Script pipeline flow

docs/source/samples/Script/script_change_pipeline_flow.rst

@@ -0,0 +1,43 @@
+Script change pipeline flow
+===========================
+
+This example shows how you can change the flow of data inside your pipeline in runtime using the :ref:`Script` node. In this example, we send a message from
+the host to choose whether we want Script node to forwards color frame to the :ref:`MobileNetDetectionNetwork`.
+
+Demo
+####
+
+.. image:: https://user-images.githubusercontent.com/18037362/187734814-df3b46c9-5e04-4a9d-bf6f-d738b40b4421.gif
+
+Pipeline Graph
+##############
+
+.. image:: https://user-images.githubusercontent.com/18037362/187736249-db7ff175-fcea-4d4e-b567-f99087bd82ee.png
+
+Setup
+#####
+
+.. include::  /includes/install_from_pypi.rst
+
+Source code
+###########
+
+.. tabs::
+
+    .. tab:: Python
+
+        Also `available on GitHub <https://github.com/luxonis/depthai-python/blob/main/examples/Script/script_change_pipeline_flow.py>`__
+
+        .. literalinclude:: ../../../../examples/Script/script_change_pipeline_flow.py
+           :language: python
+           :linenos:
+
+    .. tab:: C++
+
+        Also `available on GitHub <https://github.com/luxonis/depthai-core/blob/main/examples/Script/script_change_pipeline_flow.cpp>`__
+
+        .. literalinclude:: ../../../../depthai-core/examples/Script/script_change_pipeline_flow.cpp
+           :language: cpp
+           :linenos:
+
+.. include::  /includes/footer-short.rst

docs/source/tutorials/code_samples.rst

@@ -113,6 +113,7 @@ are presented with code.
 .. rubric:: Script
 
 - :ref:`Script camera control` - Controlling the camera with the Script node
+- :ref:`Script change pipeline flow` - Change the flow of data inside your pipeline in runtime with :ref:`Script` node
 - :ref:`Script forward frames` - Forward incoming image stream to two different output streams (demuxing)
 - :ref:`Script get local IP` - Get local IP of the device (only OAK-POE devices)
 - :ref:`Script HTTP client` - Send HTTP request to a server (only OAK-POE devices)

examples/Script/script_change_pipeline_flow.py

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+#!/usr/bin/env python3
+import depthai as dai
+import cv2
+from pathlib import Path
+import numpy as np
+
+parentDir = Path(__file__).parent
+nnPath = str((parentDir / Path('../models/mobilenet-ssd_openvino_2021.4_5shave.blob')).resolve().absolute())
+
+pipeline = dai.Pipeline()
+
+cam = pipeline.createColorCamera()
+cam.setBoardSocket(dai.CameraBoardSocket.RGB)
+cam.setInterleaved(False)
+cam.setIspScale(2,3)
+cam.setVideoSize(720,720)
+cam.setPreviewSize(300,300)
+
+xoutRgb = pipeline.create(dai.node.XLinkOut)
+xoutRgb.setStreamName('rgb')
+cam.video.link(xoutRgb.input)
+
+script = pipeline.createScript()
+
+xin = pipeline.create(dai.node.XLinkIn)
+xin.setStreamName('in')
+xin.out.link(script.inputs['toggle'])
+
+cam.preview.link(script.inputs['rgb'])
+script.setScript("""
+    toggle = False
+    while True:
+        msg = node.io['toggle'].tryGet()
+        if msg is not None:
+            toggle = msg.getData()[0]
+            node.warn('Toggle! Perform NN inferencing: ' + str(toggle))
+
+        frame = node.io['rgb'].get()
+
+        if toggle:
+            node.io['nn'].send(frame)
+""")
+
+nn = pipeline.create(dai.node.MobileNetDetectionNetwork)
+nn.setBlobPath(nnPath)
+script.outputs['nn'].link(nn.input)
+
+xoutNn = pipeline.create(dai.node.XLinkOut)
+xoutNn.setStreamName('nn')
+nn.out.link(xoutNn.input)
+
+# Connect to device with pipeline
+with dai.Device(pipeline) as device:
+    inQ = device.getInputQueue("in")
+    qRgb = device.getOutputQueue("rgb")
+    qNn = device.getOutputQueue("nn")
+
+    runNn = False
+
+    def frameNorm(frame, bbox):
+        normVals = np.full(len(bbox), frame.shape[0])
+        normVals[::2] = frame.shape[1]
+        return (np.clip(np.array(bbox), 0, 1) * normVals).astype(int)
+
+    color = (255, 127, 0)
+    def drawDetections(frame, detections):
+        for detection in detections:
+            bbox = frameNorm(frame, (detection.xmin, detection.ymin, detection.xmax, detection.ymax))
+            cv2.putText(frame, f"{int(detection.confidence * 100)}%", (bbox[0] + 10, bbox[1] + 20), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color)
+            cv2.rectangle(frame, (bbox[0], bbox[1]), (bbox[2], bbox[3]), color, 2)
+
+
+    while True:
+        frame = qRgb.get().getCvFrame()
+
+        if qNn.has():
+            detections = qNn.get().detections
+            drawDetections(frame, detections)
+
+        cv2.putText(frame, f"NN inferencing: {runNn}", (20,20), cv2.FONT_HERSHEY_TRIPLEX, 0.7, color)
+        cv2.imshow('Color frame', frame)
+
+        key = cv2.waitKey(1)
+        if key == ord('q'):
+            break
+        elif key == ord('t'):
+            runNn = not runNn
+            print(f"{'Enabling' if runNn else 'Disabling'} NN inferencing")
+            buf = dai.Buffer()
+            buf.setData(runNn)
+            inQ.send(buf)