Hi everyone,
Background
I have trained a model for detecting cars from orthophoto involving only land area.
However, it also wrongly detects ships as "cars" when I applied it to coastal area.
I have limited time to run variation of "training".
I am using mask RCNN in my training.
Q1. Do "Train Deep Learning Model" GP use unlabeled tiles as background?
Q2. So will it help reducing treating ships as cars if I adding unlabeled tiles with ships?
Q3. I see Output No Feature Tiles option in Export Training Data For Deep Learning.
Will it be useful if I use it to generate background image? I am afraid it will much increase my training time.
Thank everyone for helping with these concept.
Hello
Q1: Pull some label tiles from the label directory into ArcGIS Pro. Click on the non car areas - if it says 0 its background. Unlabeled areas/tiles area usually background.
Q2: Not 100% on this but yes I think it should.
Q3: I will increase training time, assuming your tile count goes up. Also when exporting tiles of ships, you will probably need to set a region of interest, so an area mask. To prevent getting huge amounts of data/tiles
Regards
Tim
Thank TimG for answering the questions.
I tried a export with no Feature Tiles option. However, they are seems ignored during the training process.
So I think the answer for Q1 and Q2 is no?
Q3. Thank you for your suggestion. I tried and it solved my problem