tom white dribnet

## .block
license: mit
height: 960

## mpl_cfaces.py
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt

from numpy.random import rand
from numpy import pi, arctan

def cface(ax, x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16,x17,x18):
    # x1 = height  of upper face
    # x2 = overlap of lower face

## .DS_Store

      
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                dribnet
                / .DS_Store
            
            
              Created
              July 5, 2023 22:01
                — forked from uwcc/.DS_Store
            
              
                Creative Coding 2: Project 1_Clock
              
          
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## spacy_intro.ipynb

      
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                dribnet
                / spacy_intro.ipynb
            
            
              Created
              July 25, 2017 22:26
                — forked from aparrish/spacy_intro.ipynb
            
              
                NLP Concepts with spaCy
              
          
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## stablediffusionwalk.py
"""
draws many samples from a diffusion model by slerp'ing around
the noise space, and dumps frames to a directory. You can then
stitch up the frames with e.g.:

$ ffmpeg -r 10 -f image2 -s 512x512 -i out/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p test.mp4

THIS FILE IS HACKY AND NOT CONFIGURABLE READ THE CODE, MAKE EDITS TO PATHS AND SETTINGS YOU LIKE
THIS FILE IS HACKY AND NOT CONFIGURABLE READ THE CODE, MAKE EDITS TO PATHS AND SETTINGS YOU LIKE
THIS FILE IS HACKY AND NOT CONFIGURABLE READ THE CODE, MAKE EDITS TO PATHS AND SETTINGS YOU LIKE

## .block
license: mit
height: 960

## .block
height: 540

## .block
license: mit

## .block
license: mit
height: 570

## .block
license: mit
	import matplotlib
	matplotlib.use('Agg')
	import matplotlib.pyplot as plt

	from numpy.random import rand
	from numpy import pi, arctan

	def cface(ax, x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16,x17,x18):
	# x1 = height of upper face
	# x2 = overlap of lower face
	"""
	draws many samples from a diffusion model by slerp'ing around
	the noise space, and dumps frames to a directory. You can then
	stitch up the frames with e.g.:

	$ ffmpeg -r 10 -f image2 -s 512x512 -i out/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p test.mp4

	THIS FILE IS HACKY AND NOT CONFIGURABLE READ THE CODE, MAKE EDITS TO PATHS AND SETTINGS YOU LIKE
	THIS FILE IS HACKY AND NOT CONFIGURABLE READ THE CODE, MAKE EDITS TO PATHS AND SETTINGS YOU LIKE
	THIS FILE IS HACKY AND NOT CONFIGURABLE READ THE CODE, MAKE EDITS TO PATHS AND SETTINGS YOU LIKE