针对您遇到的问题“dnn: cuda backend requires cudnn. please resolve dependency or disable openc”,这通常表明您的深度学习框架(如TensorFlow, PyTorch等)在尝试使用CUDA后端时未能找到cuDNN库。以下是一些解决步骤,这些步骤将帮助您检查和解决问题: 1. 确认CUDA和cuDNN的安装 首先,您需要确认CUDA和cuDNN是否已安...
Whenever I try to load a model using CUDA as target and backend it throws this runtime error stated in the title. net_.setPreferableBackend(cv::dnn::DNN_BACKEND_CUDA); net_.setPreferableTarget(cv::dnn::DNN_TARGET_CUDA); Environment OS: Windows 10 x64] CUDA 12.6 cuDNN 9.5 OpenCV 4.8...
[ WARN:0 ] global /tmp/pip-req-build-q3gzfcr4/opencv/modules/dnn/src/dnn.cpp (1442) setUpNet DNN module was not built with CUDA backend; switching to CPU You need to install CUDA, CuDNN and re-build OpenCV with CUDA and CuDNN support. Please use some fresh version of OpenCV to ...
-D BUILD_opencv_hdf=ON .. 5: camke 第一次会报错,修改bug: windows bug太多了,ubuntu 也不少,估计每个人遇到的 bug也不一样: 先要依赖库安装: 错误1: CMake Error at modules/dnn/CMakeLists.txt:39 (message): DNN: CUDA backend requires cuDNN. Please resolve dependency or disable OPENCV_DNN_...
Net::Impl::setUpNetDNNmodulewasnotbuilt withCUDAbackend;switching toCPU 这时候估计很纳闷,为什么我的有GPU也有相应的CUDA环境为什么不能使用CUDA加速呢。这是由于使用官方的OpenCV-python默认是CPU版本的,没有CUDA加速功能(我一直很纳闷为什么不发布编译后的CUDA版本呢)。所以,不能很轻松的去实现CUDA加速模型推理。
但是train的时候报错: ensorflow/compiler/xla/service/gpu/llvm_gpu_backend/gpu_backend_lib.cc:521] Can't find libdevice directory ${CUDA_DIR}/nvvm/libdevice. This may result in compilation or runtime failures, if the program we try to run uses routines from libdevice. ...
再次点击Configure按钮,构建完毕后可以将CUDA_ARCH_BIN参数修改为自己显卡所对应的算力,可大幅度加快后续编译速度。显卡对应算力见https://developer.nvidia.com/zh-cn/cuda-gpus#compute,也可以通过前面提到Samples中的deviceQuery得到。 最好等到输出信息中没有警告与报错,CUDA与cuDNN都被检测到而输出信息最后出现Configu...
训练yolov5或者yolov8时候会报错: Could not load library libcudnn_cnn_train.so.8. Error: /usr/local/cuda-12.1/lib64/libcudnn_cnn_train.so.8: uined symbol: _ZN5cudnn3cnn34layerNormFwd_execute_internal_implERKNS_7backend11VariantPackEP11CUstream_stRNS0ayerNormFwdParamsERKNS1_20NormForwardOp...
<dependency><groupId>org.nd4j</groupId><artifactId>nd4j-cuda-9.1-platform</artifactId><version>${nd4j.version}</version></dependency> 即可成功运行程序。 在运行程序之后可以看到如下的提示语: o.n.l.f.Nd4jBackend-Loaded[JCublasBackend]backend ...
cvNet.setPreferableTarget(cv2.dnn.DNN_TARGET_CUDA) cvOut = cvNet.forward() got a warning: dnn.cpp (1314) cv::dnn::dnn4_v20191024::Net::Impl::setUpNet DNN module was not built with CUDA backend; switching to CPU Please advise how to build dnn module with CUDA backend. ...