Stable Diffusion: Difference between revisions
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m (→Scratch) |
m (→Scratch) |
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| (2 intermediate revisions by the same user not shown) | |||
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=Scratch= |
=Scratch= |
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* 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0 |
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* 0.00, 0.03, 0.05, 0.08, 0.10, 0.12, 0.15, 0.18, 0.20, 0.23, 0.25, 0.28, 0.30, 0.33, 0.35, 0.38, 0.40, 0.43, 0.45, 0.48, 0.50, 0.53, 0.55, 0.58, 0.60, 0.62, 0.65, 0.68, 0.70, 0.73, 0.75, 0.78, 0.80, 0.83, 0.85, 0.88, 0.90, 0.93, 0.95, 0.98, 1.00 |
* 0.00, 0.03, 0.05, 0.08, 0.10, 0.12, 0.15, 0.18, 0.20, 0.23, 0.25, 0.28, 0.30, 0.33, 0.35, 0.38, 0.40, 0.43, 0.45, 0.48, 0.50, 0.53, 0.55, 0.58, 0.60, 0.62, 0.65, 0.68, 0.70, 0.73, 0.75, 0.78, 0.80, 0.83, 0.85, 0.88, 0.90, 0.93, 0.95, 0.98, 1.00 |
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* 0.00, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95, 1.00 |
* 0.00, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95, 1.00 |
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| Line 7: | Line 8: | ||
* 0.000, 0.001, 0.005, 0.011, 0.020, 0.031, 0.045, 0.061, 0.080, 0.101, 0.125, 0.151, 0.180, 0.211, 0.245, 0.281, 0.320, 0.361, 0.405, 0.451, 0.500, 0.551, 0.605, 0.661, 0.720, 0.781, 0.845, 0.911, 0.980,1.0 |
* 0.000, 0.001, 0.005, 0.011, 0.020, 0.031, 0.045, 0.061, 0.080, 0.101, 0.125, 0.151, 0.180, 0.211, 0.245, 0.281, 0.320, 0.361, 0.405, 0.451, 0.500, 0.551, 0.605, 0.661, 0.720, 0.781, 0.845, 0.911, 0.980,1.0 |
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import numpy as np |
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for i in np.arange(0, 1.001, 0.05): |
for i in np.arange(0, 1.001, 0.05): |
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print(f'{i:0.2f}, ', end="") |
print(f'{i:0.2f}, ', end="") |
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import numpy as np |
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for i in np.arange(0, 1.001, 0.05): |
for i in np.arange(0, 1.001, 0.05): |
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print(f'{math.exp(i,1.02):0.3f}, ', end="") |
print(f'{math.exp(i,1.02):0.3f}, ', end="") |
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| Line 19: | Line 22: | ||
* [https://rentry.org/sdmodels Rentry model list] |
* [https://rentry.org/sdmodels Rentry model list] |
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* [https://rentry.org/voldy NovelAI guide] |
* [https://rentry.org/voldy NovelAI guide] |
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* [https://upscale.wiki/wiki/Model_Database Upscalers & Noise removal] |
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Latest revision as of 07:49, 18 November 2022
Scratch[edit | edit source]
- 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
- 0.00, 0.03, 0.05, 0.08, 0.10, 0.12, 0.15, 0.18, 0.20, 0.23, 0.25, 0.28, 0.30, 0.33, 0.35, 0.38, 0.40, 0.43, 0.45, 0.48, 0.50, 0.53, 0.55, 0.58, 0.60, 0.62, 0.65, 0.68, 0.70, 0.73, 0.75, 0.78, 0.80, 0.83, 0.85, 0.88, 0.90, 0.93, 0.95, 0.98, 1.00
- 0.00, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95, 1.00
Non-linear:
- 0.00, 0.01, 0.02, 0.04, 0.06, 0.09, 0.12, 0.16, 0.20, 0.25, 0.30, 0.36, 0.42, 0.49, 0.56, 0.64, 0.72, 0.81, 0.90, 1.00
- 0.000, 0.001, 0.005, 0.011, 0.020, 0.031, 0.045, 0.061, 0.080, 0.101, 0.125, 0.151, 0.180, 0.211, 0.245, 0.281, 0.320, 0.361, 0.405, 0.451, 0.500, 0.551, 0.605, 0.661, 0.720, 0.781, 0.845, 0.911, 0.980,1.0
import numpy as np
for i in np.arange(0, 1.001, 0.05):
print(f'{i:0.2f}, ', end="")
import numpy as np
for i in np.arange(0, 1.001, 0.05):
print(f'{math.exp(i,1.02):0.3f}, ', end="")