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Messages - luroth

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Bug Reports / Poor performance of ImportReference
« on: September 06, 2018, 08:47:50 PM »

I'm using PhotoScan Professional in a fully integrated Python script workflow to process aerial images. For precise georeferencing after a rought alignment based on GPS coordinates, I'm using the non-coded GCP detection feature of PhotoScan with a very relaxed tolerance, followed by a reference import that assigns coordinates to the nearest detected GCP and discards all others:

Code: [Select]
chunk.detectMarkers(PhotoScan.TargetType.CrossTarget, tolerance=1)
   columns='nxyz', delimiter=',',
   ignore_labels=True, threshold = 0.4)

This code performs terribly slow if a lot of (false) GCPs were detected and had to become discarded. My 3.5 GHz 40 core CPU is on 3 % utilization, but the step takes up to 12 h. Could you please fix this performance issue, e.g. by allowing multiprocessing?

Python and Java API / Re: Export orthorectified image cube
« on: September 02, 2016, 12:36:09 PM »
Hi Alexey

That's it, with projection argument it works, without I get a "bad allocation" error. Thanks a lot!

Python and Java API / Re: Export orthorectified image cube
« on: September 01, 2016, 09:09:42 PM »
Hi Alexey

Yes, the export inside the GUI works. Importing the resulting single photos in a GIS application creates a mosaic as desired, only the Python method is not working for me...

Python and Java API / Export orthorectified image cube
« on: September 01, 2016, 03:50:33 PM »

I like to export the orthorectified images one by one in a folder. In the GUI this can be done using "Tools" - "Export" - "Export Orthophotos" and selecting a folder and providing a pattern for the filenames ("{filename}.tif")

How is the corresponding function in the Python API called? exportOrthophotos? And if yes, what is the correct syntax for "PATH"?

I tried:

> Error: Unsupported extension:

> Error: bad allocation

> Error: bad allocation

E:\Temp exists, the chunk is processed and has a Dense Cloud, 3D Model and DEM. Any suggestions?

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