Difference between revisions of "CUDA Accelerated GStreamer Camera Undistort/Performance/Nano"
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== Platform Setup == | == Platform Setup == | ||
| − | The performance measurements were done with | + | The performance measurements were done with a Jetson Nano board in ''10W'' mode, which is the default, and can be activated with |
<source lang=bash> | <source lang=bash> | ||
sudo nvpmodel -m 0 | sudo nvpmodel -m 0 | ||
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INPUT=image_1.jpg | INPUT=image_1.jpg | ||
| − | gst-launch-1.0 | + | gst-launch-1.0 filesrc location=$INPUT \ |
! nvjpegdec ! imagefreeze ! nvvidconv\ | ! nvjpegdec ! imagefreeze ! nvvidconv\ | ||
! cudaundistort distortion-model=fisheye \ | ! cudaundistort distortion-model=fisheye \ | ||
Revision as of 16:05, 25 March 2021
| CUDA Accelerated GStreamer Camera Undistort | |
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| Undistort Basics | |
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| Getting Started | |
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| User Guide | |
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| Examples | |
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| Performance | |
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| Contact Us |
The performance of the cuda unidstort element depends mainly on the input image resolution.
The following sections show the measurements of the cuda-undistort (FPS and Latency) for multiple image resolutions; as well as the impact of changing the distortion model.
Platform Setup
The performance measurements were done with a Jetson Nano board in 10W mode, which is the default, and can be activated with
sudo nvpmodel -m 0
The following sections show a comparison between using the platform at maximum frequency (With jetson_clocks) and in base mode. This mode can be set as follows:
sudo /usr/bin/jetson_clocks
Framerate
The average Frames per Second measurements are shown in the following charts, for multiple image resolutions. Also, the impact of executing or not the jetson_clocks script is shown in the results.
Pipeline structure
The general structure of the pipeline used for the framerate measurements is shown below, for the Fisheye model.
CAMERA_MATRIX="{\"fx\":9.5211633874478218e+02, \"fy\":9.4946222068253201e+02, \"cx\":6.8041416457132573e+02, \"cy\":3.1446117133659988e+02}"
DISTORTION_PARAMETERS="{\"k1\":3.8939572818197948e-01, \"k2\":-5.5685725182648649e-01, \"k3\":2.3785352925072494e+00, \"k4\":-1.2037220289124213e+00}"
INPUT=image_1.jpg
gst-launch-1.0 filesrc location=$INPUT \
! nvjpegdec ! imagefreeze ! nvvidconv\
! cudaundistort distortion-model=fisheye \
camera-matrix="$CAMERA_MATRIX" distortion-parameters="$DISTORTION_PARAMETERS" \
! perf print-cpu-load=true ! fakesink
Latency
For the purpose of this performance evaluation, Latency is measured as the time difference between the src of the element before the undistort and the undistort src, effectively measuring the time between input and output pads.
The pictures below show the latency of the cuda-undistort element, for both models and multiple resolutions, as well as using and not using the jetson_clocks script.
Pipeline structure
The general structure of the pipeline used for the latency measurements is shown below, for the Fisheye model.
CAMERA_MATRIX="{\"fx\":9.5211633874478218e+02, \"fy\":9.4946222068253201e+02, \"cx\":6.8041416457132573e+02, \"cy\":3.1446117133659988e+02}"
DISTORTION_PARAMETERS="{\"k1\":3.8939572818197948e-01, \"k2\":-5.5685725182648649e-01, \"k3\":2.3785352925072494e+00, \"k4\":-1.2037220289124213e+00}"
INPUT=image_1.jpg
GST_DEBUG="3,GST_TRACER:7" GST_TRACERS="interlatency" GST_SHARK_CTF_DISABLE=1 \
gst-launch-1.0 filesrc location=$INPUT \
! nvjpegdec ! imagefreeze ! nvvidconv \
! cudaundistort distortion-model=fisheye \
camera-matrix="$CAMERA_MATRIX" distortion-parameters="$DISTORTION_PARAMETERS" \
! perf print-cpu-load=true ! fakesink
