Hi ShivaRamoudith
Try this:
import cv2
import depthai as dai
import matplotlib.pyplot as plt
import numpy as np
# Create pipeline
pipeline = dai.Pipeline()
# Define sources and outputs
imu = pipeline.create(dai.node.IMU)
xlinkOut = pipeline.create(dai.node.XLinkOut)
pipeline.setXLinkChunkSize(0)
xlinkOut.setStreamName("imu")
# Enable GYROSCOPE_RAW at 200 Hz rate
imu.enableIMUSensor(dai.IMUSensor.GYROSCOPE_RAW, 100)
# Set batch report threshold and max batch reports
imu.setBatchReportThreshold(1)
imu.setMaxBatchReports(10)
# Link plugins IMU -> XLINK
imu.out.link(xlinkOut.input)
# Initialize list to store time deltas
time_deltas = []
# Pipeline is defined, now we can connect to the device
with dai.Device(pipeline) as device:
# Output queue for imu bulk packets
imuQueue = device.getOutputQueue(name="imu", maxSize=50, blocking=False) # Reduce maxSize for more frequent updates
lastTimestamp = None
while len(time_deltas) < 1000:
imuData: dai.IMUData = imuQueue.get() # blocking call, will wait until new data has arrived
currentTimestamp = imuData.getTimestamp().total_seconds()
if lastTimestamp is not None:
delta = (currentTimestamp - lastTimestamp) # Calculate time delta
time_deltas.append(delta)
lastTimestamp = currentTimestamp
# Calculate mean and standard deviation
time_deltas_ms = [x * 1000 for x in time_deltas]
mean_delta = np.mean(time_deltas_ms)
std_delta = np.std(time_deltas_ms)
# Create scatter plot
plt.figure(figsize=(10, 6))
plt.scatter(range(len(time_deltas_ms)), time_deltas_ms, c='blue', label='Time Deltas', s=10)
plt.axhline(mean_delta, color='red', linestyle='--', label=f'Mean = {mean_delta:.2f} ms')
plt.text(0, 0, f"Mean: {mean_delta:.2f} ms\nStd: {std_delta:.2f} ms", fontsize=12, bbox=dict(facecolor='white', alpha=0.5))
plt.xlabel('Measurement Index')
plt.ylabel('Time Delta (ms)')
plt.title('Scatter Plot of Time Deltas Between Consecutive IMU Packets')
plt.legend()
plt.show()
Thanks,
Jaka
