how to geo-reference my model?

[christo...@gmail.com]

Hello, 

I tried to make a georeferenced model. I do have the "exact position of my images stored in a .txt file.

DSC03240.jpg 519861.62425103 280721.61317575 69.24359963

DSC03095.jpg 519882.02517884 280721.83285926 69.35558947

DSC03194.jpg 519902.51109826 280721.91325819 69.78478120

DSC03250.jpg 519923.00464351 280721.77025080 70.02997290

DSC03308.jpg 519943.95633489 280721.14373284 69.87487511

DSC03042.jpg 519965.10411619 280720.60854994 69.67108211

DSC03384.jpg 519986.11518038 280720.21334504 69.09008598

DSC03109.jpg 520007.01608385 280720.17787899 68.32008756

DSC03401.jpg 520027.98578000 280720.08998486 68.42739074

DSC03387.jpg 520048.84810986 280719.94570045 69.07619129

DSC03298.jpg 520069.96034075 280719.44415267 68.42489747

DSC03038.jpg 520091.21892940 280719.10017014 67.96480733

As described in the manual.

when I try to start model_aligner with the following command 

model_aligner \

    --project_path $PROJECT_PATH/sparse/0 \

    --output_path $PROJECT_PATH/geo-registered-model \

    --ref_images_path /media/daten/luftbilder/monkswood/positionfotos_post/log/pos_fotos

I get the following error 

ERROR: Configuration file does not exist.

Where did I make the mistake? Is it correct to do the model_alignment after making the sparse cloud? 

thank you, christoph

[Johannes Schönberger]

Remove the project path option from your command.

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[christo...@gmail.com]

thank you for your answer I tried the following 

model_aligner \

>     --input_path $PROJECT_PATH/sparse/0 \

>     --output_path $PROJECT_PATH/geo-registered-model \

>     --ref_images_path /media/daten/luftbilder/jpeg/positions.txt \

>     --robust_alignment_max_error 0.10

results in the following output 

Aligning reconstruction

-----------------------

 => Using 470 reference images

 => Alignment failed

why ?

[Johannes Schönberger]

Probably the error threshold is too small. What kind of scene are you reconstructing?

[christo...@gmail.com]

It is a uav mission over dense Forrest.

[Johannes Schönberger]

SFM models have unknown scene scale, so you would have to estimate a good error threshold upon visual inspection. COLMAP scales the scene to the interval [-10, 10] in the largest direction.

[christo...@gmail.com]

hmmm.... seems to work but one question remains... The heights seems to be incredible low which I guess is related to the camera settings. Is there a possibility to read out the camera instrincts through command line?

[Johannes Schönberger]

The camera intrinsics are stored in the cameras.{bin|txt}, which can be read using the provided Python/Matlab scripts. Alternatively, you can convert the binary format to text using the model_converter executable and then read out the contents using your favorite text reader program.

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