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Hello, I'm using a RedEdge MX as a ground sensor and I would like to take into account also DLS for reflectance calibration.
Citing tutorial n. 3
"we assume a constant irradiance (over time) and a ratio of direct to diffuse irradiance of 6:1. These assumptions only hold approximately, and only for clear sky. Cloud cover can lead to dramatically different results"
and also
"If your intent is to simply use this code to correct your data, you can skip this section and access pose-corrected DLS data through the capture.dls_irradiance() method".
My questions are: does the function capture.dls_irradiance() give me a value that is not affected by the choice of the ratio of direct to diffuse irradiance? In other words, the values that this function gives me, can be used directly in the subsequent part of code, that I report her below:
Moreover, every time I tried tutorial n.3 in this part of code
import numpy as np
import micasense.dls as dls
import os, glob
import micasense.capture as capture
images_path = os.path.join('.','data','0000SET','000')
image_names = glob.glob(os.path.join(images_path,'IMG_0000_*.tif'))
cap = capture.Capture.from_filelist(image_names)
# set panel corners manually if zbar is not installed
panelCorners = [[[809,613],[648,615],[646,454],[808,452]],
[[772,623],[613,625],[610,464],[770,462]],
[[771,651],[611,653],[610,492],[770,490]],
[[829,658],[668,659],[668,496],[829,496]],
[[807,632],[648,634],[645,473],[805,471]]]
cap.set_panelCorners(panelCorners)
panel_radiances = np.array(cap.panel_radiance())
gave me this error
Cell In[285], line 1
np.array(panelCap.panel_radiance())
File ~\anaconda3\envs\micasense\lib\site-packages\micasense\capture.py:396 in panel_radiance
mean, _, _, _ = p.radiance()
File ~\anaconda3\envs\micasense\lib\site-packages\micasense\panel.py:268 in radiance
return self.region_stats(radiance_img,
File ~\anaconda3\envs\micasense\lib\site-packages\micasense\panel.py:239 in region_stats
rev_panel_pts = np.fliplr(region) # skimage and opencv coords are reversed
File <__array_function__ internals>:200 in fliplr
File ~\anaconda3\envs\micasense\lib\site-packages\numpy\lib\twodim_base.py:98 in fliplr
raise ValueError("Input must be >= 2-d.")
ValueError: Input must be >= 2-d.
What am I doing wrong? Thanks
The text was updated successfully, but these errors were encountered:
Hello, I'm using a RedEdge MX as a ground sensor and I would like to take into account also DLS for reflectance calibration.
Citing tutorial n. 3
"we assume a constant irradiance (over time) and a ratio of direct to diffuse irradiance of 6:1. These assumptions only hold approximately, and only for clear sky. Cloud cover can lead to dramatically different results"
and also
"If your intent is to simply use this code to correct your data, you can skip this section and access pose-corrected DLS data through the capture.dls_irradiance() method".
My questions are: does the function capture.dls_irradiance() give me a value that is not affected by the choice of the ratio of direct to diffuse irradiance? In other words, the values that this function gives me, can be used directly in the subsequent part of code, that I report her below:
For the correcting calibration of reflectance of the other captures should I go with:
Moreover, every time I tried tutorial n.3 in this part of code
gave me this error
What am I doing wrong? Thanks
The text was updated successfully, but these errors were encountered: