Create code.cpp

code.cpp

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+#include <CL/sycl.hpp>
+#include <Eigen/Dense>
+#include <arrayfire.h>
+#include <opencv2/opencv.hpp>
+
+namespace sycl = cl::sycl;
+
+int main() {
+  // Specify the path to the MRI image file
+  std::string imagePath = "mriimage.jpg";
+
+  // Load the MRI image using OpenCV
+  cv::Mat image = cv::imread(imagePath, cv::IMREAD_GRAYSCALE);
+
+  // Create a SYCL queue
+  sycl::queue q(sycl::default_selector{});
+
+  // Define the kernel function for tumor detection
+  auto tumorDetectionKernel = [&](sycl::handler& cgh) {
+    // Get write access to the image data
+    auto imgAccessor = imgBuffer.get_access<sycl::access::mode::write>(cgh);
+
+    // Define a parallel range based on the image dimensions
+    sycl::range<2> imageSize(image.cols, image.rows);
+
+    // Execute the tumor detection kernel
+    cgh.parallel_for(imageSize, [=](sycl::id<2> id) {
+      // Get the pixel value at the current position
+      uint8_t pixel = image.at<uint8_t>(id[1], id[0]);
+
+      // Perform tumor detection logic
+      bool isTumorPixel = ...; // Implement your tumor detection algorithm here
+
+      // Update the image with the tumor detection result
+      uint8_t resultPixel = isTumorPixel ? 255 : 0;
+      imgAccessor[id] = resultPixel;
+    });
+  };
+
+  // Submit the tumor detection kernel to the SYCL queue
+  q.submit([&](sycl::handler& cgh) {
+    // Create a buffer for the image data
+    sycl::buffer<uint8_t, 2> imgBuffer(image.data, sycl::range<2>(image.cols, image.rows));
+
+    // Associate the buffer with the kernel function
+    cgh.set_args(imgBuffer);
+
+    // Execute the tumor detection kernel
+    cgh.single_task(tumorDetectionKernel);
+  });
+
+  // Wait for the queue to finish
+  q.wait();
+
+  // Get the updated image data from the buffer
+  cv::Mat detectedImage(image.rows, image.cols, CV_8UC1, imgBuffer.get_pointer());
+
+  // Display the detected tumor image
+  cv::imshow("Detected Tumor Image", detectedImage);
+  cv::waitKey(0);
+
+  return 0;
+}