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General / Texture problems with large project
« Last post by Daniele on Today at 11:53:03 AM »
Dear all,
I am writing here after searching in the forum for a solution but with no success to solve my issue.
I have a very large underwater imagery dataset (2996 Gopro10 photos) which I would like to use to reconstruct a diving site. Due to its 3D morphology (flat areas, boulders, overhangs), I have both oblique and nadiral images to cover all the surfaces.  I have no problem with the alignment (all cameras aligned successfully in low quality to save processing time). I filtered and cleaned the resulting point cloud and generated two meshes: one in high quality and another by decimating it. Now the problem is the texturing process because I can't get a good texture on  mesh. I tried different mapping modes (generic, spherical, adaptive orthophoto)  after normal map generation but the results are the same. The images even if are from an action camera are all good and sharp enough so I don't think the problem is related to image quality. The model shaded looks better than the textured one. I am working on Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz GPU(s) NVIDIA GeForce GTX 1080. Since the project Is huge (10 gigas) maybe I could upload the report to better show the workflow used. However, the size limit of the attachment is limiting for it.

 I am attaching some snaps just to better describe such aspects.

Does someone have some suggestions to solve such an issue?
Many thanks in advance for your help!

I can only give you idea of my workflow, but it is outside of MS:
-create pointcloud in MS, export it to cloudcompare and apply poisson surface reconstruction, then export mesh to meshlab and apply "Simplification: Quadric edge collapse decimation" filter(this gives you overlap/dark triangles free mesh)
Thank you, Ill give it a shot and report back, but can we get just snap model to 0,0,0 then rotate as needed?

Also any idea on these massive face issues with overlapping etc? its a lot of work to clean up..
General / Re: Processing Pléiades tri-stereo imagery
« Last post by Alexey Pasumansky on July 01, 2022, 07:16:13 PM »
Hello Gaurav,

In the tutorial there's an instruction how to pre-process the tiled image data using GDAL (before loading to Metashape):
DIMAP format support is limited to single tile images only. Tiled DIMAP images need to be combined before adding to Metashape project:
gdal_translate DIM_<datasetname>.XML combined.tif -co TILED=YES
gdaladdo -r average combined.tif 2 4 8 16 32
Does it work with your data?
Bug Reports / Re: Metashape Pop-up Issues on Dell XPS 15
« Last post by Alexey Pasumansky on July 01, 2022, 07:13:47 PM »
Hello WLW,

If you force-use NVIDIA GPU for metashape.exe (NVIDIA will be shown in Metashape start log) and have latest NVIDIA driver installed - what is the Console pane output for regular and ANGLE compatibility mode?
Python and Java API / Re: Camera Rig configuration through Python API
« Last post by ilia on July 01, 2022, 03:50:36 PM »
I guess it is solved.

The single not solved issue I have is how to lock location of slave sensors. My solution was to set their accuracy values too small to decrease the optimization step for them. But I would prefer not to optimize them at all.
Python and Java API / Matches/IPs using reference data as GCPs in image coords
« Last post by sydneyg on July 01, 2022, 12:06:42 PM »
Hi all, I'm currently working with some historical aerial imagery with the Metashape python modules and I had a few questions:

1. Is it possible to run matchPhotos using a reference orthomosaic to create GCPs? in other words,  find IPs within a reference orthomosaic to "create" GCPs for by matching features in the historical imagery for the bundle adjustment (e.g. where the GCPs would have coordinates in e.g. WGS84 from the reference and corresponding match points in image coordinates?).

2. If #1 is not possible, would it then be possible to import pre-existing interest points as GCPs? Specifically, I have coordinates taken from a coarse reference ortho in lat/long/elev and related to image coordinates X(mm from PPA)/Y(mm from PPA) for each image that I have already created in Ames stereo pipeline, would it be possible to somehow integrate those as GCPs? In other words, for each image, can I relate a pixel coordinate to a Ground control marker, and then use that info to complete the bundle adjustment? If so, how would I go about doing that in python?

Thank you for any help,

General / Re: Loosen up requirement for matching with manually places markers
« Last post by Tobi_Passau on July 01, 2022, 10:57:41 AM »
I'm doing this all the time. The software doesn't align the photos or merges the components.
General / Re: Processing Pléiades tri-stereo imagery
« Last post by Gaurav on July 01, 2022, 10:34:21 AM »
Hi Alexey,

Thanks for the reply.

If we have multiple tile of a single image with one RPC file then how we can process the data.

General / Re: Loosen up requirement for matching with manually places markers
« Last post by DayGeckoArt on July 01, 2022, 08:37:22 AM »
Place your markers and see what happens. There's no requirement, I've had ground control points on only single photos
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