To send object detection result to LIDAR node for Sensor Fusion

ADASObjDetect.py

for detection in detections:

    if detection.score > threshold:

        class_id = int(detection.id)-1

        # Potential Objects: person, bicycle, car, bus, 
        # truck, traffic light, street sign, stop sign
        if class_id not in [0, 1, 2, 3, 5, 7, 9, 11, 12]:
            continue

        det_label = labels[class_id] if labels and 
                    len(labels) >= class_id else '#{}'.format(class_id)
        xmin = max(int(detection.xmin), 0)
        ymin = max(int(detection.ymin), 0)
        xmax = min(int(detection.xmax), x_width)
        ymax = min(int(detection.ymax), y_height)

        x_mid = np.mean([xmin, xmax])
        y_mid = np.mean([ymin, ymax])

        if not isAnnounced(det_label, x_mid, y_mid):

            # theta min and max corresponds to Pi cam FoV angle
            # Picam has 62 degrees horizontal FoV. Need to
            # convert to LIDAR angles at LIDAR node.
            theta_min = xmin / (x_width / 62) + 59
            theta_max = xmax / (x_width / 62) + 59

            now = time.localtime()

            client.publish("object/getdistance", str(det_label) + '|' +
                           str(theta_min) + '|' + str(theta_max) + '|' + 
                           str(now.tm_min * 60 + now.tm_sec))

            objectsInFrame.append(det_label)
            objectMidPts.append((x_mid, y_mid))

# List of objects and its mid points in last 30 frames will be stored in dqueue
if len(objectsInFrame) > 0:
    objLastFrames.extend([objectsInFrame])
    objMidsLastFrames.extend([objectMidPts])
    noObjFrames = 0
else:
    noObjFrames += 1
    
# If no objects found in last 30 frames, reset the queue
if noObjFrames >= 30:
    objMidsLastFrames.clear()
    objLastFrames.clear()
    noObjFrames = 0