I’m running n8n in Docker with Node.js v20 and cannot install opencv4nodejs due to an ‘idealTree already exists’ error and missing library directories. Any fixes?
I’ve faced similar issues with opencv4nodejs in Docker environments before. From my experience, the ‘idealTree already exists’ error often stems from npm cache conflicts. Have you tried clearing the npm cache and rebuilding?
Another approach that worked for me was manually installing the required system libraries before attempting the opencv4nodejs installation. Make sure you have build-essential, cmake, and libopencv-dev installed in your Docker image.
If those don’t work, you might need to downgrade Node.js to an earlier LTS version. opencv4nodejs can be finnicky with newer Node versions. I’ve had success with Node 16 in similar setups.
Lastly, consider using a pre-built opencv4nodejs Docker image as a base for your n8n container. It can save a lot of headaches with dependency issues.
I’ve run into this exact problem before with opencv4nodejs in Docker. It’s a real pain, but I found a workaround that might help you out.
First, try using the --build-from-source flag when installing opencv4nodejs. This bypasses some of the pre-built binaries that can cause issues.
If that doesn’t work, you might need to set up a custom Dockerfile. Include steps to install all the necessary dependencies before npm install. I had to add libgl1-mesa-dev and libglib2.0-0 to get things working.
Another trick is to use the OPENCV4NODEJS_DISABLE_AUTOBUILD environment variable. Set it to 1 before installation. This forces it to use system-wide OpenCV libraries instead of trying to build its own.
Lastly, if all else fails, consider using a different image processing library altogether. Sharp or Jimp are good alternatives that don’t have as many installation headaches in Docker environments.
hey dave, i ran into similar probs. try using node:16-buster as ur base image instead. it’s got the right libs pre-installed. Also, add RUN apt-get update && apt-get install -y libgl1-mesa-dev to ur Dockerfile. that fixed it for me. good luck!