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We need a function which tests a keypoint detector by trying it on all the data (train and test) and checking it finds an appropriate number of keypoints for all of them.
The text was updated successfully, but these errors were encountered:
For the implementation, use neukrill_net.utils.Settings(settings.json)
and load images with neukrill_net.utils.load_rawdata.
and loop until an image is no good.
(See train_bow.py in work repo for example of how to load data with this function.)
Alternatively, we could write a processing wrapper function which is applied to each image on load and returns True or False for each image.
That would probably be better. Although it wouldn't be able to halt at the first False.
We need a function which tests a keypoint detector by trying it on all the data (train and test) and checking it finds an appropriate number of keypoints for all of them.
The text was updated successfully, but these errors were encountered: