Estimate target location from blobs

Signed-off-by: milind-u <milind.upadhyay@gmail.com>
Change-Id: Ib9bfe0dc494b1581236d1f3f57bc65c6687981e5
diff --git a/y2022/vision/blob_detector.cc b/y2022/vision/blob_detector.cc
index 737363d..b76ffc5 100644
--- a/y2022/vision/blob_detector.cc
+++ b/y2022/vision/blob_detector.cc
@@ -1,6 +1,11 @@
 #include "y2022/vision/blob_detector.h"
 
+#include <cmath>
+#include <string>
+
 #include "aos/network/team_number.h"
+#include "opencv2/features2d.hpp"
+#include "opencv2/imgproc.hpp"
 
 DEFINE_uint64(green_delta, 50,
               "Required difference between green pixels vs. red and blue");
@@ -20,7 +25,8 @@
       uint8_t red = pixel.val[2];
       // Simple filter that looks for green pixels sufficiently brigher than
       // red and blue
-      if ((green > blue + 30) && (green > red + 50)) {
+      if ((green > blue + FLAGS_green_delta) &&
+          (green > red + FLAGS_green_delta)) {
         binarized_image.at<uint8_t>(row, col) = 255;
       } else {
         binarized_image.at<uint8_t>(row, col) = 0;
@@ -69,16 +75,28 @@
     std::vector<std::vector<cv::Point>> blobs,
     std::vector<BlobDetector::BlobStats> blob_stats) {
   std::vector<std::vector<cv::Point>> filtered_blobs;
+
   auto blob_it = blobs.begin();
   auto stats_it = blob_stats.begin();
   while (blob_it < blobs.end() && stats_it < blob_stats.end()) {
+    // To estimate the maximum y, we can figure out the y value of the blobs
+    // when the camera is the farthest from the target, at the field corner.
+    // We can solve for the pitch of the blob:
+    // blob_pitch = atan((height_tape - height_camera) / depth) + camera_pitch
+    // The triangle with the height of the tape above the camera and the camera
+    // depth is similar to the one with the focal length in y pixels and the y
+    // coordinate offset from the center of the image.
+    // Therefore y_offset = focal_length_y * tan(blob_pitch), and
+    // y = -(y_offset - offset_y)
     constexpr int kMaxY = 400;
     constexpr double kTapeAspectRatio = 5.0 / 2.0;
     constexpr double kAspectRatioThreshold = 1.5;
     constexpr double kMinArea = 10;
-    constexpr size_t kMinPoints = 2;
+    constexpr size_t kMinPoints = 6;
+
     // Remove all blobs that are at the bottom of the image, have a different
     // aspect ratio than the tape, or have too little area or points
+    // TODO(milind): modify to take into account that blobs will be on the side.
     if ((stats_it->centroid.y <= kMaxY) &&
         (std::abs(kTapeAspectRatio - stats_it->aspect_ratio) <
          kAspectRatioThreshold) &&
@@ -88,6 +106,7 @@
     blob_it++;
     stats_it++;
   }
+
   return filtered_blobs;
 }
 
@@ -99,12 +118,14 @@
   CHECK_GT(view_image.cols, 0);
   if (unfiltered_blobs.size() > 0) {
     // Draw blobs unfilled, with red color border
-    drawContours(view_image, unfiltered_blobs, -1, cv::Scalar(0, 0, 255), 0);
+    cv::drawContours(view_image, unfiltered_blobs, -1, cv::Scalar(0, 0, 255),
+                     0);
   }
 
-  drawContours(view_image, filtered_blobs, -1, cv::Scalar(0, 255, 0),
-               cv::FILLED);
+  cv::drawContours(view_image, filtered_blobs, -1, cv::Scalar(0, 255, 0),
+                   cv::FILLED);
 
+  // Draw blob centroids
   for (auto stats : blob_stats) {
     cv::circle(view_image, stats.centroid, 2, cv::Scalar(255, 0, 0),
                cv::FILLED);