I have a question regarding the matching score check
for both invisible gt and pred points the matching distance is set to 0 :
euclidean_dist[both_invisibleindices] = 0
and the cost for matching is set as:
cost = np.sum(euclidean_dist)
however the matching score threshold is set to number of all points multiply by dist_th
but invisible points distance is set to zero, causing higher threshold for shorter lanes
match_results[i, 2] < self.dist_th * self.y_samples.shape[0]
hello and thanks for this useful code
I have a question regarding the matching score check for both invisible gt and pred points the matching distance is set to 0 : euclidean_dist[both_invisibleindices] = 0 and the cost for matching is set as: cost = np.sum(euclidean_dist) however the matching score threshold is set to number of all points multiply by dist_th but invisible points distance is set to zero, causing higher threshold for shorter lanes match_results[i, 2] < self.dist_th * self.y_samples.shape[0]
what have I missed here ?