https://bugs.kde.org/show_bug.cgi?id=497565
--- Comment #3 from Michael Miller <michael_mil...@msn.com> --- (In reply to js333031 from comment #2) > Thank you Mike. Please see > https://github.com/opencv/opencv/wiki/Intel-OpenVINO-backend#usage > > The link, if I understood correctly states that OpenVINO backend will be > used if it's installed. The optional part of that section mentions device > selection. That would be useful to select between integrated/discreet Intel > GPUs or VPU. Here's a list of the targets and backends I'm currently working to support: > const std::map<std::string, int> str2backend > { > { "default", cv::dnn::DNN_BACKEND_DEFAULT }, > { "halide", cv::dnn::DNN_BACKEND_HALIDE }, > { "ie", cv::dnn::DNN_BACKEND_INFERENCE_ENGINE }, > { "opencv", cv::dnn::DNN_BACKEND_OPENCV }, > { "cuda", cv::dnn::DNN_BACKEND_CUDA } > }; > > const std::map<std::string, int> str2target > { > { "cpu", cv::dnn::DNN_TARGET_CPU }, > { "opencl", cv::dnn::DNN_TARGET_OPENCL }, > { "myriad", cv::dnn::DNN_TARGET_MYRIAD }, > { "vulkan", cv::dnn::DNN_TARGET_VULKAN }, > { "opencl_fp16", cv::dnn::DNN_TARGET_OPENCL_FP16 }, > { "cuda", cv::dnn::DNN_TARGET_CUDA }, > { "cuda_fp16", cv::dnn::DNN_TARGET_CUDA_FP16 } You can see cv::dnn::DNN_BACKEND_INFERENCE_ENGINE is already on the list. It looks like the correct combination for OpenVINO is DNN_TARGET_OPENCL target with DNN_BACKEND_INFERENCE_ENGINE backend. The issue is that most of the models used by digiKam are in .onnx format. The documentation link you sent says DNN_BACKEND_INFERENCE_ENGINE can only be used with .bin or .xml DNN models. I will see if that has changed since that documentation is a year and half old, which is ancient by OpenCV standards. When selecting a target and backend, I need to check if the hardware installed in the computer supports the model. If so, then I enable GPU processing, otherwise it defaults to CPU. Right now I only have a check to see if OpenCL is enabled. I will add checks for other hardware soon. Cheers, Mike -- You are receiving this mail because: You are watching all bug changes.
