Exception: jetson.utils -- failed to create videoSource device

[karishmathumu]

Hai Sir,

1. Can ./imagenet (imagenet.cpp) /dev/video0 be used for live detection (when implemented outside jetson-inference directory) where the contents are same as in imagenet.cpp fiel along with CMakelist.txt file?
   P.S: My idea is to do the kind of my-recognition code or the imagenet.cpp to the live camera feed, instead of only calling up single images like, polar.jpg etc.

2. Is it possible to implement the image detection and object detection in C language , instead of C++ and Python codes?

3. when I follow the steps and the codes as in this query thread, Jetson Nano Object Detection C/C++ Example - #7 by dusty_nv

I am having multiple issues. Would you mind helping me with figuring it out please.

I did the

cmake .
make
make VERBOSE=1

the test file at this point had the code of this thread: Jetson Nano Object Detection C/C++ Example - #9 by dusty_nv

so removed the line : printf(" depth: %u (bpp)\n \n", camera->GetPixelDepth());

and then ~/test

$ ./test --width=640 --height=480

This the error I am facing.

Later I changed the test file to this

include “jetson-utils/gstCamera.h”
include “jetson-utils/glDisplay.h”
include “cudaFont.h”

include “jetson-inference/imageNet.h”
include “jetson-utils/commandLine.h”

include <signal.h>

include <jetson-inference/detectNet.h>

bool signal_recieved = false;

void sig_handler(int signo)
{
if( signo == SIGINT )
{
LogVerbose(“received SIGINT\n”);
signal_recieved = true;
}
}

int usage()
{
printf(“usage: imagenet [–help] [–network=NETWORK] …\n”);
printf(" input_URI [output_URI]\n\n");
printf(“Classify a video/image stream using an image recognition DNN.\n”);
printf(“See below for additional arguments that may not be shown above.\n\n”);
printf(“positional arguments:\n”);
printf(" input_URI resource URI of input stream (see videoSource below)\n");
printf(" output_URI resource URI of output stream (see videoOutput below)\n\n");
printf(“%s”, imageNet::Usage());
printf(“%s”, videoSource::Usage());
printf(“%s”, videoOutput::Usage());
printf(“%s”, Log::Usage());
return 0;
}

int main( int argc, char** argv )
{
/*

• parse command line
  */
  commandLine cmdLine(argc, argv);

if( cmdLine.GetFlag(“help”) )
return usage();

/*

• attach signal handler
  */
  if( signal(SIGINT, sig_handler) == SIG_ERR )
  LogError(“can’t catch SIGINT\n”);

/*

• create input stream
  /
  videoSource input = videoSource::Create(cmdLine, ARG_POSITION(0));

if( !input )
{
LogError(“imagenet: failed to create input stream\n”);
return 1;
}

/*

• create output stream

/
videoOutput output = videoOutput::Create(cmdLine, ARG_POSITION(1));

if( !output )
LogError(“imagenet: failed to create output stream\n”);

/*

• create font for image overlay
  /
  cudaFont font = cudaFont::Create();

if( !font )
{
LogError(“imagenet: failed to load font for overlay\n”);
return 1;
}

/*

• create recognition network
  /
  imageNet net = imageNet::Create(cmdLine);

if( !net )
{
LogError(“imagenet: failed to initialize imageNet\n”);
return 1;
}

/*

• processing loop
  /
  while( !signal_recieved )
  {
  // capture next image image
  uchar3 image = NULL;

  if( !input->Capture(&image, 1000) )
  {
  // check for EOS
  if( !input->IsStreaming() )
  break;

   LogError("imagenet:  failed to capture next frame\n");
   continue;
  

  }

  // classify image
  float confidence = 0.0f;
  const int img_class = net->Classify(image, input->GetWidth(), input->GetHeight(), &confidence);

  if( img_class >= 0 )
  {
  LogVerbose(“imagenet: %2.5f%% class #%i (%s)\n”, confidence * 100.0f, img_class, net->GetClassDesc(img_class));

   // overlay class label onto original image
   char str[256];
   sprintf(str, "%05.2f%% %s", confidence * 100.0f, net->GetClassDesc(img_class));
   font->OverlayText(image, input->GetWidth(), input->GetHeight(),
   			   str, 5, 5, make_float4(255, 255, 255, 255), make_float4(0, 0, 0, 100));
  

  }

  // render outputs
  if( output != NULL )
  {
  output->Render(image, input->GetWidth(), input->GetHeight());

   // update status bar
   char str[256];
   sprintf(str, "TensorRT %i.%i.%i | %s | Network %.0f FPS", NV_TENSORRT_MAJOR, NV_TENSORRT_MINOR, NV_TENSORRT_PATCH, net->GetNetworkName(), net->GetNetworkFPS());
   output->SetStatus(str);	
  
   // check if the user quit
   if( !output->IsStreaming() )
   	signal_recieved = true;
  

  }

  // print out timing info
  net->PrintProfilerTimes();
  }

/*

• destroy resources
  */
  LogVerbose(“imagenet: shutting down…\n”);

SAFE_DELETE(input);
SAFE_DELETE(output);
SAFE_DELETE(net);

LogVerbose(“imagenet: shutdown complete.\n”);
return 0;
}

and the CMAKELIST.TXT file contains the following

cmake_minimum_required(VERSION 2.8)

include_directories(${PROJECT_INCLUDE_DIR} ${PROJECT_INCLUDE_DIR}/jetson-inference ${PROJECT_INCLUDE_DIR}/jetson-utils)
include_directories(/usr/include/gstreamer-1.0 /usr/lib/aarch64-linux-gnu/gstreamer-1.0/include /usr/include/glib-2.0 /usr/include/libxml2 /usr/lib/aarch64-linux-gnu/glib-2.0/include/ /usr/local/include/jetson-utils)

//declare my-recognition project
project(test)

file(GLOB imagenetCameraSources *.cpp)
file(GLOB imagenetCameraIncludes *.h )

find_package(jetson-utils)
find_package(jetson-inference)
find_package(CUDA)

//add directory for libnvbuf-utils to program
link_directories(/usr/lib/aarch64-linux-gnu/tegra)

cuda_add_executable(test ${imagenetCameraSources})

target_link_libraries(test jetson-inference)

install(TARGETS test DESTINATION bin)

if I run

$./test --width=640 --height=480 --threshold=0.2 through SSH remote

I am totally lost. Kindly excuse my lack of knowledge in this stream.

Regards,
Karishma