I've gone through the deep learning tutorial to detect palm trees in Tonga several times, each time thinking I could try something new to achieve better results. I have failed every time to come up with something even remotely better than old school image classification. I've spent months watching every video I can find and researching every article I can find about deep learning. Everything ESRI puts out shows people using Jupyter notebooks and they never explain exactly how to train those models using notebooks. They just show their final results, which of course always look good. There are several references to using the model provided by the "data scientist" but I've had a hard time finding useful examples for my application (detecting macadamia nut trees in an orchard). If you go through the deep learning tutorial for identifying palm tree health, the results are pretty much useless. Anyone know where else I can turn to get some better instruction?
Scott... is this the tutorial you are referring to?
Yes, that's the one. I've watched about a half dozen videos produced by
ESRI showing examples of object detection in the case of cars, pools,
damaged vs undamaged houses, well pads, and shipwrecks. In those examples
the model performs very well, but the demonstrators are always using
jupyter notebooks to train their model and I can't find any help on using
notebooks or example code. I'm trying to learn but running into dead ends.
Thanks for replying.
I tried ESRI example for palm identification it gives promising results but same steps if i apply on my Drone image (Tiff format with 3 bands) i am able to create Image chips files output is very good up to this step, but when i go forward to "Train a Deep learning model" next steps its showing me an error cannot identify image chips.
is there any solution for this step ?
Please guide me on this Dan Patterson