| 12345678910111213141516171819202122232425262728293031 |
- """Probe image intensities along a set of radii"""
- from vedo import Image, dataurl, Circle, Lines, show
- from vedo.pyplot import plot
- import numpy as np
- img = Image(dataurl+'images/spheroid.jpg')
- cpt = [580,600,0]
- circle = Circle(cpt, r=500, res=36).wireframe()
- pts = circle.points # 3d coords of the points of the circle
- centers = np.zeros_like(pts) + cpt # create the same amount of center coords
- lines = Lines(centers, pts, res=50) # create Lines with 50 pts of resolution each
- lines.interpolate_data_from(img, n=3) # interpolate all msh data onto the lines
- print(lines.pointdata) # print all available arrays
- rgb = lines.pointdata['JPEGImage'] # extract the rgb intensities
- intensities = np.sum(rgb, axis=1) # sum the rgb values into one single intensity
- intensities_ray = np.split(intensities, 36) # split array so we can index any radius
- mean_intensity = np.mean(intensities_ray, axis=0) # compute the average intensity
- # add some optional plotting here:
- fig = plot(
- mean_intensity,
- lc='black', lw=5, spline=True,
- xtitle='radial distance', ytitle='intensity', aspect=16/9,
- )
- for i in range(0,36, 3):
- fig += plot(intensities_ray[i], lc=i, lw=1, like=fig)
- fig.scale(21).shift(60,-800) # scale up and move plot below the image
- show(img, circle, lines, fig, __doc__, size=(625,1000), zoom=1.5)
|
