Failed to enable a V4l2 device with imagenet-camera

Robotics & Edge Computing Jetson & Embedded Systems Jetson TX2
1

Hi

Does imagenet-camera work with a V4l2 device on TX2(R28.1)?

We tried to use a V4l2 yuv camera and got error-“failed to open camera for streaming.”

We modified the DEFAULT_CAMERA to 0 and set gstreamer decoder pipeline string as teh following:
v4l2src device=/dev/video0" ! video/x-raw, width=(int)1920, height=(int)1080, format=(string)I420 ! nvvidconv ! video/x-raw(memory:NVMM) ! appsink name=mysink

Thank you for any advice.

Here is the error log.
nvidia@tegra-ubuntu:~/TR/jetson-inference/build/aarch64/bin$ ./imagenet-camera
imagenet-camera
args (1): 0 [./imagenet-camera]

[gstreamer] initialized gstreamer, version 1.8.3.0
[gstreamer] gstreamer decoder pipeline string:
v4l2src device=/dev/video0" ! video/x-raw, width=(int)1920, height=(int)1080, format=(string)I420 ! nvvidconv ! video/x-raw(memory:NVMM) ! appsink name=mysink

imagenet-camera: successfully initialized video device
width: 1920
height: 1080
depth: 24 (bpp)

imageNet – loading classification network model from:
– prototxt networks/googlenet.prototxt
– model networks/bvlc_googlenet.caffemodel
– class_labels networks/ilsvrc12_synset_words.txt
– input_blob ‘data’
– output_blob ‘prob’
– batch_size 2

[GIE] TensorRT version 2.1, build 2102
[GIE] attempting to open cache file networks/bvlc_googlenet.caffemodel.2.tensorcache
[GIE] loading network profile from cache… networks/bvlc_googlenet.caffemodel.2.tensorcache
[GIE] platform has FP16 support.
[GIE] networks/bvlc_googlenet.caffemodel loaded
[GIE] CUDA engine context initialized with 2 bindings
[GIE] networks/bvlc_googlenet.caffemodel input binding index: 0
[GIE] networks/bvlc_googlenet.caffemodel input dims (b=2 c=3 h=224 w=224) size=1204224
[cuda] cudaAllocMapped 1204224 bytes, CPU 0x102a00000 GPU 0x102a00000
[GIE] networks/bvlc_googlenet.caffemodel output 0 prob binding index: 1
[GIE] networks/bvlc_googlenet.caffemodel output 0 prob dims (b=2 c=1000 h=1 w=1) size=8000
[cuda] cudaAllocMapped 8000 bytes, CPU 0x102c00000 GPU 0x102c00000
networks/bvlc_googlenet.caffemodel initialized.
[GIE] networks/bvlc_googlenet.caffemodel loaded
imageNet – loaded 1000 class info entries
networks/bvlc_googlenet.caffemodel initialized.
default X screen 0: 1920 x 1200
[OpenGL] glDisplay display window initialized
[OpenGL] creating 1920x1080 texture
loaded image fontmapA.png (256 x 512) 2097152 bytes
[cuda] cudaAllocMapped 2097152 bytes, CPU 0x102e00000 GPU 0x102e00000
[cuda] cudaAllocMapped 8192 bytes, CPU 0x102c02000 GPU 0x102c02000
[gstreamer] gstreamer transitioning pipeline to GST_STATE_PLAYING
[gstreamer] gstreamer failed to set pipeline state to PLAYING (error 0)

imagenet-camera: failed to open camera for streaming

Thank you,

2

Hi,

Could you check if your v4l2 camera is indeed mounted at /dev/video0?
Sometimes the v4l2 camera is located at /dev/video1.

Thanks.

3

Hi AastaLLL,

Thanks for your prompt reply.

Yes. it’s at /dev/video0.
The /dev/video0 preview was ok by using the same gstreamer pipeline string.

Thank you,

4

Hi,

We just double checked jetson_infernce with a Logitech webcam.
We can open camera without issue. Here is our changes:

diff --git a/imagenet-camera/imagenet-camera.cpp b/imagenet-camera/imagenet-camera.cpp
index 24e25c6..fcdf8cb 100644
--- a/imagenet-camera/imagenet-camera.cpp
+++ b/imagenet-camera/imagenet-camera.cpp
@@ -34,7 +34,7 @@
 #include "imageNet.h"
 
 
-#define DEFAULT_CAMERA -1	// -1 for onboard camera, or change to index of /dev/video V4L2 camera (>=0)	
+#define DEFAULT_CAMERA 1	// -1 for onboard camera, or change to index of /dev/video V4L2 camera (>=0)

Could you clean build the project and try it again?
Thanks.

5

Hi AastaLLL,

Thank you for your support.
It works now.

Plus, does Face-recognition support a v4l2 device?

On the same Tx2, face-recognition failed to run with a v4l2 device and showed “cudaPreImageNetMean failed”.

Here is the error log.
nvidia@tegra-ubuntu:~/Face-Recognition/build/aarch64/bin$ ./face-recognition
Building and running a GPU inference engine for /home/nvidia/Face-Recognition/data/deploy.prototxt, N=1…
[gstreamer] initialized gstreamer, version 1.8.3.0
[gstreamer] gstreamer decoder pipeline string:
v4l2src device=/dev/video0 ! video/x-raw, width=(int)1920, height=(int)1080, format=(string)I420 ! videoconvert ! video/x-raw, format=RGB ! videoconvert ! appsink name=mysink
successfully initialized video device
width: 1920
height: 1080
depth: 24 (bpp)

Bindings after deserializing:
Binding 0 (data): Input.
Binding 1 (coverage_fd): Output.
Binding 2 (bboxes_fd): Output.
Binding 3 (count_fd): Output.
Binding 4 (bbox_fr): Output.
Binding 5 (bbox_id): Output.
Binding 6 (softmax_fr): Output.
Binding 7 (label): Output.
loaded image /home/nvidia/Face-Recognition/data/fontmapA.png (256 x 512) 2097152 bytes
[cuda] cudaAllocMapped 2097152 bytes, CPU 0x102a00000 GPU 0x102a00000
[cuda] cudaAllocMapped 8192 bytes, CPU 0x102c00000 GPU 0x102c00000
default X screen 0: 1920 x 1200
[OpenGL] glDisplay display window initialized
[OpenGL] creating 1920x1080 texture
[gstreamer] gstreamer transitioning pipeline to GST_STATE_PLAYING
[gstreamer] gstreamer changed state from NULL to READY ==> mysink
[gstreamer] gstreamer changed state from NULL to READY ==> videoconvert1
[gstreamer] gstreamer changed state from NULL to READY ==> capsfilter1
[gstreamer] gstreamer changed state from NULL to READY ==> videoconvert0
[gstreamer] gstreamer changed state from NULL to READY ==> capsfilter0
[gstreamer] gstreamer changed state from NULL to READY ==> v4l2src0
[gstreamer] gstreamer changed state from NULL to READY ==> pipeline0
[gstreamer] gstreamer changed state from READY to PAUSED ==> videoconvert1
[gstreamer] gstreamer changed state from READY to PAUSED ==> capsfilter1
[gstreamer] gstreamer changed state from READY to PAUSED ==> videoconvert0
[gstreamer] gstreamer changed state from READY to PAUSED ==> capsfilter0
[gstreamer] gstreamer stream status CREATE ==> src
[gstreamer] gstreamer changed state from READY to PAUSED ==> v4l2src0
[gstreamer] gstreamer changed state from READY to PAUSED ==> pipeline0
[gstreamer] gstreamer msg new-clock ==> pipeline0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> videoconvert1
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> capsfilter1
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> videoconvert0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> capsfilter0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> v4l2src0
[gstreamer] gstreamer stream status ENTER ==> src
[gstreamer] gstreamer msg stream-start ==> pipeline0
Allocate memory: input blob
Allocate memory: coverage
Allocate memory: box
Allocate memory: count
Allocate memory: selected bbox
Allocate memory: selected index
Allocate memory: softmax
Allocate memory: label
failed to capture frame
failed to convert from NV12 to RGBA
[cuda] cudaPreImageNetMean((float4*)imgRGBA, camera->GetWidth(), camera->GetHeight(), data, dimsData.w(), dimsData.h(), make_float3(127.0f, 127.0f, 127.0f))
[cuda] invalid device pointer (error 17) (hex 0x11)
[cuda] /home/nvidia/Face-Recognition/face-recognition/face-recognition.cpp:224
cudaPreImageNetMean failed

Thank you,

6

Hi,

Yes. Face recognition doesn’t support the v4l2 camera.
This sample targets for TensorRT plugin layer demonstration. We don’t enable it with v4l2 camera support.

Please refer to jeston_inference for the TensorRT+v4l2 camera use-case.
Thanks.

7

Hi AastaLLL,

Thank you for your information.
Will jeston_inference include Face recognition function in the future version?

Thank you,

8

Hi,

We don’t have such a plan.
Sorry for the inconvenience.

9

Thank you.