How does one encode and stream detectnet object detection video over network using the dusty-jetson-inference repo?

I have followed the two days to a demo tutorial posted at: https://developer.nvidia.com/embedded/twodaystoademo

I have everything up and running and am able to detect various objects using the stream from a usb camera which is then displayed in an OpenGl window. I now need to stream this feed over the local network to a recording server. Can anybody help point in the right direction? Are there libraries available in the dusty-jetson-inference repo which will allow me to do this? or am I going to need to write my own code using libavcodec to encode the generated frames into a video stream? Or is there a way to send the camera feed with the overlayed detection boxes over the network using gstreamer?

Thanks

Hi kcrossman, libavcodec (ffmpeg) doesn’t utilize Jetson’s video codec hardware, so it will be slow to encode.

The jetson-utils repo has a gstEncoder class which can write to a compressed video file or over the network via RTP/RTSP. The dev branch of jetson-inference is currently setup to build jetson-utils as a submodule, (the master branch is currently in the process of migrating to using it as a submodule).

You would need to integrate and test the gstEncoder class in your program of choice, as you mention the samples output to OpenGL display today.

Note that gstEncoder expects the input frames in I420 colorspace format, so you will need to use these functions from cudaYUV.h to convert them from RGBA colorspace first.

Thanks for the speedy reply.

Ok I see, this will be a great help.

Is there any example code available as a starting point of how to implement the gstEncoder class to stream the video with bounding boxes over RTP?

Hi,

I was able to pull the dev branch of the jetson-interface repo build and deploy using the standard detectnet-camera model.

I had to add “static” to the create methods of the gstENcoder.h file otherwise I would receive the error " “cannot call gstEncoder function without object”.

I then went into the Camera.cpp to attempt to initialize the gstEncode as follows:

/*
 * Copyright (c) 2017, NVIDIA CORPORATION. All rights reserved.
 *
 * Permission is hereby granted, free of charge, to any person obtaining a
 * copy of this software and associated documentation files (the "Software"),
 * to deal in the Software without restriction, including without limitation
 * the rights to use, copy, modify, merge, publish, distribute, sublicense,
 * and/or sell copies of the Software, and to permit persons to whom the
 * Software is furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL
 * THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
 * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
 * DEALINGS IN THE SOFTWARE.
 */

#include "gstCamera.h"

#include "glDisplay.h"
#include "glTexture.h"

#include <stdio.h>
#include <signal.h>
#include <unistd.h>

#include "cudaMappedMemory.h"
#include "cudaNormalize.h"
#include "cudaFont.h"

#include "detectNet.h"
#include "gstEncoder.h"
#include "gstUtility.h"


#define DEFAULT_CAMERA 1	// -1 for onboard camera, or change to index of /dev/video V4L2 camera (>=0)
		

bool signal_recieved = false;

void sig_handler(int signo)
{
	if( signo == SIGINT )
	{
		printf("received SIGINT\n");
		signal_recieved = true;
	}
}


int main( int argc, char** argv )
{
	printf("detectnet-camera\n  args (%i):  ", argc);

	for( int i=0; i < argc; i++ )
		printf("%i [%s]  ", i, argv[i]);
		
	printf("\n\n");
	

	/*
	 * parse network type from CLI arguments
	 */
	/*detectNet::NetworkType networkType = detectNet::PEDNET_MULTI;

	if( argc > 1 )
	{
		if( strcmp(argv[1], "multiped") == 0 || strcmp(argv[1], "pednet") == 0 || strcmp(argv[1], "multiped-500") == 0 )
			networkType = detectNet::PEDNET_MULTI;
		else if( strcmp(argv[1], "ped-100") == 0 )
			networkType = detectNet::PEDNET;
		else if( strcmp(argv[1], "facenet") == 0 || strcmp(argv[1], "facenet-120") == 0 || strcmp(argv[1], "face-120") == 0 )
			networkType = detectNet::FACENET;
	}*/
	
	if( signal(SIGINT, sig_handler) == SIG_ERR )
		printf("\ncan't catch SIGINT\n");


	/*
	 * create the camera device
	 */
	gstCamera* camera = gstCamera::Create(DEFAULT_CAMERA);
	gstEncoder* enc = gstEncoder::Create(GST_CODEC_H264,1280,720,"192.168.108.163",8080);

	
	if( !camera )
	{
		printf("\ndetectnet-camera:  failed to initialize video device\n");
		return 0;
	}
	
	printf("\ndetectnet-camera:  successfully initialized video device\n");
	printf("    width:  %u\n", camera->GetWidth());
	printf("   height:  %u\n", camera->GetHeight());
	printf("    depth:  %u (bpp)\n\n", camera->GetPixelDepth());
	

	/*
	 * create detectNet
	 */
	detectNet* net = detectNet::Create(argc, argv);
	
	if( !net )
	{
		printf("detectnet-camera:   failed to initialize imageNet\n");
		return 0;
	}


	/*
	 * allocate memory for output bounding boxes and class confidence
	 */
	const uint32_t maxBoxes = net->GetMaxBoundingBoxes();		printf("maximum bounding boxes:  %u\n", maxBoxes);
	const uint32_t classes  = net->GetNumClasses();
	
	float* bbCPU    = NULL;
	float* bbCUDA   = NULL;
	float* confCPU  = NULL;
	float* confCUDA = NULL;
	
	if( !cudaAllocMapped((void**)&bbCPU, (void**)&bbCUDA, maxBoxes * sizeof(float4)) ||
	    !cudaAllocMapped((void**)&confCPU, (void**)&confCUDA, maxBoxes * classes * sizeof(float)) )
	{
		printf("detectnet-console:  failed to alloc output memory\n");
		return 0;
	}
	

	/*
	 * create openGL window
	 */
	glDisplay* display = glDisplay::Create();
	glTexture* texture = NULL;
	
	if( !display ) {
		printf("\ndetectnet-camera:  failed to create openGL display\n");
	}
	else
	{
		texture = glTexture::Create(camera->GetWidth(), camera->GetHeight(), GL_RGBA32F_ARB/*GL_RGBA8*/);

		if( !texture )
			printf("detectnet-camera:  failed to create openGL texture\n");
	}
	
	
	/*
	 * create font
	 */
	cudaFont* font = cudaFont::Create();
	

	/*
	 * start streaming
	 */
	if( !camera->Open() )
	{
		printf("\ndetectnet-camera:  failed to open camera for streaming\n");
		return 0;
	}
	
	printf("\ndetectnet-camera:  camera open for streaming\n");
	//const size_t texSz = camera->GetWidth() * camera->GetHeight() * 3 / 2;
	
	/*
	 * processing loop
	 */
	float confidence = 0.0f;
	
	while( !signal_recieved )
	{
		void* imgCPU  = NULL;
		void* imgCUDA = NULL;
		
		// get the latest frame
		if( !camera->Capture(&imgCPU, &imgCUDA, 1000) )
			printf("\ndetectnet-camera:  failed to capture frame\n");

		// convert from YUV to RGBA
		void* imgRGBA = NULL;
		
		if( !camera->ConvertRGBA(imgCUDA, &imgRGBA) )
			printf("detectnet-camera:  failed to convert from NV12 to RGBA\n");

		// classify image with detectNet
		int numBoundingBoxes = maxBoxes;
	
		if( net->Detect((float*)imgRGBA, camera->GetWidth(), camera->GetHeight(), bbCPU, &numBoundingBoxes, confCPU))
		{
			printf("%i bounding boxes detected\n", numBoundingBoxes);
		
			int lastClass = 0;
			int lastStart = 0;
			
			for( int n=0; n < numBoundingBoxes; n++ )
			{
				const int nc = confCPU[n*2+1];
				float* bb = bbCPU + (n * 4);
				
				printf("bounding box %i   (%f, %f)  (%f, %f)  w=%f  h=%f\n", n, bb[0], bb[1], bb[2], bb[3], bb[2] - bb[0], bb[3] - bb[1]); 
				
				if( nc != lastClass || n == (numBoundingBoxes - 1) )
				{
					if( !net->DrawBoxes((float*)imgRGBA, (float*)imgRGBA, camera->GetWidth(), camera->GetHeight(), 
						                        bbCUDA + (lastStart * 4), (n - lastStart) + 1, lastClass) )
						printf("detectnet-console:  failed to draw boxes\n");
						
					lastClass = nc;
					lastStart = n;

					CUDA(cudaDeviceSynchronize());
				}
			}
		
			/*if( font != NULL )
			{
				char str[256];
				sprintf(str, "%05.2f%% %s", confidence * 100.0f, net->GetClassDesc(img_class));
				
				font->RenderOverlay((float4*)imgRGBA, (float4*)imgRGBA, camera->GetWidth(), camera->GetHeight(),
								    str, 10, 10, make_float4(255.0f, 255.0f, 255.0f, 255.0f));
			}*/
			
			if( display != NULL )
			{
				char str[256];
				sprintf(str, "TensorRT %i.%i.%i | %s | %04.1f FPS", NV_TENSORRT_MAJOR, NV_TENSORRT_MINOR, NV_TENSORRT_PATCH, precisionTypeToStr(net->GetPrecision()), display->GetFPS());
				display->SetTitle(str);	
			}	
		}	


		// update display
		if( display != NULL )
		{
			//enc->EncodeFrame((float4*)imgRGBA,texSz);
			display->UserEvents();
			display->BeginRender();

			if( texture != NULL )
			{
				// rescale image pixel intensities for display
				CUDA(cudaNormalizeRGBA((float4*)imgRGBA, make_float2(0.0f, 255.0f), 
								   (float4*)imgRGBA, make_float2(0.0f, 1.0f), 
		 						   camera->GetWidth(), camera->GetHeight()));

				// map from CUDA to openGL using GL interop
				void* tex_map = texture->MapCUDA();

				if( tex_map != NULL )
				{
					cudaMemcpy(tex_map, imgRGBA, texture->GetSize(), cudaMemcpyDeviceToDevice);
					texture->Unmap();
				}

				// draw the texture
				texture->Render(100,100);		
			}

			display->EndRender();
		}
	}
	
	printf("\ndetectnet-camera:  un-initializing video device\n");
	
	
	/*
	 * shutdown the camera device
	 */
	if( camera != NULL )
	{
		delete camera;
		camera = NULL;
	}

	if( display != NULL )
	{
		delete display;
		display = NULL;
	}
	
	printf("detectnet-camera:  video device has been un-initialized.\n");
	printf("detectnet-camera:  this concludes the test of the video device.\n");
	return 0;
}

I essentially added “gstEncoder* enc = gstEncoder::Create(GST_CODEC_H264,1280,720,“192.168.108.163”,8080);” as a test.

I was then able to rebuild the project. However when I try and run ./detectnet-camera I get an error in the terminal “Segmentation fault (core dumped)”

What could be causing this? A quick google states that it is trying to access memory it does not have memory to. But I am not sure why this is happening.

Thanks

It looks like it has some problem creating the encoder, I will have to debug it sometime.

I remembered there is also this fork of jetson-inference with RTP streaming: https://github.com/Abaco-Systems/jetson-inference-gv

There may be repos with network streaming working if you look around the forks.

Ok,

Was gstEncoder tested as working? As I see in this thread: https://devtalk.nvidia.com/default/topic/1038377/video-encode-error/?offset=10# it appears to run.

could it be something on my side?

It appears that whenever any of the variables declared under Private in gstEncoder.h are accessed, it causes the segmentation fault. Why would this be? I have checked the other classes like gstCamera and they are structured in the exact same manner?

I would greatly appreciate it if we could debug this as it is the only thing holding me back from completing this project.

OK, I made some fixes to gstEncoder and added RGBA->I420 colorspace conversion into the class.

Tested it by outputting a test MP4 file to disk, working for both H.264 and H.265 codecs.

Re-clone the jetson-inference dev branch, and here is the detectnet-camera.cpp test code:

/*
 * Copyright (c) 2017, NVIDIA CORPORATION. All rights reserved.
 *
 * Permission is hereby granted, free of charge, to any person obtaining a
 * copy of this software and associated documentation files (the "Software"),
 * to deal in the Software without restriction, including without limitation
 * the rights to use, copy, modify, merge, publish, distribute, sublicense,
 * and/or sell copies of the Software, and to permit persons to whom the
 * Software is furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL
 * THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
 * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
 * DEALINGS IN THE SOFTWARE.
 */

#include "gstCamera.h"

#include "glDisplay.h"
#include "glTexture.h"

#include <stdio.h>
#include <signal.h>
#include <unistd.h>

#include "cudaMappedMemory.h"
#include "cudaNormalize.h"
#include "cudaFont.h"

#include "detectNet.h"
#include "gstEncoder.h"
#include "gstUtility.h"

#define DEFAULT_CAMERA -1	// -1 for onboard camera, or change to index of /dev/video V4L2 camera (>=0)
		

bool signal_recieved = false;

void sig_handler(int signo)
{
	if( signo == SIGINT )
	{
		printf("received SIGINT\n");
		signal_recieved = true;
	}
}

int main( int argc, char** argv )
{
	printf("detectnet-camera\n  args (%i):  ", argc);

	for( int i=0; i < argc; i++ )
		printf("%i [%s]  ", i, argv[i]);
		
	printf("\n\n");
	

	/*
	 * parse network type from CLI arguments
	 */
	/*detectNet::NetworkType networkType = detectNet::PEDNET_MULTI;

	if( argc > 1 )
	{
		if( strcmp(argv[1], "multiped") == 0 || strcmp(argv[1], "pednet") == 0 || strcmp(argv[1], "multiped-500") == 0 )
			networkType = detectNet::PEDNET_MULTI;
		else if( strcmp(argv[1], "ped-100") == 0 )
			networkType = detectNet::PEDNET;
		else if( strcmp(argv[1], "facenet") == 0 || strcmp(argv[1], "facenet-120") == 0 || strcmp(argv[1], "face-120") == 0 )
			networkType = detectNet::FACENET;
	}*/
	
	if( signal(SIGINT, sig_handler) == SIG_ERR )
		printf("\ncan't catch SIGINT\n");

	/*
	 * create the camera device
	 */
	gstCamera* camera = gstCamera::Create(DEFAULT_CAMERA);
	
	if( !camera )
	{
		printf("\ndetectnet-camera:  failed to initialize video device\n");
		return 0;
	}
	
	printf("\ndetectnet-camera:  successfully initialized video device\n");
	printf("    width:  %u\n", camera->GetWidth());
	printf("   height:  %u\n", camera->GetHeight());
	printf("    depth:  %u (bpp)\n\n", camera->GetPixelDepth());
	

	/*
	 * create the video encoder
	 */
	gstEncoder* encoder = gstEncoder::Create(GST_CODEC_H264, camera->GetWidth(), camera->GetHeight(), "test.mp4"/*"192.168.108.163",8080*/);

	if( !encoder )
	{
		printf("detectnet-camera:  failed to initialize gstEncoder\n");
		return 0;
	}

	/*
	 * create detectNet
	 */
	detectNet* net = detectNet::Create(argc, argv);
	
	if( !net )
	{
		printf("detectnet-camera:   failed to initialize imageNet\n");
		return 0;
	}

	/*
	 * allocate memory for output bounding boxes and class confidence
	 */
	const uint32_t maxBoxes = net->GetMaxBoundingBoxes();		printf("maximum bounding boxes:  %u\n", maxBoxes);
	const uint32_t classes  = net->GetNumClasses();
	
	float* bbCPU    = NULL;
	float* bbCUDA   = NULL;
	float* confCPU  = NULL;
	float* confCUDA = NULL;
	
	if( !cudaAllocMapped((void**)&bbCPU, (void**)&bbCUDA, maxBoxes * sizeof(float4)) ||
	    !cudaAllocMapped((void**)&confCPU, (void**)&confCUDA, maxBoxes * classes * sizeof(float)) )
	{
		printf("detectnet-console:  failed to alloc output memory\n");
		return 0;
	}
	

	/*
	 * create openGL window
	 */
	glDisplay* display = glDisplay::Create();
	glTexture* texture = NULL;
	
	if( !display ) {
		printf("\ndetectnet-camera:  failed to create openGL display\n");
	}
	else
	{
		texture = glTexture::Create(camera->GetWidth(), camera->GetHeight(), GL_RGBA32F_ARB/*GL_RGBA8*/);

		if( !texture )
			printf("detectnet-camera:  failed to create openGL texture\n");
	}
	
	
	/*
	 * create font
	 */
	cudaFont* font = cudaFont::Create();
	

	/*
	 * start streaming
	 */
	if( !camera->Open() )
	{
		printf("\ndetectnet-camera:  failed to open camera for streaming\n");
		return 0;
	}
	
	printf("\ndetectnet-camera:  camera open for streaming\n");
	//const size_t texSz = camera->GetWidth() * camera->GetHeight() * 3 / 2;
	
	/*
	 * processing loop
	 */
	float confidence = 0.0f;
	
	while( !signal_recieved )
	{
		void* imgCPU  = NULL;
		void* imgCUDA = NULL;
		
		// get the latest frame
		if( !camera->Capture(&imgCPU, &imgCUDA, 1000) )
			printf("\ndetectnet-camera:  failed to capture frame\n");

		// convert from YUV to RGBA
		void* imgRGBA = NULL;
		
		if( !camera->ConvertRGBA(imgCUDA, &imgRGBA) )
			printf("detectnet-camera:  failed to convert from NV12 to RGBA\n");

		// classify image with detectNet
		int numBoundingBoxes = maxBoxes;
	
		if( net->Detect((float*)imgRGBA, camera->GetWidth(), camera->GetHeight(), bbCPU, &numBoundingBoxes, confCPU))
		{
			printf("%i bounding boxes detected\n", numBoundingBoxes);
		
			int lastClass = 0;
			int lastStart = 0;
			
			for( int n=0; n < numBoundingBoxes; n++ )
			{
				const int nc = confCPU[n*2+1];
				float* bb = bbCPU + (n * 4);
				
				printf("bounding box %i   (%f, %f)  (%f, %f)  w=%f  h=%f\n", n, bb[0], bb[1], bb[2], bb[3], bb[2] - bb[0], bb[3] - bb[1]); 
				
				if( nc != lastClass || n == (numBoundingBoxes - 1) )
				{
					if( !net->DrawBoxes((float*)imgRGBA, (float*)imgRGBA, camera->GetWidth(), camera->GetHeight(), 
						                        bbCUDA + (lastStart * 4), (n - lastStart) + 1, lastClass) )
						printf("detectnet-console:  failed to draw boxes\n");
						
					lastClass = nc;
					lastStart = n;

					CUDA(cudaDeviceSynchronize());
				}
			}
		
			/*if( font != NULL )
			{
				char str[256];
				sprintf(str, "%05.2f%% %s", confidence * 100.0f, net->GetClassDesc(img_class));
				
				font->RenderOverlay((float4*)imgRGBA, (float4*)imgRGBA, camera->GetWidth(), camera->GetHeight(),
								    str, 10, 10, make_float4(255.0f, 255.0f, 255.0f, 255.0f));
			}*/
			
			if( display != NULL )
			{
				char str[256];
				sprintf(str, "TensorRT %i.%i.%i | %s | %04.1f FPS", NV_TENSORRT_MAJOR, NV_TENSORRT_MINOR, NV_TENSORRT_PATCH, precisionTypeToStr(net->GetPrecision()), display->GetFPS());
				display->SetTitle(str);	
			}	
		}	

		// update encoder
		if( encoder != NULL )
		{
			if( !encoder->EncodeRGBA((float*)imgRGBA) )
				printf("detectnet-console:  gstEncoder failed to encode frame\n");
		}

		// update display
		if( display != NULL )
		{
			//enc->EncodeFrame((float4*)imgRGBA,texSz);
			display->UserEvents();
			display->BeginRender();

			if( texture != NULL )
			{
				// rescale image pixel intensities for display
				CUDA(cudaNormalizeRGBA((float4*)imgRGBA, make_float2(0.0f, 255.0f), 
								   (float4*)imgRGBA, make_float2(0.0f, 1.0f), 
		 						   camera->GetWidth(), camera->GetHeight()));

				// map from CUDA to openGL using GL interop
				void* tex_map = texture->MapCUDA();

				if( tex_map != NULL )
				{
					cudaMemcpy(tex_map, imgRGBA, texture->GetSize(), cudaMemcpyDeviceToDevice);
					texture->Unmap();
				}

				// draw the texture
				texture->Render(100,100);		
			}

			display->EndRender();
		}
	}
	
	printf("\ndetectnet-camera:  un-initializing video device\n");
	
	
	/*
	 * shutdown the camera device
	 */
	if( encoder != NULL )
	{
		delete encoder;
		encoder = NULL;
	}

	if( camera != NULL )
	{
		delete camera;
		camera = NULL;
	}

	if( display != NULL )
	{
		delete display;
		display = NULL;
	}
	
	printf("detectnet-camera:  video device has been un-initialized.\n");
	printf("detectnet-camera:  this concludes the test of the video device.\n");
	return 0;
}

It outputs to test.mp4 in the aarch64/bin directory. Make sure to close the app with Ctrl+C in the console, if you close the GUI window itself right now, the stream doesn’t have a chance to close properly and the MP4 file will be corrupt.

Also I changed the DEFAULT_CAMERA define back to -1 in the code above, as I was working with the integrated camera.

Hi Dusty_NV,

I have pulled down the changes and am able to stream over the network and pickup the stream using gstreamer on a client PC.

I just have one more question. I am capturing the feed in program called Milestone. It however requires an RTSP server feed in the form of a uri similar to rtsp://192.168.108.193:8888/test. It is unable to pick up a feed which is just the IP address and port. It wants some sort of designation like “/test” in its connection uri.

I have found a gst-rtsp-server repo : https://github.com/GStreamer/gst-rtsp-server which is able to do this. Do you have any experience with this or any suggestions on how to include it?

Thanks

Good to hear that you were able to stream the compressed video over the network.

I haven’t personally used that gst-rtsp-server plugin before, and it looks like the rtsp elements that come with GStreamer out of the box are for receiving rtsp and not server.

If you are able to build and install that plugin, then what you will want to do is change out the rtp/udpsink portions of the gstEncoder pipeline here, and replace those with this new rtsp-server element in the pipeline string.

Would it be possible to use vlc instead of gstreamer? As vlc has the ability to create an RTSP server.

I am struggling to figure out how to include the gst-rtsp-server into the jetson-inference.

Thanks

VLC uses ffmpeg, and ffmpeg does not include support for the Tegra hw-accelerated video encoder/decoder engines. So it would use CPU only.

What I recommend doing, is getting a standalone test pipeline with gst-rtsp-server working first that you launch from the command line (using gst-launch-1.0). You can see other standalone test pipelines included in the L4T Accelerated GStreamer Guide. Some of them use the videotestsrc element, the camera, or a video input file to generate data.

Once you get a pipeline working with rtsp-server, you can modify the pipeline that jetson-inference uses to include this new element. The network portion of the pipeline is generated here in the code:

https://github.com/dusty-nv/jetson-utils/blob/acac0521371b710e64133b10cf86581d9d528a2a/codec/gstEncoder.cpp#L341

Right now it is setup to invoke RTP/UDP streaming using the rtph264pay and udpsink elements. You will want to replace those with your own elements from the rtsp-server pipeline that you create and test above.

I have managed to get everything working.

Thank you for your help!

Hello,

I am trying to do something similar to what ‘kcrossman’ created this thread for, i.e.streaming the video feed to network. I tried dusty_nv’s code fix that uses gstEncoder , for me it works for the save to disk, e.g. test.mp4 file, but when I try to run with the IP address and port to stream it on RTP, the console shows this kind of error continuously:

(detectnet-camera:31540): GStreamer-CRITICAL **: gst_segment_to_running_time: assertion 'segment->format == format' failed

When I am trying to run the stream from VLC media player, its also complaining about the format. Any help would be appreciated!!

Thanks,
-Shamoon.

Hi shamooon,
Here are two working cases of running gstreamer sample test-launch:
https://devtalk.nvidia.com/default/topic/1018689/jetson-tx2/vlc-playing-gstreamer-flow/post/5187270/#5187270
https://devtalk.nvidia.com/default/topic/1043770/jetson-tx2/problems-minimizing-latency-and-maximizing-quality-for-rtsp-and-mpeg-ts-/post/5295828/#5295828

You may refer to these along with dusty’s suggestion.