register_module()
+class T4SegLoggerHook(LoggerHook):
+    """Logger hook for T4 segmentation configs using custom TensorBoard metric tags."""
+
+    def after_val_epoch(self, runner, metrics=None) -> None:
+        """Log validation results without the default TensorBoard scalar dump."""
+        _, log_str = runner.log_processor.get_log_after_epoch(runner, len(runner.val_dataloader), "val")
+        runner.logger.info(log_str)

autoware_ml/hooks/t4_seg_tensorboard_hook.py

@@ -0,0 +1,63 @@
+import matplotlib.pyplot as plt
+from mmengine.hooks import Hook
+from mmengine.registry import HOOKS
+from mmengine.visualization import Visualizer
+
+from autoware_ml.segmentation3d.evaluation import (
+    T4SegMetric,
+    build_t4_seg_tb_scalars,
+    figure_to_numpy,
+    iter_t4_seg_confusion_matrix_figures,
+)
+
+
+@HOOKS.register_module()
+class T4SegTensorboardHook(Hook):
+    """Log shared T4 segmentation TensorBoard tags for MMEngine runners."""
+
+    priority = "LOW"
+
+    def after_val_epoch(self, runner, metrics=None):
+        self._log_stage(runner, stage="val", step=runner.iter)
+
+    def after_test_epoch(self, runner, metrics=None):
+        self._log_stage(runner, stage="test", step=0)
+
+    def _log_stage(self, runner, stage: str, step: int) -> None:
+        metric = self._get_metric(runner, stage)
+        if metric is None or metric.last_eval_result is None:
+            return
+
+        try:
+            vis = Visualizer.get_current_instance()
+        except Exception:
+            return
+
+        class_names = [metric.last_label2cat[i] for i in sorted(metric.last_label2cat)]
+        scalars = build_t4_seg_tb_scalars(
+            metrics=metric.last_eval_result.metrics,
+            class_names=class_names,
+            stage=stage,
+            distance_ranges=metric.distance_ranges,
+        )
+        if scalars:
+            vis.add_scalars(scalars, step=step)
+
+        for tag, fig in iter_t4_seg_confusion_matrix_figures(metric.last_eval_result, class_names, stage):
+            try:
+                vis.add_image(tag, figure_to_numpy(fig), step=step)
+            except Exception:
+                pass
+            finally:
+                plt.close(fig)
+
+    @staticmethod
+    def _get_metric(runner, stage: str):
+        loop = runner.val_loop if stage == "val" else runner.test_loop
+        evaluator = getattr(loop, "evaluator", None)
+        if evaluator is None:
+            return None
+        for metric in getattr(evaluator, "metrics", []):
+            if isinstance(metric, T4SegMetric):
+                return metric
+        return None

autoware_ml/segmentation3d/evaluation/__init__.py

@@ -0,0 +1,45 @@
+# Copyright (c) TIER IV, Inc. All rights reserved.
+"""Segmentation evaluation: functional helpers + MMEngine metric adapter."""
+
+from .functional.t4_seg_eval import (
+    SegEvalResult,
+    compute_bev_distance,
+    fast_hist,
+    figure_to_numpy,
+    get_acc,
+    get_acc_cls,
+    normalize_confusion_matrix,
+    per_class_f1,
+    per_class_iou,
+    per_class_precision,
+    per_class_recall,
+    plot_confusion_matrix,
+    range_label,
+    t4_seg_eval,
+    t4_seg_eval_from_hists,
+    update_seg_eval_histograms,
+)
+from .metrics.t4_seg_metric import T4SegMetric
+from .tensorboard import build_t4_seg_tb_scalars, iter_t4_seg_confusion_matrix_figures
+
+__all__ = [
+    "SegEvalResult",
+    "T4SegMetric",
+    "build_t4_seg_tb_scalars",
+    "compute_bev_distance",
+    "fast_hist",
+    "figure_to_numpy",
+    "get_acc",
+    "get_acc_cls",
+    "normalize_confusion_matrix",
+    "per_class_f1",
+    "per_class_iou",
+    "per_class_precision",
+    "per_class_recall",
+    "plot_confusion_matrix",
+    "range_label",
+    "t4_seg_eval",
+    "t4_seg_eval_from_hists",
+    "iter_t4_seg_confusion_matrix_figures",
+    "update_seg_eval_histograms",
+]

autoware_ml/segmentation3d/evaluation/functional/__init__.py

@@ -0,0 +1,34 @@
+# Copyright (c) TIER IV, Inc. All rights reserved.
+from .t4_seg_eval import (
+    SegEvalResult,
+    compute_bev_distance,
+    fast_hist,
+    figure_to_numpy,
+    get_acc,
+    get_acc_cls,
+    normalize_confusion_matrix,
+    per_class_f1,
+    per_class_iou,
+    per_class_precision,
+    per_class_recall,
+    plot_confusion_matrix,
+    range_label,
+    t4_seg_eval,
+)
+
+__all__ = [
+    "SegEvalResult",
+    "compute_bev_distance",
+    "fast_hist",
+    "figure_to_numpy",
+    "get_acc",
+    "get_acc_cls",
+    "normalize_confusion_matrix",
+    "per_class_f1",
+    "per_class_iou",
+    "per_class_precision",
+    "per_class_recall",
+    "plot_confusion_matrix",
+    "range_label",
+    "t4_seg_eval",
+]