Messages

1

General / Re: Issue of orthophoto with DJI Phantom4 Multispectral

« on: March 18, 2021, 08:33:15 PM »

Different dataset offcourse than mention in this thread but issues seems 99.9% the same. We still have the issue in 1.7.2

2

General / Re: Issue of orthophoto with DJI Phantom4 Multispectral

« on: March 01, 2021, 12:45:24 PM »

We often see similar issues. Seems to be following exactly the seamlines so might also be related to image blending (next to flight conditions, camera calibration). We had this issue with this sensor but also with MicaSense RedEdge & Altum.

3

General / Re: Thermal Reflectance Map from RJPG Images

« on: October 08, 2020, 12:43:05 PM »

Different person, same issue. I will try to convert it to grayscale tifs. Altough real RJPG support would be great.

4

General / Re: Streaks in orthomosaic

« on: September 03, 2020, 11:33:49 AM »

Might be related to the mosaic blending method and illumination of the images?

5

Python and Java API / Re: Export DTYPE

« on: July 13, 2020, 04:57:44 PM »

I understand. Would be (really) great if someday Agisoft could automatically select the smallest possible dtype to avoid generating unnecessarily large files.

6

Python and Java API / Export DTYPE

« on: July 07, 2020, 03:12:46 PM »

We are currently exporting orthomsaics by using a band transformation and exporting the index value. We use of NoData value of -10000. This provide an tif with Floating point 32Bit. The original values easily fit in a smaller DTYPE. Is it possible to change this (with python?) Thanks!

7

Python and Java API / Re: Access camera locations and error estimates through python?

« on: January 20, 2020, 01:09:56 PM »

I think the issue is solved. I combined some old code from post with a similar question.

Code: [Select]

    errors = Metashape.Vector([0,0,0,0])
    n = 0
    for camera in chunk.cameras:
        if not camera.transform:
            continue
        if not camera.reference.location:
            continue

        estimated_geoc = chunk.transform.matrix.mulp(camera.center)
        error = estimated_geoc - chunk.crs.unproject(camera.reference.location)
        m = chunk.crs.localframe(chunk.transform.matrix.mulp(camera.center))
        error = m.mulv(error)
        errors += Metashape.Vector([error.x **2, error.y **2, error.z **2, error.norm() **2])
        n += 1

    total_error = math.sqrt(errors[3] / n)
    print("total_error", total_error)
Thank you

8

Python and Java API / Re: Access camera locations and error estimates through python?

« on: January 13, 2020, 05:56:20 PM »

Thank you. X error , Y error and Z error are good now.

One more question. How do you calculate XY (m) and Total error (m)?

9

Python and Java API / Export OrthoMosaic with nodata_value

« on: January 10, 2020, 03:20:17 PM »

Hi,

Maybe at the wrong location in this forum but I am now using this function to export an orthomosaic with a nodata value of -10000 in Python:
       
chunk.exportRaster(db.rgb_pg_path, nodata_value=-10000, save_alpha=True, white_background=False, source_data=Metashape.OrthomosaicData, image_compression=compression)

Sometimes when we have issues with the automatic processing we would like to export an orthomosaic with the normal user interface. However I cannot find an option to set the nodata_value there?

Kind regards,

Sven

10

Python and Java API / Re: Access camera locations and error estimates through python?

« on: January 09, 2020, 05:28:23 PM »

I am able to access the x, y, z and total error for each camera now.
However when I calculate the average for each component for all cameras I get a different value then visible in the report.
Which is weird because I think it is just a simple average?

I am now using the following code

 total_error = []
    x_error = []
    y_error = []
    z_error = []
    for camera in chunk.cameras:
        error = chunk.transform.matrix.mulp(camera.center) - chunk.crs.unproject(camera.reference.location)
        m = chunk.crs.localframe(chunk.transform.matrix.mulp(camera.center))
        error = m.mulv(error)
        print(camera.label, error.x, error.y, error.z, error.norm())
        x_error.append(error.x)
        y_error.append(error.y)
        z_error.append(error.z)
        total_error.append(error.norm())
    mean_total_error = statistics.mean(total_error)
    mean_x_error = statistics.mean(x_error)
    mean_y_error = statistics.mean(y_error)
    mean_z_error = statistics.mean(z_error)

11

Python and Java API / Re: buildOrthoMosaic/buildDEM projection Python v1.6

« on: January 08, 2020, 05:47:39 PM »

Thank you for your help. Our scripts are up and running again with v1.6

12

Python and Java API / Access camera locations and error estimates through python?

« on: January 08, 2020, 02:19:27 PM »

In the processing report there is a nice table with X-Error, Y-Error, Z-Error, XY error and total error (m).
Is it possible to access this information with the python API?
We want to automatically check if the accuracy falls within the expected range (especially important for RTK flights).

Thanks in advance,

Sven

13

Python and Java API / buildOrthoMosaic/buildDEM projection Python v1.6

« on: January 07, 2020, 07:01:37 PM »

Hi,

I used to build the orthomosaic with the following line of code:

chunk.buildOrthomosaic(surface_data=data_source_ortho, projection=localCRS, progress=progress_print)

I get a Value Error: Invalid argement value: projection:

localCRS = Metashape.CoordinateSystem("EPSG::" + str(utm1))

in this case:

localCRS = <CoordinateSystem 'WGS 84 / UTM zone 31N (EPSG::32631)'>

How do I need to provide the correct coordinate system with the new API?

Thanks in advance,

Sven

14

Python and Java API / Re: How to export BigTIFF orthomosaic from v1.6 Python API?

« on: January 07, 2020, 06:52:31 PM »

Thank I had a similar question. Big tiff is now working.
How can I export data with TiffCompressionLZW?

Thanks!

15

General / radiometric jpgs from FLIR Vue Pro R alignment issues

« on: January 07, 2020, 12:03:26 PM »

I already processed many thermal flights as grayscale tifs and even though the temperature calibration is often quite hit or miss (but that is an hardware issue) I was able to create an Orthomosaic.

Now I received a dataset from a client that has been aquired as radiometric jpgs and I am stuck. The image alignment completely fails. Am I missing something if there a different workflow for radiometric jpgs compared with thermal images aquired as grayscale tif?

Kind regards,

Sven