File:Composition in 3D generated with the opensimplex noise.png
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Original file (1,504 × 2,160 pixels, file size: 3.3 MB, MIME type: image/png)
Captions
Captions
Abstract composition generated in Python using OpenSimplex noise 4D.
Summary[edit]
| Description |
English: Composition is generated in Python. Nodes of bezier curves are following a vector field generated with the open simplex noise algorithm. Scene is ray-traced with PlotOptiX package. |
| Date | |
| Source | Own work |
| Author | Rob su |
Licensing[edit]
I, the copyright holder of this work, hereby publish it under the following license:
This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
- You are free:
- to share – to copy, distribute and transmit the work
- to remix – to adapt the work
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
Source code (python)[edit]
import numpy as np
# docs, examples: https://plotoptix.rnd.team
from plotoptix import TkOptiX
from plotoptix.materials import m_plastic
from plotoptix.utils import simplex
b = 7000 # number of curves
n = 60 # number pf nodes per curve
dt = 0.1 # nodes distance
ofs = 50 * np.random.rand(3)
inp = 5 * np.random.rand(b, 3, 4) - 2.5
for c in range(b):
inp[c,1:,:3] = inp[c,0,:3]
inp[c,:,0] *= 1.75 # more spread in X
inp[c,:,3] = ofs # sync the 4'th dim of the noise
pos = np.zeros((b, n, 3), dtype=np.float32)
r = np.zeros((b, n), dtype=np.float32)
rnd = simplex(inp)
for t in range(n):
rt = 2.0 * (t+1) / (n+2) - 1
rt = 1 - rt*rt
r[:,t] = 0.07 * rt * rt
for c in range(b):
mag = np.linalg.norm(rnd[c])
r[c,t] *= 0.2 + 0.8 * mag # modulate thickness
rnd[c] = (0.08/mag) * rnd[c] # normalize and scale the step size
inp[c,:,:3] += rnd[c] # step in the field direction
pos[c,t] = inp[c,0,:3]
rnd = simplex(inp, rnd) # calculate noise at the next pos
rt = TkOptiX(start_now=False)
rt.set_param(
min_accumulation_step=1,
max_accumulation_frames=200,
rt_timeout=100000 # accept lower fps
)
exposure = 1.2; gamma = 1.8
rt.set_float("tonemap_exposure", exposure)
rt.set_float("tonemap_gamma", gamma)
rt.set_float("denoiser_blend", 0.25)
rt.add_postproc("Denoiser")
rt.setup_material("plastic", m_plastic)
for c in range(b):
if np.random.uniform() < 0.05:
rt.set_data("c"+str(c), pos=pos[c], r=1.1*r[c], c=[0.4, 0, 0], geom="BezierChain")
else:
rt.set_data("c"+str(c), pos=pos[c], r=r[c], c=0.94, geom="BezierChain", mat="plastic")
rt.setup_camera("dof_cam", eye=[0, 0, 12], target=[0, 0, 0], fov=57, focal_scale=0.7, cam_type="DoF")
rt.setup_light("l1", pos=[8, -3, 13], color=1.5*np.array([0.99, 0.97, 0.93]), radius=5)
rt.setup_light("l2", pos=[-17, -7, 5], u=[0, 0, -10], v=[0, 14, 0], color=1*np.array([0.25, 0.28, 0.35]), light_type="Parallelogram")
rt.set_ambient([0.05, 0.07, 0.09])
rt.set_background(0)
rt.show()
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 16:45, 23 May 2020 | | 1,504 × 2,160 (3.3 MB) | Rob su (talk | contribs) | Uploaded own work with UploadWizard |
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