# Error trying to use OpenCV with CUDA support on Docker: CUDA driver version is insufficient for CUDA runtime version

**URL:** <https://forums.developer.nvidia.com/t/error-trying-to-use-opencv-with-cuda-support-on-docker-cuda-driver-version-is-insufficient-for-cuda-runtime-version/217168>\
**Category:** Jetson Nano\
**Tags:** opencv, docker, cuda\
**Created:** [June 10, 2022, 7:40am UTC](https://forums.developer.nvidia.com/t/error-trying-to-use-opencv-with-cuda-support-on-docker-cuda-driver-version-is-insufficient-for-cuda-runtime-version/217168 "2022-06-10T07:40:08Z")\
**Posts on this page:** 5\
**Page:** 1

<div class="post-metadata">

**Author:** ![florianC31](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@florianC31](https://forums.developer.nvidia.com/u/florianC31)\
**Post date:** [June 10, 2022, 7:40am UTC](https://forums.developer.nvidia.com/t/error-trying-to-use-opencv-with-cuda-support-on-docker-cuda-driver-version-is-insufficient-for-cuda-runtime-version/217168/1 "2022-06-10T07:40:08Z")

</div>

Hello,

I try to build a Docker image with OpenCV with CUDA support on my Jetson Nano GB Developer Kit.

I flashed the Jetpack 4.6.1 on the Jetson and I build a new docker image from the Nvidia L4T r32.7.1 docker image where I added openCV4.1.1 (the version included in the Jetpack 4.6.1) which I compiled with CUDA 10.2 support:

```auto
ARG L4T_FULL_VERSION=r32.7.1
ARG BASE_IMAGE=nvcr.io/nvidia/l4t-base:${L4T_FULL_VERSION}

FROM ${BASE_IMAGE} as base

ARG CUDA_VERSION=10.2
ARG OPENCV_VERSION=4.1.1
ARG L4T_MAJOR_VERSION=r32.7

WORKDIR /root

# reveal the CUDA location
RUN sh -c "echo '/usr/local/cuda/lib64' >> /etc/ld.so.conf.d/nvidia-tegra.conf"
RUN ldconfig

# install the dependencies
RUN apt-get update && apt-get install -q -y \
    dialog apt-utils \
    build-essential cmake git unzip pkg-config zlib1g-dev \
    libjpeg-dev libjpeg8-dev libjpeg-turbo8-dev libpng-dev libtiff-dev \
    libavcodec-dev libavformat-dev libswscale-dev libglew-dev \
    libgtk2.0-dev libgtk-3-dev libcanberra-gtk* \
    python-dev python-numpy python-pip \
    python3-dev python3-numpy python3-pip \
    libxvidcore-dev libx264-dev libgtk-3-dev \
    libtbb2 libtbb-dev libdc1394-22-dev libxine2-dev \
    gstreamer1.0-tools libv4l-dev v4l-utils v4l2ucp qv4l2 \
    libgstreamer-plugins-base1.0-dev libgstreamer-plugins-good1.0-dev \
    libavresample-dev libvorbis-dev libxine2-dev libtesseract-dev \
    libfaac-dev libmp3lame-dev libtheora-dev libpostproc-dev \
    libopencore-amrnb-dev libopencore-amrwb-dev \
    libopenblas-dev libatlas-base-dev libblas-dev \
    liblapack-dev liblapacke-dev libeigen3-dev gfortran \
    libhdf5-dev protobuf-compiler \
    libprotobuf-dev libgoogle-glog-dev libgflags-dev \
    && rm -rf /var/lib/apt/lists/*

# Install Cuda ToolKit
RUN echo "deb https://repo.download.nvidia.com/jetson/common $L4T_MAJOR_VERSION main" > /etc/apt/sources.list.d/nvidia-l4t-apt-source.list
RUN echo "deb https://repo.download.nvidia.com/jetson/t210 $L4T_MAJOR_VERSION main" >> /etc/apt/sources.list.d/nvidia-l4t-apt-source.list
RUN apt-key adv --fetch-key https://repo.download.nvidia.com/jetson/jetson-ota-public.asc
RUN apt-get update && apt-get install -q -y \  
    cuda-tools-10-2 cuda-libraries-10-2 \
    && rm -rf /var/lib/apt/lists/*

RUN ldconfig

# download the latest version
RUN wget -O opencv.zip https://github.com/opencv/opencv/archive/$OPENCV_VERSION.zip 
RUN wget -O opencv_contrib.zip https://github.com/opencv/opencv_contrib/archive/$OPENCV_VERSION.zip 
# unpack

RUN unzip opencv.zip && unzip opencv_contrib.zip && mv opencv-$OPENCV_VERSION opencv && mv opencv_contrib-$OPENCV_VERSION opencv_contrib && rm opencv.zip && rm opencv_contrib.zip

# set install dir
WORKDIR /root/opencv
RUN mkdir build
WORKDIR /root/opencv/build

# Reference: https://hub.docker.com/r/mdegans/tegra-opencv
# https://forums.developer.nvidia.com/t/opencv-4-2-0-and-cudnn-for-jetson-nano/112281/44
RUN cmake \
-D CMAKE_LIBRARY_PATH=/usr/local/cuda/lib64/stubs \
    -D BUILD_EXAMPLES=OFF \
    -D BUILD_opencv_python2=OFF \
    -D BUILD_opencv_python3=OFF \
    -D CMAKE_BUILD_TYPE=RELEASE \
    -D CMAKE_INSTALL_PREFIX=/usr/local \
    -D CUDA_ARCH_BIN=5.3,6.2,7.2 \
    -D CUDA_ARCH_PTX= \
    -D CUDA_FAST_MATH=ON \
    -D EIGEN_INCLUDE_PATH=/usr/include/eigen3 \
    -D ENABLE_NEON=ON \
    -D OPENCV_ENABLE_NONFREE=ON \
    -D OPENCV_EXTRA_MODULES_PATH=/root/opencv_contrib/modules \
    -D OPENCV_GENERATE_PKGCONFIG=ON \
    -D WITH_CUBLAS=ON \
    -D WITH_CUDA=ON \
# -D WITH_CUDNN=ON \
# -D CUDNN_VERSION='8.0' \
# -D OPENCV_DNN_CUDA=ON \
    -D WITH_GSTREAMER=ON \
    -D WITH_LIBV4L=ON \
    -D WITH_OPENGL=ON \
    -D INSTALL_C_EXAMPLES=OFF \
    -D INSTALL_TESTS=OFF \
    ..

# run make
RUN make -j1 && make install && make clean

RUN ldconfig

WORKDIR /root
RUN rm -R opencv opencv_contrib

ARG REVISION
LABEL revision=${REVISION}

```

The docker image is build without any issue. So, in order to check if everything was ok, I tried this code in the docker container of the built image :

```auto
#include <iostream>
using namespace std;

#include <opencv2/core.hpp>
using namespace cv;

#include <opencv2/cudaarithm.hpp>
using namespace cv::cuda;

int main()
{
    printShortCudaDeviceInfo(getDevice());
    int cuda_devices_number = getCudaEnabledDeviceCount();
    cout << "CUDA Device(s) Number: "<< cuda_devices_number << endl;
    DeviceInfo _deviceInfo;
    bool _isd_evice_compatible = _deviceInfo.isCompatible();
    cout << "CUDA Device(s) Compatible: " << _isd_evice_compatible << endl;
    return 0;
}

```

I successfully compiled it using:

```auto
g++ check_cuda.cpp -o check_cuda `pkg-config opencv4 --cflags --libs`

```

**But when I try to launch it, I have the following error message :**

```auto
terminate called after throwing an instance of 'cv::Exception'
  what(): OpenCV(4.1.1) /root/opencv/modules/core/src/cuda_info.cpp:84: error: (-217:Gpu API call) CUDA driver version is insufficient for CUDA runtime version in function 'getDevice'

```

I don’t understand why since I used the last official L4T image for Jetson Nano (containing Cuda 10.2) and I installed the same OpenCV version that the one included in the last Jetpack.  
I build OpenCV for Cuda Arch Bin 5.3, which, if I’m not wrong, is correct for Jetson Nano.

So, I don’t have any idea any more…

For information the Cuda version (on the Jetson, and in the container) is the same:

```auto
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Sun_Feb_28_22:34:44_PST_2021
Cuda compilation tools, release 10.2, V10.2.300
Build cuda_10.2_r440.TC440_70.29663091_0

```

Thanks for your help.

---

<div class="post-metadata">

**Author:** ![florianC31](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@florianC31](https://forums.developer.nvidia.com/u/florianC31)\
**Post date:** [June 10, 2022, 8:00am UTC](https://forums.developer.nvidia.com/t/error-trying-to-use-opencv-with-cuda-support-on-docker-cuda-driver-version-is-insufficient-for-cuda-runtime-version/217168/2 "2022-06-10T08:00:59Z")

</div>

I just tried to use the docker file from [this Git repo](https://github.com/dusty-nv/jetson-inference/blob/master/docs/aux-docker.md) (as suggested at the end of this [Nvidia page](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-base)).

I use directly the Docker image [`dustynv/jetson-inference:r32.7.1`](https://hub.docker.com/r/dustynv/jetson-inference/tags), and I ran the same c++ code with almost exactly the same result (only the OpenCV version is different):

```auto
terminate called after throwing an instance of 'cv::Exception'
  what(): OpenCV(4.5.0) /opt/opencv/modules/core/src/cuda_info.cpp:84: error: (-217:Gpu API call) CUDA driver version is insufficient for CUDA runtime version in function 'getDevice'

```

---

<div class="post-metadata">

**Author:** ![florianC31](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@florianC31](https://forums.developer.nvidia.com/u/florianC31)\
**Post date:** [June 10, 2022, 9:30am UTC](https://forums.developer.nvidia.com/t/error-trying-to-use-opencv-with-cuda-support-on-docker-cuda-driver-version-is-insufficient-for-cuda-runtime-version/217168/3 "2022-06-10T09:30:39Z")

</div>

I just solved the problem.  
It was a docker issue, I needed to pass the param `--runtime nvidia` in the docker run command to link the GPU to my docker.  
More details on [the run script of dusty-nv/jetson-inference git repo](https://github.com/dusty-nv/jetson-inference/blob/master/docker/run.sh).

At the end it works for both docker images (mine and jetson-inference).

---

<div class="post-metadata">

**Author:** ![kayccc](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/kayccc/32/14043_2.png) [@kayccc](https://forums.developer.nvidia.com/u/kayccc)\
**Post date:** [June 13, 2022, 2:09am UTC](https://forums.developer.nvidia.com/t/error-trying-to-use-opencv-with-cuda-support-on-docker-cuda-driver-version-is-insufficient-for-cuda-runtime-version/217168/4 "2022-06-13T02:09:31Z")

</div>

Thanks for your sharing!!

---

<div class="post-metadata">

**Author:** ![system](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/system/32/68080_2.png) [@system](https://forums.developer.nvidia.com/u/system)\
**Post date:** [June 27, 2022, 2:09am UTC](https://forums.developer.nvidia.com/t/error-trying-to-use-opencv-with-cuda-support-on-docker-cuda-driver-version-is-insufficient-for-cuda-runtime-version/217168/5 "2022-06-27T02:09:45Z")

</div>

Closed on June 27, 2022, 2:09am UTC

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