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Altimis avatar Altimis commented on May 23, 2024

You dont have to setup the number of classes. This code is the continuation of the code example presented in the main Mask-RCNN repo. You just compute the predictions for each images, assign each prediction (classe) to its actual ground-truth using two ordered vectors (gt_tot and pred_tot), and classically compute the confusion matrix for the entire dataset. These two vectors will contain in each element the ground-truth classe for each object in the dataset (the vector gt_tot) and the corresponding predicted classe (the vector pred_tot).

from confusion-matrix-for-mask-r-cnn.

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