Hi jzbontar,
We have a set of stereo images that has been tested on the .lua code provided and the disparity maps are obtained. From visualization, we can say whether it is giving good results or not. But are there any metrics which can actually evaluate the dataset.
An example can be as follows:
"For object detection/ classification, we have metrics such as accuracy, precision, recall, F1-score, IoU, mAP, confusion matrix etc.. What are the metrics for stereo? Are they implemented in your code and if so, how to use them?"
Thanking you
Srinath
Hi jzbontar,
We have a set of stereo images that has been tested on the .lua code provided and the disparity maps are obtained. From visualization, we can say whether it is giving good results or not. But are there any metrics which can actually evaluate the dataset.
An example can be as follows:
"For object detection/ classification, we have metrics such as accuracy, precision, recall, F1-score, IoU, mAP, confusion matrix etc.. What are the metrics for stereo? Are they implemented in your code and if so, how to use them?"
Thanking you
Srinath