Install libgtk2.0-dev and pkg-config, then re-run cmake or configure script in function ‘cvWaitKey’

Issue Overview

Users are experiencing issues when attempting to run OpenCV applications on the Nvidia Jetson Orin Nano Dev board using a PyTorch Docker image (nvcr.io/nvidia/pytorch:24.05-py3-igpu). The specific error message encountered is:

cv2.error: OpenCV(4.7.0) /opencv-4.7.0/modules/highgui/src/window.cpp:1338: error: (-2:Unspecified error) The function is not implemented. Rebuild the library with Windows, GTK+ 2.x or Cocoa support.

This issue arises when executing a sample OpenCV program (test_cam.py) that attempts to display video from two camera sources using the GStreamer backend. The problem occurs consistently when the cv2.waitKey() function is called, indicating that the necessary GUI support for OpenCV is missing.

The user has installed opencv-python==4.8.0.74 but continues to face errors related to GUI functionality, suggesting that the library may not have been built with the required support for GTK+.

Possible Causes

• Missing Dependencies: The absence of libgtk2.0-dev and pkg-config can prevent OpenCV from utilizing GUI features.

• Incorrect OpenCV Build: The installed version of OpenCV may not have been compiled with support for GUI frameworks like GTK+, leading to the observed errors.

• Docker Environment Limitations: Running applications inside a Docker container can sometimes restrict access to graphical interfaces unless configured correctly.

• Version Mismatch: The user is running OpenCV version 4.7.0, while they mentioned installing opencv-python==4.8.0.74, which may indicate a version conflict or improper installation.

Troubleshooting Steps, Solutions & Fixes

1. Install Required Packages:
   To ensure that all necessary dependencies are installed, run the following command in your terminal:

   sudo apt-get install libgtk2.0-dev pkg-config
   

2. Rebuild OpenCV:
   If the above command does not resolve the issue, you may need to rebuild OpenCV with the correct flags for GUI support:

   • First, remove existing installations of OpenCV:

     pip uninstall opencv-python opencv-python-headless
     

   • Clone the OpenCV repository and build it:

     git clone https://github.com/opencv/opencv.git
     cd opencv
     mkdir build
     cd build
     cmake -D WITH_GTK=ON ..
     make -j$(nproc)
     sudo make install
     

3. Check Docker Configuration:
   Ensure that your Docker container has access to the X11 server for GUI applications:

   • Run your Docker container with the following flags:

     docker run -it --rm --runtime=nvidia --gpus all \
       -e DISPLAY=$DISPLAY \
       -v /tmp/.X11-unix:/tmp/.X11-unix \
       nvcr.io/nvidia/pytorch:24.05-py3-igpu
     

4. Test with a Simple Script:
   After installing dependencies and rebuilding OpenCV, test with a minimal script to verify that cv2.imshow() works correctly:

   import cv2
   import numpy as np
   
   img = np.zeros((512, 512, 3), np.uint8)
   cv2.imshow('Test Image', img)
   cv2.waitKey(0)
   cv2.destroyAllWindows()
   

5. Verify Installation:
   Check if OpenCV was built with GTK+ support using:

   import cv2
   print(cv2.getBuildInformation())
   

   Look for "GUI" in the output; it should indicate GTK+ support.

6. Reinstalling Specific Versions:
   If issues persist, consider installing a specific version of OpenCV known to work well in your environment:

   pip install opencv-python==4.5.3.20210927  # Example version; adjust as needed.
   

7. Consult Documentation:
   Refer to the official OpenCV documentation and Nvidia forums for additional guidance on compatibility and installation instructions specific to Jetson devices.

By following these steps, users should be able to resolve the issues related to GUI functionality in their OpenCV applications on the Nvidia Jetson Orin Nano Dev board. If problems persist after these troubleshooting steps, further investigation into specific environment configurations may be necessary.