initial oakd classification checkin

src/main/java/org/myrobotlab/service/InMoov2.java

@@ -36,6 +36,7 @@
 import org.myrobotlab.service.config.InMoov2Config;
 import org.myrobotlab.service.config.OpenCVConfig;
 import org.myrobotlab.service.config.SpeechSynthesisConfig;
+import org.myrobotlab.service.data.Classification;
 import org.myrobotlab.service.data.JoystickData;
 import org.myrobotlab.service.data.Locale;
 import org.myrobotlab.service.interfaces.IKJointAngleListener;
@@ -2294,5 +2295,10 @@ public void waitTargetPos() {
     sendToPeer("leftArm", "waitTargetPos");
     sendToPeer("torso", "waitTargetPos");
   }
+
+  public Map publishClassification(Map<String, Object> c) {
+    // log.info(c);    
+    return c;
+  }
 
 }

src/main/resources/resource/OakD/classification.py

@@ -0,0 +1,13 @@
+# new awesome robot script
+# new awesome robot script
+python = runtime.getService("python")
+if python:
+    python.subscribe("i01","publishClassification")
+
+def onClassification(c):
+    print("label       ", c.get("label"))
+    print("confidence  ", c.get("confidence"))
+    print("bounding box", c.get("xmin"), c.get("xmax"), c.get("ymin"), c.get("ymax"))    
+    print("position    ", c.get("x"), c.get("y"), c.get("z"))
+
+print("loaded classifications.py")

src/main/resources/resource/OakD/mrl_callbacks.py

@@ -0,0 +1,71 @@
+import requests
+import json
+
+def onNewFrame(frame, source):
+    pass
+
+
+def onShowFrame(frame, source):
+    pass
+
+# found in config.json in the model directory
+# e.g. resources/nn/mobilenet-ssd/mobilenet-ssd.json
+labels = ["background",  "aeroplane",  "bicycle",  "bird",  "boat",  "bottle",  "bus",  "car",  "cat",  "chair",  "cow",  "diningtable",  "dog",  "horse",  "motorbike",  "person",  "pottedplant",  "sheep",  "sofa",  "train",  "tvmonitor"]
+# TODO - debounce the detections
+
+def onNn(nn_packet, decoded_data):
+    # print(dir(nn_packet))
+    # print(dir(decoded_data))
+    # print(json.dumps(decoded_data))
+    for detection in decoded_data:
+        print(detection.spatialCoordinates.x)
+        print(detection.spatialCoordinates.y)
+        print(detection.spatialCoordinates.z)
+        # print(detection.boundingBoxMapping)
+        # print(dir(detection.boundingBoxMapping))
+        print(labels[detection.label])
+        print(detection.confidence)
+        print(f'xmin {detection.xmin}')
+        print(f'xmax {detection.xmin}')
+        print(f'ymin {detection.ymin}')
+        print(f'ymax {detection.xmin}')
+        # Add detections to visualizer
+        url = 'http://localhost:8888/api/service/i01/publishClassification'  # Replace with your URL
+        data = {
+            "xmin": detection.xmin,
+            "xmax": detection.xmax,
+            "ymin": detection.xmin,
+            "ymax": detection.ymax,
+            "label": labels[detection.label],
+            "confidence": detection.confidence,
+            "x": detection.spatialCoordinates.x,
+            "y": detection.spatialCoordinates.y,
+            "z": detection.spatialCoordinates.z
+        }
+
+        # Make the POST request with JSON data
+        try:
+            response = requests.post(url, json=[data])
+        except requests.exceptions.HTTPError as http_err:
+            print(f'HTTP error occurred: {http_err}')  # HTTP error
+        except requests.exceptions.ConnectionError as conn_err:
+            print(f'Connection error occurred: {conn_err}')  # Connection error
+        except requests.exceptions.Timeout as timeout_err:
+            print(f'Timeout error occurred: {timeout_err}')  # Timeout error
+        except requests.exceptions.RequestException as req_err:
+            print(f'An error occurred: {req_err}')  # Other errors
+
+def onReport(report):
+    pass
+
+
+def onSetup(*args, **kwargs):
+    pass
+
+
+def onTeardown(*args, **kwargs):
+    pass
+
+
+def onIter(*args, **kwargs):
+    pass