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Feature: Add OpenVINO NPU support #27363 ## Why - OpenVINO now supports inference on integrated NPU devices in intel's Core Ultra series processors. - Sometimes as fast as GPU, but should use considerably less power. ## How - The NPU plugin is now available as "NPU" in openvino `ov::Core::get_available_devices()`. - Removed the guards and checks for NPU in available targets for Inference Engine backend. ## Test example ### Pre-requisites - Intel [Core Ultra series processor](https://www.intel.com/content/www/us/en/products/details/processors/core-ultra/edge.html#tab-blade-1-0) - [Intel NPU driver](https://github.com/intel/linux-npu-driver/releases) - OpenVINO 2023.3.0+ (Tested on 2025.1.0) ### Example ```cpp #include <opencv2/dnn.hpp> #include <iostream> int main(){ cv::dnn::Net net = cv::dnn::readNet("../yolov8s-openvino/yolov8s.xml", "../yolov8s-openvino/yolov8s.bin"); cv::Size net_input_shape = cv::Size(640, 480); std::cout << "Setting backend to DNN_BACKEND_INFERENCE_ENGINE and target to DNN_TARGET_NPU" << std::endl; net.setPreferableBackend(cv::dnn::DNN_BACKEND_INFERENCE_ENGINE); net.setPreferableTarget(cv::dnn::DNN_TARGET_NPU); cv::Mat image(net_input_shape, CV_8UC3); cv::randu(image, cv::Scalar(0, 0, 0), cv::Scalar(255, 255, 255)); cv::Mat blob = cv::dnn::blobFromImage( image, 1, net_input_shape, cv::Scalar(0, 0, 0), true, false, CV_32F); net.setInput(blob); std::cout << "Running forward" << std::endl; cv::Mat result = net.forward(); std::cout << "Output shape: " << result.size << std::endl; // Output shape: 1 x 84 x 6300 } ``` model files [here](https://limewire.com/d/bPgiA#BhUeSTBnMc) docker image used to build opencv: [ghcr.io/mro47/opencv-builder](https://github.com/MRo47/opencv-builder/blob/main/Dockerfile) Closes #26240 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake |
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| .. | ||
| dnn_android | ||
| dnn_custom_layers | ||
| dnn_face | ||
| dnn_googlenet | ||
| dnn_halide | ||
| dnn_halide_scheduling | ||
| dnn_javascript | ||
| dnn_OCR | ||
| dnn_openvino | ||
| dnn_pytorch_tf_classification | ||
| dnn_pytorch_tf_detection | ||
| dnn_pytorch_tf_segmentation | ||
| dnn_text_spotting | ||
| dnn_yolo | ||
| images | ||
| table_of_content_dnn.markdown | ||