Jupyter-CTPO infotrend/ctpo-jupyter-cuda_tensorflow_pytorch_opencv-unraid https://hub.docker.com/r/infotrend/ctpo-jupyter-cuda_tensorflow_pytorch_opencv-unraid bridge bash false https://forums.unraid.net/topic/148667-support-infotrendctpo-cuda-tensorflow-pytorch-opencv/ https://github.com/Infotrend-Inc/CTPO Unraid compatible Jupyter Lab (Python kernel) container with GPU-optimized Tensorflow, PyTorch and OpenCV. The default password to access the Jupyter Lab is iti This is the GPU-bound container's version. Please note that the container images is large at over 18GB To use it requires the Nvidia driver installation on your Unraid server for support of Docker. This installation needs to support the version of CUDA installed to use with this container. If you have multiple GPUs in your system with some allocated to VMs, make sure to replace --gpus all with --runtime=nvidia and add the NVIDIA_DRIVER_CAPABILITIES and NVIDIA_VISIBLE_DEVICES environment variables to only give the container access to selected GPUs. A CPU equivalent container is also available and named Jupyter-TPO and is over 5GB The system is ran as the jupyter user (has sudo privileges) and /iti is where you can place your weights and other files to support your development. Please see https://github.com/Infotrend-Inc/CTPO for further details. Productivity: http://[IP]:[PORT:8888] https://github.com/Infotrend-Inc/CTPO/blob/main/assets/Infotrend_LogoOnly.png?raw=true --gpus all 8888 /mnt/user/appdata/jupyter_ctpo/iti /mnt/user/appdata/jupyter_ctpo/home