Benchmark Camera

This example showcases how the BenchmarkIn node works. It measures the FPS and latency of some message stream, in this case, the video stream from the camera.By default, the node will aggregate 50 messages and then print (firmware warning) the FPS and latency. In our case, that's 33.3ms (30fps) * 50 messages = 1.665 seconds.

Demo

Command Line

1Benchmark $ python3.9 benchmark_camera.py
2[18443010211F850E00] [1.1] [3.367] [BenchmarkIn(1)] [warning] FPS: 30.019516
3[18443010211F850E00] [1.1] [3.367] [BenchmarkIn(1)] [warning] Messages took 1.6655831 s
4[18443010211F850E00] [1.1] [3.367] [BenchmarkIn(1)] [warning] Average latency: 0.010152339 s
5[18443010211F850E00] [1.1] [5.067] [BenchmarkIn(1)] [warning] FPS: 30.000103
6[18443010211F850E00] [1.1] [5.067] [BenchmarkIn(1)] [warning] Messages took 1.6666609 s
7[18443010211F850E00] [1.1] [5.067] [BenchmarkIn(1)] [warning] Average latency: 0.010102791 s
8[18443010211F850E00] [1.1] [6.767] [BenchmarkIn(1)] [warning] FPS: 30.000868

Setup

This example requires the DepthAI v3 API, see installation instructions.

Pipeline

React Flow

Source code

Python

C++

Python

GitHub

1#!/usr/bin/env python3
2import depthai as dai
3import time
4
5# Create pipeline
6with dai.Pipeline() as pipeline:
7    # Create the nodes
8    cam = pipeline.create(dai.node.Camera).build()
9    benchmarkIn = pipeline.create(dai.node.BenchmarkIn)
10    # benchmarkIn.setRunOnHost(True) # The node can also run on host and include the transfer limitation, default is False
11    output = cam.requestFullResolutionOutput()
12    output.link(benchmarkIn.input)
13
14    pipeline.start()
15    while pipeline.isRunning():
16        time.sleep(1) # Let the logger print out the FPS

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Benchmark Camera

Demo

Setup

Pipeline

Source code

Python

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