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Add options to choose min and max images per class #161
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That's a good idea. I actually have this feature implemented already in the I just haven't exposed it through the web interface yet. |
Thanks @lukeyeager, I knew I had seen these options somewhere in Digits, but had forgotten where. Still exposing them through web interface would be nice. |
Should the min/max conditions apply to the training set only or should they also apply to the validation/test sets? Should we ignore min/max number of images per class when samples are specified through text files? Thanks. |
I think min/max should be applied before dividing it into train/validation/test set. For example if you set min to 10 and train/val/test split to 60/20/20, then each class will have at least 6 training samples, 2 validation samples and 2 test samples. In case it doesn't split evenly, I would round down validation and test numbers and use remaining for training, so all samples are still used. I agree, that when samples are specified using text files, min/max constraints should be ignored. Tambet Sent from a device without proper keyboard
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Add ParseFolderTasks info in dataset job JSON Add tests for image counts and min/max samples per category
Add ParseFolderTasks info in dataset job JSON Add tests for image counts and min/max samples per category
Add ParseFolderTasks info in dataset job JSON Add tests for image counts and min/max samples per category
Sorry, I was on a vacation and now catching up with backlog. I'll give this a try ASAP. |
Add options to choose min images and max images per class when adding new dataset. This would ignore folders (classes) that have less than or more than given number of images. These fields could be added to dataset creation form, below validation set creation options. This would in many cases allow using of original dataset folder without additional preprocessing.
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