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Python and Java API / Projecting image space corners on dense cloud boundary
« on: January 22, 2021, 09:12:12 PM »
Hi,
In our application we are using Metashape to project a variety of UAV acquired image space features into world space using the dense cloud results. (The heart of the code that performs the projections is discussed in this post: https://www.agisoft.com/forum/index.php?topic=12781.0). The approach works well, but we are working to trap a few boundary conditions. Among the features we are projecting are the image corners. For images that are literally on the geographic boundary of the site and have a valid `camera.transform` we can get degenerate points returned for one or more of the image corners, like this (in UTM):
Is there a way to extend the dense cloud boundary, or change other model creation params, so that we are not returning zeros from `chunk.dense_cloud.pickPoint()` for image points on the boundary? We are hoping that reliably extending the interpolation boundary may also result in fewer non-valid `camera.transform`s for images on the boundary, for which we cannot project any points of course.
KCM
In our application we are using Metashape to project a variety of UAV acquired image space features into world space using the dense cloud results. (The heart of the code that performs the projections is discussed in this post: https://www.agisoft.com/forum/index.php?topic=12781.0). The approach works well, but we are working to trap a few boundary conditions. Among the features we are projecting are the image corners. For images that are literally on the geographic boundary of the site and have a valid `camera.transform` we can get degenerate points returned for one or more of the image corners, like this (in UTM):
Code: [Select]
"type": "Polygon",
"coordinates": [
[
[
0,
0
],
[
0,
0
],
[
572650.2037708747,
5102280.396009785
],
[
0,
0
],
[
0,
0
]
]
]
Is there a way to extend the dense cloud boundary, or change other model creation params, so that we are not returning zeros from `chunk.dense_cloud.pickPoint()` for image points on the boundary? We are hoping that reliably extending the interpolation boundary may also result in fewer non-valid `camera.transform`s for images on the boundary, for which we cannot project any points of course.
KCM