Messages

1

Python and Java API / Re: Estimate image quality ignoring masked regions and disable images

« on: May 28, 2018, 08:02:50 AM »

thank you!
it works great.

2

Python and Java API / Estimate image quality ignoring masked regions and disable images

« on: May 25, 2018, 07:53:20 AM »

Hi, I try to estimate the image quality and disable those that have a quality lower than 0.6, I have tried with the following code:

Code: [Select]

chunk.estimateImageQuality(chunk.cameras)
    for camera in chunk.cameras:
        if float(camera.photo.meta["Image/Quality"]) < 0.6:
            camera.enabled = False
However, the console reports the following error:

Code: [Select]

float() argument must be a string or a number, not 'NoneType'
What would be the correct code?

Also I would like to know if there is a parameter for the estimation to be carried out ignoring the masked areas, I reviewed the phyton agisoft guide but I did not find anything.

Thanks a lot

3

Python and Java API / Re: Update view and bounding box for each chunk

« on: March 04, 2017, 08:27:33 AM »

Hello m,

Here's the code that automatically orients the viewpoint to display the bounding box fully in the Model view frame and exports the model to PDF format.

Code: [Select]

import PhotoScan
from PySide import QtGui

chunk = PhotoScan.app.document.chunk
T = chunk.transform.matrix
viewpoint = PhotoScan.app.viewpoint

main =  QtGui.qApp
for wdg in list(main.allWidgets()):
    if wdg.inherits('QGLWidget'):
        cy = wdg.height()
        cx = wdg.width()
        break

region = chunk.region
r_center = region.center
r_rotate = region.rot
r_size = region.size
r_vert = list()

for i in range(8):   #bounding box corners
r_vert.append(PhotoScan.Vector([0.5 * r_size[0] * ((i & 2) - 1), r_size[1] * ((i & 1) - 0.5), 0.25 * r_size[2] * ((i & 4) - 2)]))
r_vert[i] = r_center + r_rotate * r_vert[i]

height =  T.mulv(r_vert[1] - r_vert[0]).norm()
width  = T.mulv(r_vert[2] - r_vert[0]).norm()

if width / cx > height /cy:
scale = cx / width
else:
scale = cy / height

PhotoScan.app.viewpoint.coo = T.mulp(chunk.region.center)
PhotoScan.app.viewpoint.mag = scale
PhotoScan.app.viewpoint.rot = chunk.transform.rotation * r_rotate

crs = PhotoScan.CoordinateSystem("LOCAL")
chunk.exportModel(path, format="pdf", projection=crs)

As for the script that should use the coordinates of the bounding box corners, are you planning to specify all eight points or four laying in the plane?

What modifications should I make in this code to be compatible with version 1.3.0?