Make SIFT faster
This uses various halide-optimized functions to do the actual image
processing. It still finds around the same number of features, but much
faster.
Change-Id: I9d7f7093b0ec41acf7ed16b2c91cdadada2f9a22
diff --git a/y2020/vision/sift/testing_sift.cc b/y2020/vision/sift/testing_sift.cc
new file mode 100644
index 0000000..d4b1306
--- /dev/null
+++ b/y2020/vision/sift/testing_sift.cc
@@ -0,0 +1,87 @@
+#include <memory>
+
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgcodecs.hpp>
+#include <opencv2/imgproc.hpp>
+
+#include "aos/init.h"
+#include "aos/time/time.h"
+#include "y2020/vision/sift/fast_gaussian.h"
+#include "glog/logging.h"
+#include "y2020/vision/sift/sift971.h"
+
+DEFINE_string(image, "", "Image to test with");
+
+int main(int argc, char **argv) {
+ aos::InitGoogle(&argc, &argv);
+
+ cv::setNumThreads (4);
+
+ const cv::Mat raw_image = cv::imread(FLAGS_image);
+ CHECK(!raw_image.empty()) << ": Failed to read: " << FLAGS_image;
+ CHECK_EQ(CV_8UC3, raw_image.type());
+#if 0
+ cv::Mat color_image;
+ raw_image.convertTo(color_image, CV_32F, 1.0/255.0);
+ cv::Mat image;
+ cv::cvtColor(color_image, image, cv::COLOR_BGR2GRAY);
+#else
+ cv::Mat gray_image;
+ cv::cvtColor(raw_image, gray_image, cv::COLOR_BGR2GRAY);
+ cv::Mat float_image;
+#if 0
+ gray_image.convertTo(float_image, CV_32F, 0.00390625);
+#else
+ float_image = gray_image;
+#endif
+ cv::Mat image;
+ cv::resize(float_image, image, cv::Size(1280, 720), 0, 0, cv::INTER_AREA);
+#endif
+#if 0
+#if 0
+ cv::namedWindow("source", cv::WINDOW_AUTOSIZE);
+ cv::imshow("source", raw_image);
+ cv::namedWindow("converted", cv::WINDOW_AUTOSIZE);
+ cv::imshow("converted", image);
+#endif
+
+ cv::Mat slow_blurred, fast_blurred;
+ const double sigma = 3.0900155872895909;
+ cv::GaussianBlur(image, slow_blurred, cv::Size(9, 9), sigma, sigma);
+ frc971::vision::FastGaussian(image, &fast_blurred, sigma);
+ cv::namedWindow("slow", cv::WINDOW_AUTOSIZE);
+ cv::imshow("slow", slow_blurred);
+ cv::namedWindow("fast", cv::WINDOW_AUTOSIZE);
+ cv::imshow("fast", fast_blurred);
+ cv::waitKey(0);
+ return 0;
+#endif
+
+ LOG(INFO);
+ std::unique_ptr<frc971::vision::SIFT971_Impl> sift(new frc971::vision::SIFT971_Impl());
+ std::vector<cv::KeyPoint> keypoints;
+ cv::Mat descriptors;
+ LOG(INFO) << "detectAndCompute on " << image.rows << "x" << image.cols;
+ sift->detectAndCompute(image, cv::noArray(), keypoints, descriptors);
+ LOG(INFO);
+
+#if 0
+ return 0;
+#endif
+
+ static constexpr int kIterations = 40;
+ const auto start = aos::monotonic_clock::now();
+ for (int i = 0; i < kIterations; ++i) {
+ keypoints.clear();
+ descriptors.release();
+ sift->detectAndCompute(image, cv::noArray(), keypoints, descriptors);
+ }
+ const auto end = aos::monotonic_clock::now();
+ LOG(INFO)
+ << "Took: "
+ << (std::chrono::duration<double>(end - start) / kIterations).count();
+ // Should be ~352 for FRC-Image4-cleaned.png downscaled to 640x360.
+ // 376 in DoG_TYPE_SHORT mode.
+ // 344 now with 1280x720 non-upscaled.
+ LOG(INFO) << "found " << keypoints.size() << " and " << descriptors.size();
+}