Extracting xyz coordinates for image/photo/camera locations

[spatialdigger]

I have an external scripted workflow which does the usual processes (adds photos, aligns, import target coords, through to dense point cloud, code included for reference)

I would like to access the individual image/photo name and the calculated camera xyz location and any other directional information that exists so this can be brought into a pandas dataframe.

Any idea where to start?

Code: [Select]

    doc = Metashape.Document()

    # set up a chunk
    chunk = doc.addChunk()

    # add photos
    chunk.addPhotos(filenames=photo_list)

    print(str(len(photo_list)) + " Added")

    # detect markers
    chunk.detectMarkers()
    # assign crs
    chunk.crs = Metashape.CoordinateSystem("EPSG::27700")

    count_photos = len(image_list)

    # import target coords
    chunk.importReference(path=targets_path, format=Metashape.ReferenceFormatCSV,
                        columns='nxyz', delimiter=',',create_markers=True, skip_rows=1)

    chunk.matchPhotos(downscale=2, generic_preselection=True, reference_preselection=True, keypoint_limit=80000,
                      tiepoint_limit=3000)  # , filter_mask=False, mask_tiepoints=True, keypoint_limit=40000, tiepoint_limit=4000

    chunk.alignCameras(adaptive_fitting=True)
    chunk.buildDepthMaps(downscale=4)
    chunk.buildDenseCloud()
    chunk.buildModel(source_data=Metashape.DataSource.DenseCloudData, surface_type=Metashape.Arbitrary, interpolation=Metashape.EnabledInterpolation, face_count=Metashape.MediumFaceCount)
    doc.save(filepath)
    chunk = doc.chunk
    espgCode = 27700
    localCRS = Metashape.CoordinateSystem("EPSG::" + str(espgCode))
    proj = Metashape.OrthoProjection()
    proj.crs = localCRS
    chunk.buildOrthomosaic(surface_data=Metashape.DataSource.ModelData, blending_mode=Metashape.MosaicBlending, projection=proj)
    chunk.exportRaster(path=ortho_path, image_format=Metashape.ImageFormatJPEG, save_world=True, projection=proj)
    docu_path = os.path.join(docu_path, "report.pdf")
    chunk.exportReport(path=docu_path, title=job + selected_job)
    doc.save(filepath)

[Paulo]

Hi spatial digger,

look at following script from Agisoft Github https://github.com/agisoft-llc/metashape-scripts/blob/master/src/save_estimated_reference.py. It will save to a text file for each camera its reference source location, estimated location, error and sigma as well as reference source rotation, estimated rotation, error and sigma....
as in (where XYZ is location info and YPR rotation info in yaw, pitch, roll format):

Code: [Select]

IMG_6256.JPG
       XYZ source: 350457.283156 2852834.941277 760.147899
       XYZ error: -0.501244 0.393616 0.685989
       XYZ estimated: 350456.782032 2852835.334798 760.833885
       XYZ sigma: 0.014008 0.014108 0.019027
       YPR source: 77.144 6.770 0.814
       YPR error: 5.127 1.539 -2.952
       YPR estimated: 82.271 8.309 -2.138
       YPR sigma: 0.001 0.004 0.004
IMG_6257.JPG
       XYZ source: 350505.734175 2852832.854006 759.132261
       XYZ error: 0.582248 -0.318101 1.874715
       XYZ estimated: 350506.316283 2852832.535981 761.006984
       XYZ sigma: 0.013379 0.013864 0.018723
       YPR source: 96.045 4.840 -7.320
       YPR error: -0.441 2.846 7.053
       YPR estimated: 95.604 7.686 -0.267
       YPR sigma: 0.001 0.004 0.005
... This should get you a good start.... of course this is a more elaborate script developed to help understand how different items are calculated...

if you just want to export to some txt file the camera id, estimated location and rotation just use the chunk.exportReference(....) as in attached screen copy .... consult API reference manual for details on parameters used...

[spatialdigger]

Thanks Paulo,

I'm trying to build it up bit by bit so I understand.

I can access the cameras via chunk.cameras

But when I run the following I get:
   
    TypeError: argument 1 must be Metashape.Metashape.Vector, not None

Code: [Select]

for camera in chunk.cameras:
    error = chunk.transform.matrix.mulp(camera.center) - chunk.crs.unproject(camera.reference.location)

[spatialdigger]

ok this kind of does the job, I'd rather have it in a pandas data frame but I can read it in from the csv.

Code: [Select]

chunk.exportReference(path=archive_path + '\\cameras.csv',format=Metashape.ReferenceFormatCSV, items=Metashape.ReferenceItemsCameras, columns='nuvwdef', delimiter =',')

[Paulo]

Good to hear the CSV export can do the job,

for the previous error, it means one of your chunk's cameras  is either not aligned (camera.center is None) or has no reference location (camera.reference.location is None)....also could be you have some camera keyframes (part of an animation or Camera Track)  in your project  and these camera types have no reference location....

[spatialdigger]

We have a slate with the project details, so obviously that wont align, and we wouldn't want it to, I've added a try/except clause in, but I welcome recommendations, incl. a way to avoid writing to csv and keep in pandas df

[Paulo]

Hi again,

if you want to write a pandas Df with ImageId, Estimated position (3) and estimated rotation (3), i.e. 7 colums following code would do the trick:

Code: [Select]

import numpy as np
import pandas as pd
def getAntennaTransform(sensor):
    location = sensor.antenna.location
    if location is None:
        location = sensor.antenna.location_ref
    rotation = sensor.antenna.rotation
    if rotation is None:
        rotation = sensor.antenna.rotation_ref
    return Metashape.Matrix.Diag((1, -1, -1, 1)) * Metashape.Matrix.Translation(location) * Metashape.Matrix.Rotation(Metashape.Utils.ypr2mat(rotation))

def getcolumnsName(euler_angles):
       if euler_angles == Metashape.EulerAnglesOPK:
           return ['Id','X_Est','Y_Est','Z_Est','Omega_Est','Phi_Est','Kappa_Est']
       if euler_angles == Metashape.EulerAnglesPOK:
           return ['Id','X_Est','Y_Est','Z_Est','Phi_Est','Omega_Est','Kappa_Est']
       if euler_angles == Metashape.EulerAnglesYPR:
           return ['Id','X_Est','Y_Est','Z_Est','Yaw_Est','Pitch_Est','Roll_Est']
       if euler_angles == Metashape.EulerAnglesANK:
           return ['Id','X_Est','Y_Est','Z_Est','Alpha_Est','Nu_Est','Kappa_Est']

chunk = Metashape.app.document.chunk
est = list()
for camera in chunk.cameras:
    if not camera.transform:
        continue

    transform = chunk.transform.matrix
    crs = chunk.crs

    if chunk.camera_crs:
        transform = Metashape.CoordinateSystem.datumTransform(crs, chunk.camera_crs) * transform
        crs = chunk.camera_crs

    ecef_crs = crs.geoccs

    camera_transform = transform * camera.transform
    antenna_transform = getAntennaTransform(camera.sensor)
    location_ecef = camera_transform.translation() + camera_transform.rotation() * antenna_transform.translation()
    rotation_ecef = camera_transform.rotation() * antenna_transform.rotation()

    est_loc = Metashape.CoordinateSystem.transform(location_ecef, ecef_crs, crs)
    if chunk.euler_angles == Metashape.EulerAnglesOPK or chunk.euler_angles == Metashape.EulerAnglesPOK:
        localframe = crs.localframe(location_ecef)
    else:
        localframe = ecef_crs.localframe(location_ecef)

    est_rot = Metashape.utils.mat2euler(localframe.rotation() * rotation_ecef, chunk.euler_angles)
    est.append([camera.label,est_loc.x,est_loc.y,est_loc.z,est_rot.x,est_rot.y,est_rot.z])
pd.DataFrame(np.array(est),columns = getcolumnsName(chunk.euler_angles))
and resut would be like the following for 3 image data set....