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#! /bin/sh -x | |
DIR=`pwd` | |
FPS=24 | |
S_NUMBER=83 | |
LOOP=10 | |
STEREO="left-right" #"top-bottom" | |
DIST_PREFIX="dist" | |
SRC_DIR="360" | |
DIST_DIR=${DIR} |
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# %% | |
import stanza | |
import graphviz as gv | |
# %% | |
# https://qiita.com/ytaki0801/items/b8d7d4c778fe98966ce5 | |
def p_lex(p): | |
for s in '()[]{}",': |
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# %% | |
import bpy | |
import networkx as nx # /path/to/blender's/python -m pip install scipy networkx | |
import numpy as np | |
from scipy.spatial import ConvexHull | |
def obj2GraphAndXyzAndNormFiedler(obj): | |
edges = [(e.vertices[0], e.vertices[1]) for e in obj.data.edges] | |
G = nx.Graph(edges) |
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# %% | |
import bpy | |
from sklearn.cluster import KMeans # /path/to/blender's/python -m pip install scikit-learn | |
import networkx as nx # /path/to/blender's/python -m pip install scipy networkx | |
obj = bpy.data.objects['Armadillo'] | |
mesh = obj.data | |
edges = [(e.vertices[0], e.vertices[1]) for e in mesh.edges] | |
G = nx.Graph(edges) | |
S = [G.subgraph(c).copy() for c in nx.connected_components(G)] | |
G = S[0] |
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