Read .pfm to numpy and conversion from pixel to world about rc_genicam_api

[zaksel]

This is interesting, but obviously wrong!

So when i read the data as 16 bit unsigned Int and after that generate two images from the 614400 Values like below and then reshape and get the pixel value:

data = np.fromfile(file, dtype='>u2')
data1 = data[::2]           #take even indices gives one image
data2 = data[1::2]          #take odd indices gives another
data = np.add(data1, data2) #add them and boom

I get dik=632 and p_z=887.5mm which seems way closer.
But i don´t get what happens there and i would really appreciate it if somebody can explain it to me :)

[flixr]

The Scan3dCoordinateScale is only needed when converting the 16bit image (as in the GenICam image buffer) to a floating point disparity value in pixels.

Since you are using the cli tool gc_stream which already saves the disparity image in float format (*.pfm), you alreay have the floating point value in pixels and the scaling should not be applied again.

[zaksel]

Ahh alright. Thank you! So i do the conversion like that:

p_x = (x-self.params['Scan3dPrincipalPointU']) * self.params['Scan3dBaseline']/dik
p_y = (y-self.params['Scan3dPrincipalPointV']) * self.params['Scan3dBaseline']/dik
p_z = self.params['Scan3dFocalLength'] * self.params['Scan3dBaseline']/dik