hcwinsemius
hcwinsemius
For photogrammetry it is helpful to have projected images with overlap on each face with its neighbouring faces.
Full traceback ```python --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Input In [54], in 6 #...and then filtered velocimetry as scalr 7 # p1 = ds_median_filt.velocimetry.plot.pcolormesh( 8 # ax=p.axes, (...)...
This example would return an error ``` cam_config = pyorc.CameraConfig(gcps=gcps) ax = plt.subplot() cam_config.set_corners(corners) cam_config.resolution = 0.02 cam_config.window_size = 15 ax = cam_config.plot() ``` ``` --------------------------------------------------------------------------- AttributeError Traceback (most recent...
Idea to base this on a quantile of nr of available samples, estimated from locations where number of values is not zero. Pseudo-code ``` # count the amount of valid...
With highly turbulent flows patterns matching may require larger interrogation windows. Automated by doing a short velocimetry estimate with filtering over only a few frames with different settings.
x, y, z, u, v, s
export frames to geotiff (either rgb or grey)
implement for velocimetry, frames average
Can be implemented as `.frames.stabilize`. Use https://stackoverflow.com/questions/3431434/video-stabilization-with-opencv as a starting point