[OpenGL] failed to create X11 Window

willemvdkletersteeg · February 9, 2021, 10:07am

I am trying to get object detection running on my Xavier NX but somehow I can’t get the output on my display (HDMI monitor). When I supply a file for output it works fine.

Output:

    [OpenGL] glDisplay -- X screen 0 resolution:  2560x1440
    [OpenGL] glDisplay -- X window resolution:    2560x1440
    [OpenGL] failed to create X11 Window.
    jetson.utils -- no output streams, creating fake null output

After which it will render to a fake output.

The code is mainly copied from this:

github.com

dusty-nv/jetson-inference/blob/master/docs/detectnet-console-2.md

<img src="https://github.com/dusty-nv/jetson-inference/raw/master/docs/images/deep-vision-header.jpg" width="100%">
<p align="right"><sup><a href="imagenet-camera-2.md">Back</a> | <a href="detectnet-camera-2.md">Next</a> | </sup><a href="../README.md#hello-ai-world"><sup>Contents</sup></a>
<br/>
<sup>Object Detection</sup></s></p>

# Locating Objects with DetectNet
The previous recognition examples output class probabilities representing the entire input image.  Next we're going to focus on **object detection**, and finding where in the frame various objects are located by extracting their bounding boxes.  Unlike image classification, object detection networks are capable of detecting many different objects per frame.

<img src="https://github.com/dusty-nv/jetson-inference/raw/dev/docs/images/detectnet.jpg" >

The [`detectNet`](../c/detectNet.h) object accepts an image as input, and outputs a list of coordinates of the detected bounding boxes along with their classes and confidence values.  [`detectNet`](../c/detectNet.h) is available to use from [Python](https://rawgit.com/dusty-nv/jetson-inference/python/docs/html/python/jetson.inference.html#detectNet) and [C++](../c/detectNet.h).  See below for various [pre-trained detection models](#pre-trained-detection-models-available)  available for download.  The default model used is a [91-class](../data/networks/ssd_coco_labels.txt) SSD-Mobilenet-v2 model trained on the MS COCO dataset, which achieves realtime inferencing performance on Jetson with TensorRT. 

As examples of using the `detectNet` class, we provide sample programs for C++ and Python:

- [`detectnet.cpp`](../examples/detectnet/detectnet.cpp) (C++) 
- [`detectnet.py`](../python/examples/detectnet.py) (Python) 

These samples are able to detect objects in images, videos, and camera feeds.  For more info about the various types of input/output streams supported, see the [Camera Streaming and Multimedia](aux-streaming.md) page.

### Detecting Objects from Images

This file has been truncated. show original

I have found similar topics but none of them contain a conclusive solution… I have tried
$ export DISPLAY=:0
with no result. How can I try to troubleshoot this?

Honey_Patouceul · February 9, 2021, 11:38am

Not sure for your case, but I’ve faced the same once when using a RTSP video source.
I can’t tell what was the root cause, but the workaround was to create the GL sink before the video source.

willemvdkletersteeg · February 9, 2021, 3:00pm

Jep! That worked. Who would’ve thought… Such a simpel solution. I’ve declared output first, then input, now it works. Thanks!