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Functional learned vtr for Warthog #226

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Functional learned vtr for Warthog #226

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shemshesh
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  • Some clean up of comments to do.

  • Need to resolve how to use Git LFS for the model weights.

if (fully_matched && channel.cameras.size() == 2)
// return extractStereoFeaturesDisp(channel, channel_disp);
if (fully_matched && channel.cameras.size() == 2){
// CLOG(DEBUG, "stereo.learned_features") << "made it here";
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Remove please.


return F::grid_sample(disparity, keypoints_norm, options).reshape({-1});
return output;
// return F::grid_sample(disparity, keypoints_norm, options).reshape({-1});
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Could drop to a single line again and remove the comment.

}
cv::Mat floatDisp;
disp.convertTo(floatDisp, CV_32F, 1.0f / disparity_multiplier);
// CLOG(DEBUG, "stereo.learned_features") << "disp_type " << disp.type();
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Remove comments please.

@@ -639,6 +636,10 @@ ChannelFeatures LFE::extractStereoFeaturesDisp(const cv::Mat &left_img,

// Get disparity for each keypoint
torch::Tensor disparity = getDisparityTensor(disp);

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Remove please.

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2 participants