5344 implement pq metric (Project-MONAI#5377)

Fixes Project-MONAI#5344 .

### Description

This PR implements the metric of Panoptic Quality.


### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [x] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [x] In-line docstrings updated.
- [x] Documentation updated, tested `make html` command in the `docs/`
folder.

Signed-off-by: Yiheng Wang <vennw@nvidia.com>
Co-authored-by: Behrooz Hashemian <3968947+drbeh@users.noreply.github.com>
Co-authored-by: Dženan Zukić <dzenan.zukic@kitware.com>
Co-authored-by: Wenqi Li <831580+wyli@users.noreply.github.com>

docs/source/handlers.rst

@@ -71,6 +71,12 @@ Surface distance metrics handler
     :members:
 
 
+Panoptic Quality metrics handler
+--------------------------------
+.. autoclass:: PanopticQuality
+    :members:
+
+
 Mean squared error metrics handler
 ----------------------------------
 .. autoclass:: MeanSquaredError

docs/source/metrics.rst

@@ -104,6 +104,13 @@ Metrics
 .. autoclass:: SurfaceDiceMetric
     :members:
 
+`PanopticQualityMetric`
+-----------------------
+.. autofunction:: compute_panoptic_quality
+
+.. autoclass:: PanopticQualityMetric
+    :members:
+
 `Mean squared error`
 --------------------
 .. autoclass:: MSEMetric

monai/handlers/__init__.py

@@ -26,6 +26,7 @@
 from .metrics_saver import MetricsSaver
 from .mlflow_handler import MLFlowHandler
 from .nvtx_handlers import MarkHandler, RangeHandler, RangePopHandler, RangePushHandler
+from .panoptic_quality import PanopticQuality
 from .parameter_scheduler import ParamSchedulerHandler
 from .postprocessing import PostProcessing
 from .probability_maps import ProbMapProducer

monai/handlers/panoptic_quality.py

@@ -0,0 +1,67 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Callable, Union
+
+from monai.handlers.ignite_metric import IgniteMetric
+from monai.metrics import PanopticQualityMetric
+from monai.utils import MetricReduction
+
+
+class PanopticQuality(IgniteMetric):
+    """
+    Computes Panoptic quality from full size Tensor and collects average over batch, class-channels, iterations.
+    """
+
+    def __init__(
+        self,
+        num_classes: int,
+        metric_name: str = "pq",
+        reduction: Union[MetricReduction, str] = MetricReduction.MEAN_BATCH,
+        match_iou_threshold: float = 0.5,
+        smooth_numerator: float = 1e-6,
+        output_transform: Callable = lambda x: x,
+        save_details: bool = True,
+    ) -> None:
+        """
+
+        Args:
+            num_classes: number of classes. The number should not count the background.
+            metric_name: output metric. The value can be "pq", "sq" or "rq".
+            reduction: define mode of reduction to the metrics, will only apply reduction on `not-nan` values,
+                available reduction modes: {``"none"``, ``"mean"``, ``"sum"``, ``"mean_batch"``, ``"sum_batch"``,
+                ``"mean_channel"``, ``"sum_channel"``}, default to `self.reduction`. if "none", will not do reduction.
+            match_iou_threshold: IOU threshould to determine the pairing between `y_pred` and `y`. Usually,
+                it should >= 0.5, the pairing between instances of `y_pred` and `y` are identical.
+                If set `match_iou_threshold` < 0.5, this function uses Munkres assignment to find the
+                maximal amout of unique pairing.
+            smooth_numerator: a small constant added to the numerator to avoid zero.
+            output_transform: callable to extract `y_pred` and `y` from `ignite.engine.state.output` then
+                construct `(y_pred, y)` pair, where `y_pred` and `y` can be `batch-first` Tensors or
+                lists of `channel-first` Tensors. the form of `(y_pred, y)` is required by the `update()`.
+                `engine.state` and `output_transform` inherit from the ignite concept:
+                https://pytorch.org/ignite/concepts.html#state, explanation and usage example are in the tutorial:
+                https://github.com/Project-MONAI/tutorials/blob/master/modules/batch_output_transform.ipynb.
+            save_details: whether to save metric computation details per image, for example: panoptic quality of
+                every image.
+                default to True, will save to `engine.state.metric_details` dict with the metric name as key.
+
+        See also:
+            :py:meth:`monai.metrics.panoptic_quality.compute_panoptic_quality`
+        """
+        metric_fn = PanopticQualityMetric(
+            num_classes=num_classes,
+            metric_name=metric_name,
+            reduction=reduction,
+            match_iou_threshold=match_iou_threshold,
+            smooth_numerator=smooth_numerator,
+        )
+        super().__init__(metric_fn=metric_fn, output_transform=output_transform, save_details=save_details)

monai/metrics/__init__.py

@@ -18,6 +18,7 @@
 from .meandice import DiceMetric, compute_dice, compute_meandice
 from .meaniou import MeanIoU, compute_iou, compute_meaniou
 from .metric import Cumulative, CumulativeIterationMetric, IterationMetric, Metric
+from .panoptic_quality import PanopticQualityMetric, compute_panoptic_quality
 from .regression import MAEMetric, MSEMetric, PSNRMetric, RMSEMetric, SSIMMetric
 from .rocauc import ROCAUCMetric, compute_roc_auc
 from .surface_dice import SurfaceDiceMetric, compute_surface_dice