Filter blobs based on aspect ratio and size
Signed-off-by: milind-u <milind.upadhyay@gmail.com>
Change-Id: Idad861a777a9f09de7da10792ce5ab73c5daa6d1
diff --git a/y2022/vision/blob_detector.cc b/y2022/vision/blob_detector.cc
index bf5afd7..737363d 100644
--- a/y2022/vision/blob_detector.cc
+++ b/y2022/vision/blob_detector.cc
@@ -1,7 +1,5 @@
#include "y2022/vision/blob_detector.h"
-#include <opencv2/imgproc.hpp>
-
#include "aos/network/team_number.h"
DEFINE_uint64(green_delta, 50,
@@ -13,7 +11,7 @@
namespace vision {
cv::Mat BlobDetector::ThresholdImage(cv::Mat rgb_image) {
- cv::Mat gray_image(cv::Size(rgb_image.cols, rgb_image.rows), CV_8UC1);
+ cv::Mat binarized_image(cv::Size(rgb_image.cols, rgb_image.rows), CV_8UC1);
for (int row = 0; row < rgb_image.rows; row++) {
for (int col = 0; col < rgb_image.cols; col++) {
cv::Vec3b pixel = rgb_image.at<cv::Vec3b>(row, col);
@@ -23,14 +21,14 @@
// Simple filter that looks for green pixels sufficiently brigher than
// red and blue
if ((green > blue + 30) && (green > red + 50)) {
- gray_image.at<uint8_t>(row, col) = 255;
+ binarized_image.at<uint8_t>(row, col) = 255;
} else {
- gray_image.at<uint8_t>(row, col) = 0;
+ binarized_image.at<uint8_t>(row, col) = 0;
}
}
}
- return gray_image;
+ return binarized_image;
}
std::vector<std::vector<cv::Point>> BlobDetector::FindBlobs(
@@ -44,26 +42,60 @@
return contours;
}
+std::vector<BlobDetector::BlobStats> BlobDetector::ComputeStats(
+ std::vector<std::vector<cv::Point>> blobs) {
+ std::vector<BlobDetector::BlobStats> blob_stats;
+ for (auto blob : blobs) {
+ // Make the blob convex before finding bounding box
+ std::vector<cv::Point> convex_blob;
+ cv::convexHull(blob, convex_blob);
+ auto blob_size = cv::boundingRect(convex_blob).size();
+ cv::Moments moments = cv::moments(convex_blob);
+
+ const auto centroid =
+ cv::Point(moments.m10 / moments.m00, moments.m01 / moments.m00);
+ const double aspect_ratio =
+ static_cast<double>(blob_size.width) / blob_size.height;
+ const double area = moments.m00;
+ const size_t points = blob.size();
+
+ blob_stats.emplace_back(BlobStats{centroid, aspect_ratio, area, points});
+ }
+ return blob_stats;
+}
+
// Filter blobs to get rid of noise, too large items, etc.
std::vector<std::vector<cv::Point>> BlobDetector::FilterBlobs(
- std::vector<std::vector<cv::Point>> blobs) {
- // TODO: Put in some filters
-
+ std::vector<std::vector<cv::Point>> blobs,
+ std::vector<BlobDetector::BlobStats> blob_stats) {
std::vector<std::vector<cv::Point>> filtered_blobs;
- for (auto blob : blobs) {
- // for now, let's remove all blobs that are at the bottom of the image
- if (blob[0].y < 400) {
- filtered_blobs.push_back(blob);
- } else {
- // LOG(INFO) << "Found and removed blob";
+ auto blob_it = blobs.begin();
+ auto stats_it = blob_stats.begin();
+ while (blob_it < blobs.end() && stats_it < blob_stats.end()) {
+ 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;
+ // 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
+ if ((stats_it->centroid.y <= kMaxY) &&
+ (std::abs(kTapeAspectRatio - stats_it->aspect_ratio) <
+ kAspectRatioThreshold) &&
+ (stats_it->area >= kMinArea) && (stats_it->points >= kMinPoints)) {
+ filtered_blobs.push_back(*blob_it);
}
+ blob_it++;
+ stats_it++;
}
return filtered_blobs;
}
void BlobDetector::DrawBlobs(
- cv::Mat view_image, std::vector<std::vector<cv::Point>> unfiltered_blobs,
- std::vector<std::vector<cv::Point>> filtered_blobs) {
+ cv::Mat view_image,
+ const std::vector<std::vector<cv::Point>> &unfiltered_blobs,
+ const std::vector<std::vector<cv::Point>> &filtered_blobs,
+ const std::vector<BlobStats> &blob_stats) {
CHECK_GT(view_image.cols, 0);
if (unfiltered_blobs.size() > 0) {
// Draw blobs unfilled, with red color border
@@ -72,26 +104,23 @@
drawContours(view_image, filtered_blobs, -1, cv::Scalar(0, 255, 0),
cv::FILLED);
-}
-std::vector<std::vector<cv::Point>> BlobDetector::ComputeStats(
- std::vector<std::vector<cv::Point>> blobs) {
- // Placeholder for now for this
- // TODO<Jim>: need to compute stats on blobs, like centroid, aspect
- // ratio, bounding box
- return blobs;
+ for (auto stats : blob_stats) {
+ cv::circle(view_image, stats.centroid, 2, cv::Scalar(255, 0, 0),
+ cv::FILLED);
+ }
}
void BlobDetector::ExtractBlobs(
cv::Mat rgb_image, cv::Mat binarized_image, cv::Mat blob_image,
std::vector<std::vector<cv::Point>> &filtered_blobs,
std::vector<std::vector<cv::Point>> &unfiltered_blobs,
- std::vector<std::vector<cv::Point>> &blob_stats) {
+ std::vector<BlobStats> &blob_stats) {
binarized_image = ThresholdImage(rgb_image);
unfiltered_blobs = FindBlobs(binarized_image);
- filtered_blobs = FilterBlobs(unfiltered_blobs);
- DrawBlobs(blob_image, unfiltered_blobs, filtered_blobs);
- blob_stats = ComputeStats(filtered_blobs);
+ blob_stats = ComputeStats(unfiltered_blobs);
+ filtered_blobs = FilterBlobs(unfiltered_blobs, blob_stats);
+ DrawBlobs(blob_image, unfiltered_blobs, filtered_blobs, blob_stats);
}
} // namespace vision