Feature: Add Thermal Image Parser

depthai_nodes/ml/messages/creators/__init__.py

@@ -3,6 +3,7 @@
 from .image import create_image_message
 from .keypoints import create_hand_keypoints_message, create_keypoints_message
 from .segmentation import create_segmentation_message
+from .thermal import create_thermal_message
 from .tracked_features import create_tracked_features_message
 
 __all__ = [
@@ -14,4 +15,5 @@
     "create_line_detection_message",
     "create_tracked_features_message",
     "create_keypoints_message",
+    "create_thermal_message",
 ]

depthai_nodes/ml/messages/creators/thermal.py

@@ -0,0 +1,38 @@
+import depthai as dai
+import numpy as np
+
+
+def create_thermal_message(thermal_image: np.array) -> dai.ImgFrame:
+    """Creates a thermal image message in the form of an ImgFrame using the provided
+    thermal image array.
+
+    Args:
+        thermal_image (np.array): A NumPy array representing the thermal image with shape (CHW or HWC).
+
+    Returns:
+        dai.ImgFrame: An ImgFrame object containing the thermal information.
+    """
+
+    if not isinstance(thermal_image, np.ndarray):
+        raise ValueError(f"Expected numpy array, got {type(thermal_image)}.")
+    if len(thermal_image.shape) != 3:
+        raise ValueError(f"Expected 3D input, got {len(thermal_image.shape)}D input.")
+
+    if thermal_image.shape[0] == 1:
+        thermal_image = thermal_image[0, :, :]  # CHW to HW
+    elif thermal_image.shape[2] == 1:
+        thermal_image = thermal_image[:, :, 0]  # HWC to HW
+    else:
+        raise ValueError(
+            "Unexpected image shape. Expected CHW or HWC, got", thermal_image.shape
+        )
+
+    thermal_image = thermal_image.astype(np.uint16)
+
+    imgFrame = dai.ImgFrame()
+    imgFrame.setFrame(thermal_image)
+    imgFrame.setWidth(thermal_image.shape[1])
+    imgFrame.setHeight(thermal_image.shape[0])
+    imgFrame.setType(dai.ImgFrame.Type.RAW16)
+
+    return imgFrame

depthai_nodes/ml/parsers/__init__.py

@@ -7,6 +7,7 @@
 from .scrfd import SCRFDParser
 from .segmentation import SegmentationParser
 from .superanimal_landmarker import SuperAnimalParser
+from .thermal_image import ThermalImageParser
 from .xfeat import XFeatParser
 from .yunet import YuNetParser
 
@@ -22,4 +23,5 @@
     "KeypointParser",
     "MLSDParser",
     "XFeatParser",
+    "ThermalImageParser",
 ]

depthai_nodes/ml/parsers/thermal_image.py

@@ -0,0 +1,35 @@
+import depthai as dai
+
+from ..messages.creators import create_thermal_message
+
+
+class ThermalImageParser(dai.node.ThreadedHostNode):
+    def __init__(self):
+        dai.node.ThreadedHostNode.__init__(self)
+        self.input = dai.Node.Input(self)
+        self.out = dai.Node.Output(self)
+
+    def run(self):
+        """Postprocessing logic for a model with thermal image output (e.g. UGSR-FA).
+
+        Returns:
+            dai.ImgFrame: uint16, HW thermal image.
+        """
+
+        while self.isRunning():
+            try:
+                output: dai.NNData = self.input.get()
+            except dai.MessageQueue.QueueException:
+                break  # Pipeline was stopped
+
+            output_layer_names = output.getAllLayerNames()
+            if len(output_layer_names) != 1:
+                raise ValueError(
+                    f"Expected 1 output layer, got {len(output_layer_names)}."
+                )
+            output = output.getTensor(output_layer_names[0])
+
+            thermal_map = output[0]
+
+            thermal_message = create_thermal_message(thermal_map=thermal_map)
+            self.out.send(thermal_message)