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fix appending features behind all the zeros occurring at coordinates … #508

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fix appending features behind all the zeros occurring at coordinates … #508

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18 changes: 8 additions & 10 deletions depthai_bridge/src/TrackedFeaturesConverter.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -33,16 +33,14 @@ void TrackedFeaturesConverter::toRosMsg(std::shared_ptr<dai::TrackedFeatures> in
msg.header.frame_id = _frameName;
msg.features.resize(inFeatures->trackedFeatures.size());

for(const auto& feature : inFeatures->trackedFeatures) {
depthai_ros_msgs::msg::TrackedFeature ft;
ft.header = msg.header;
ft.position.x = feature.position.x;
ft.position.y = feature.position.y;
ft.age = feature.age;
ft.id = feature.id;
ft.harris_score = feature.harrisScore;
ft.tracking_error = feature.trackingError;
msg.features.emplace_back(ft);
Comment on lines 34 to -45
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@wouterio wouterio Mar 5, 2024 •
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What actually goes wrong here is that msg.features.resize(inFeatures->trackedFeatures.size()) expands the msg.features vector with value-initialized feature elements. That causes all the zero features mentioned in this issue. Then later on msg.features.emplace_back(ft) appends the actual features.

So replacing msg.features.resize with msg.features.reserve might solve the problem too.

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I agree with @wouterio, although vec[i] might be faster than emplace_back in some cases, I would leave it as is and only change the resize part

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He @Serafadam, thanks for addressing this!

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@wouterio wouterio Mar 20, 2024 •
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I also expect emplace_back to be the right choice here, because the link you mentioned concludes with this:

In principle, if the type stored in the vector is a simple type (not a class or a struct), the loop is often vectorizable and one could expect to see similar numbers as we have seen here. With larger classes, it is the opposite: vectorization doesn’t pay off because of the low memory efficiency, so the operator[] version will in principle slower.

Since the features we're inserting are class/struct types, so we can expect emplace_back to be faster. But of course:

as always with software performance, the runtime numbers are the ones that give the final verdict.

for(int i = 0; i < inFeatures->trackedFeatures.size(); ++i) {
msg.features[i].header = msg.header;
msg.features[i].position.x = inFeatures->trackedFeatures[i].position.x;
msg.features[i].position.y = inFeatures->trackedFeatures[i].position.y;
msg.features[i].age = inFeatures->trackedFeatures[i].age;
msg.features[i].id = inFeatures->trackedFeatures[i].id;
msg.features[i].harris_score = inFeatures->trackedFeatures[i].harrisScore;
msg.features[i].tracking_error = inFeatures->trackedFeatures[i].trackingError;
}
featureMsgs.push_back(msg);
}
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