Sorry I have almost no experience with opencv version provided in JetPack, but it has nothing accelerated (no CUDA support), only gstreamer support that can give access to HW accelerated plugins.
Guessing that your STREAM is a just an URI, the reason might be that, without any other API specified, opencv videoio would use FFMEG backend. But the apt version of ffmpeg has no accelaration support for Jetson.
So, (assuming your stream is H264 encoded) the simplest would be to use a gstreamer pipeline with HW accelerated H264 decoder as input:
#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/videoio.hpp>
int main (void)
{
/* Create input pipeline */
const char *gst_cap =
"rtspsrc location=rtspt://wowzaec2demo.streamlock.net/vod/mp4:BigBuckBunny_175k.mov"
" ! application/x-rtp, media=video, encoding-name=H264"
" ! queue ! rtph264depay ! h264parse ! omxh264dec ! nvvidconv ! video/x-raw,format=BGRx "
" ! videoconvert ! video/x-raw, format=BGR ! appsink ";
cv::VideoCapture cap (gst_cap, cv::CAP_GSTREAMER);
if (!cap.isOpened ()) {
std::cout << "Error: Cv::VideoCapture.open() failed" << std::endl;
return 1;
}
else
std::cout << "Cam opened (backend: " << cap.getBackendName () << ")" << std::endl;
unsigned int width = cap.get (cv::CAP_PROP_FRAME_WIDTH);
unsigned int height = cap.get (cv::CAP_PROP_FRAME_HEIGHT);
float fps = cap.get (cv::CAP_PROP_FPS);
std::cout << "Framing : " << width << " x " << height << "@" << fps << " FPS" << std::endl;
/* Create output pipeline */
const char *gst_2nvegl =
"appsrc ! video/x-raw, format=BGR ! queue"
" ! videoconvert ! video/x-raw, format=RGBA "
" ! nvvidconv ! nvegltransform ! nveglglessink ";
cv::VideoWriter writer (gst_2nvegl, cv::CAP_GSTREAMER, 0, fps, cv::Size (width, height));
if (!writer.isOpened ()) {
std::cout << "Error: Cv::VideoWriter.open() failed" << std::endl;
return 2;
}
else
std::cout << "Writer opened" << std::endl;
/* Loop */
cv::Mat frame_in (width, height, CV_8UC3);
for (;;) {
if (!cap.read (frame_in)) {
std::cout << "Capture read error" << std::endl;
break;
}
/* Process BGR frame */
writer.write (frame_in);
}
writer.release ();
cap.release ();
return 0;
}
Alternately, but this would be a bit more complicated, you may try to build your own ffmpeg with jocover’s patch.
I successfully used this script a few time ago for building on AGX Xavier (you may just use make -j4 on Nano):
#!/usr/bin/env bash
set -e
cd /home/nvidia/Desktop
# Build and install library for ffmpeg
git clone https://github.com/jocover/jetson-ffmpeg.git
cd jetson-ffmpeg
cp /usr/src/jetson_multimedia_api/include/nvbuf_utils.h include
mkdir build
cd build
cmake ..
make -j8
sudo make install
sudo ldconfig
# Build and install ffmpeg
git clone git://source.ffmpeg.org/ffmpeg.git -b release/4.2 --depth=1
cd ffmpeg
wget https://github.com/jocover/jetson-ffmpeg/raw/master/ffmpeg_nvmpi.patch
git apply ffmpeg_nvmpi.patch
sudo apt-get update
sudo apt-get install libcanberra-gtk-module
./configure --toolchain=hardened --libdir=/usr/lib/aarch64-linux-gnu --incdir=/usr/include/aarch64-linux-gnu --enable-nvmpi --enable-opengl --enable-libdrm --enable-shared
make -j8
sudo make install
Then build opencv from source, it should find ffmpeg (check your cmake configure log) :
or:
Rebuild your application and retry, you should see improvement with ffmpeg backend for this case.
Using NVIDIA’s version of ffmpeg for opencv would be ideal, but it may rise some issues…not investigated much further, maybe @DaneLLL or @AastaLLL or someone else has succeeded in this and may share.
