Add detection scene

Signed-off-by: Ashwin Vaidya <[email protected]>

Author: ashwinvaidya17

src/python/model_api/models/result/detection.py

@@ -111,6 +111,11 @@ def label_names(self, value):
 
     @property
     def saliency_map(self):
+        """Saliency map for XAI.
+
+        Returns:
+            np.ndarray: Saliency map in dim of (B, N_CLASSES, H, W).
+        """
         return self._saliency_map
 
     @saliency_map.setter

src/python/model_api/visualizer/scene/detection.py

@@ -3,12 +3,15 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+from itertools import starmap
 from typing import Union
 
+import cv2
 from PIL import Image
 
 from model_api.models.result import DetectionResult
-from model_api.visualizer.layout import Layout
+from model_api.visualizer.layout import Flatten, HStack, Layout
+from model_api.visualizer.primitive import BoundingBox, Label, Overlay
 
 from .scene import Scene
 
@@ -17,5 +20,30 @@ class DetectionScene(Scene):
     """Detection Scene."""
 
     def __init__(self, image: Image, result: DetectionResult, layout: Union[Layout, None] = None) -> None:
-        self.image = image
-        self.result = result
+        super().__init__(
+            base=image,
+            label=self._get_labels(result),
+            bounding_box=self._get_bounding_boxes(result),
+            overlay=self._get_overlays(result),
+            layout=layout,
+        )
+
+    def _get_labels(self, result: DetectionResult) -> list[Label]:
+        labels = []
+        for label, score, label_name in zip(result.labels, result.scores, result.label_names):
+            labels.append(Label(label=f"{label} {label_name}", score=score))
+        return labels
+
+    def _get_overlays(self, result: DetectionResult) -> list[Overlay]:
+        overlays = []
+        for saliency_map in result.saliency_map[0][1:]:  # Assumes only one batch. Skip background class.
+            saliency_map = cv2.applyColorMap(saliency_map, cv2.COLORMAP_JET)
+            overlays.append(Overlay(saliency_map))
+        return overlays
+
+    def _get_bounding_boxes(self, result: DetectionResult) -> list[BoundingBox]:
+        return list(starmap(BoundingBox, result.bboxes))
+
+    @property
+    def default_layout(self) -> Layout:
+        return HStack(Flatten(BoundingBox, Label), Overlay)