Open sophiahe671 opened 1 month ago
Now playing with patch size: https://deepforest.readthedocs.io/en/latest/better.html
I can't find a good way to run a pretrained deepforest model with specified parameters. the predict_tile() function is giving me errors. I also can't figure out where to specify n_estimators.
When I run predict_tile, I get this error:
RuntimeError:
An attempt has been made to start a new process before the
current process has finished its bootstrapping phase.
This probably means that you are not using fork to start your
child processes and you have forgotten to use the proper idiom
in the main module:
if __name__ == '__main__':
freeze_support()
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce an executable.
To fix this issue, refer to the "Safe importing of main module"
section in https://docs.python.org/3/library/multiprocessing.html
But it works for Alex and it seems to work a lot better than predict_image
I can edit nms_thresh
on the deepforest.config yml file. This makes it so the algorithm will overlap tree prediction areas more.
On the left, nms_thresh = .5
On the right, nms_thresh = .05
(default)
I don't think editing nms_thresh
will help for this image.
predict_tile() works on some of our computers and it is much better than predict_image()! We think this is because the .tif file is very detailed and very large.
With predict_image(), we couldn't even run the program on the .tif file, just the .png file. So this is much better.
The parameters we can edit now are:
Here is the result with patch size 30. It took about 7 hours to run. All the 'trees' it found were a lot smaller than the actual trees. I think the patch size might be so small that it doesn't even cover one whole tree. Maybe we should start testing with patch size 100?
Patch size 100 also seems too small. Took 30 minutes to run.
Looking at DeepForest parameters such as n_estimators and max_layers: https://deep-forest.readthedocs.io/en/stable/parameters_tunning.html