making it pretty
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64b1b91f21
commit
0d0fd3e638
2
draw.py
2
draw.py
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@ -5,8 +5,8 @@ machine chooch.
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"""
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import os
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import linedraw
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import stream
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import linedraw
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def draw(rec_filename):
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"""
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194
linedraw.py
194
linedraw.py
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@ -1,11 +1,15 @@
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#!/usr/bin/env python3
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"""
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Takes a raster image file and vectorizes it to create line art usable by
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a pen plotter.
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"""
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import os
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from random import *
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import math
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from random import *
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from PIL import Image, ImageDraw, ImageOps
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no_cv = True
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export_path = "output/out.svg"
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draw_contours = True
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draw_hatch = False
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@ -24,6 +28,7 @@ F_Blur = {
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(-2,1):4,(-1,1):9,(0,1):12,(1,1):9,(2,1):4,
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(-2,2):2,(-1,2):4,(0,2):5,(1,2):4,(2,2):2,
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}
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F_SobelX = {
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(-1,-1): 1,
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(0,-1): 0,
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@ -33,7 +38,8 @@ F_SobelX = {
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(1,0): -2,
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(-1,1): 1,
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(0,1): 0,
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(1,1): -1}
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(1,1) -1}
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F_SobelY = {
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(-1,-1): 1,
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(0,-1): 2,
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@ -45,23 +51,23 @@ F_SobelY = {
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(0,1): -2,
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(1,1): -1}
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def appmask(IM,masks):
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PX = IM.load()
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w,h = IM.size
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def appmask(image, masks):
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PX = image.load()
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w, h = image.size
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NPX = {}
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for x in range(0,w):
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for y in range(0,h):
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for x in range(0, w):
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for y in range(0, h):
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a = [0]*len(masks)
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for i in range(len(masks)):
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for p in masks[i].keys():
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if 0<x+p[0]<w and 0<y+p[1]<h:
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a[i] += PX[x+p[0],y+p[1]] * masks[i][p]
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if sum(masks[i].values())!=0:
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if 0 < x + p[0] < w and 0 < y + p[1] < h:
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a[i] += PX[x + p[0], y + p[1]] * masks[i][p]
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if sum(masks[i].values()) != 0:
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a[i] = a[i] / sum(masks[i].values())
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NPX[x,y]=int(sum([v**2 for v in a])**0.5)
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for x in range(0,w):
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for y in range(0,h):
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PX[x,y] = NPX[x,y]
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NPX[x,y] = int(sum([v**2 for v in a])**0.5)
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for x in range(0, w):
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for y in range(0, h):
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PX[x, y] = NPX[x, y]
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def distsum(*args):
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@ -71,8 +77,8 @@ def distsum(*args):
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"""
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dists = []
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for i in range(1, len(args):
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a = args[i][0]-args[i-1][0]
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b = args[i][1]-args[i-1][1]
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a = args[i][0] - args[i-1][0]
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b = args[i][1] - args[i-1][1]
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dist = (a**2 + b**2)**0.5
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dists.append(dist)
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return sum(dists)
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@ -83,14 +89,14 @@ def sortlines(lines):
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clines = lines[:]
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slines = [clines.pop(0)]
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while clines != []:
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x,s,r = None,1000000,False
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x, s, r = None, 1000000, False
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for l in clines:
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d = distsum(l[0],slines[-1][-1])
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dr = distsum(l[-1],slines[-1][-1])
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d = distsum(l[0], slines[-1][-1])
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dr = distsum(l[-1], slines[-1][-1])
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if d < s:
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x,s,r = l[:],d,False
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x, s, r = l[:], d, False
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if dr < s:
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x,s,r = l[:],s,True
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x, s, r = l[:], s, True
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clines.remove(x)
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if r == True:
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@ -99,49 +105,48 @@ def sortlines(lines):
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return slines
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def auto_canny(img, sigma=0.33):
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def auto_canny(image, sigma=0.33):
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"""
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Automatically determines appropriate upper and lower boundries for the Canny function.
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"""
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med = np.median(img)
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med = np.median(image)
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lower = int(max(0, (1.0 - sigma) * med))
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upper = int(min(255, (1.0 + sigma) * med))
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edges = cv2.Canny(img, lower, upper)
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edges = cv2.Canny(image, lower, upper)
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return edges
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def find_edges(IM):
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def find_edges(image):
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print("finding edges...")
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no_cv = True
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if no_cv:
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#appmask(IM,[F_Blur])
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appmask(IM,[F_SobelX,F_SobelY])
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#appmask(image, [F_Blur])
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appmask(image, [F_SobelX, F_SobelY])
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else:
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im = np.array(IM)
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im = cv2.GaussianBlur(im,(3,3),0)
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#im = cv2.Canny(im,100,200)
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im = auto_canny(im)
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IM = Image.fromarray(im)
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return IM.point(lambda p: p > 128 and 255)
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image = np.array(image)
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image = cv2.GaussianBlur(image, (3, 3), 0)
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#image = cv2.Canny(image,100,200)
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image = auto_canny(image)
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image = Image.fromarray(image)
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return image.point(lambda p: p > 128 and 255)
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def getdots(IM):
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def getdots(image):
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print("getting contour points...")
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PX = IM.load()
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PX = image.load()
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dots = []
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w,h = IM.size
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w, h = image.size
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for y in range(h-1):
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row = []
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for x in range(1,w):
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if PX[x,y] == 255:
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for x in range(1, w):
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if PX[x, y] == 255:
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if len(row) > 0:
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if x-row[-1][0] == row[-1][-1]+1:
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row[-1] = (row[-1][0],row[-1][-1]+1)
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if x-row[-1][0] == row[-1][-1] + 1:
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row[-1] = (row[-1][0], row[-1][-1] + 1)
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else:
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row.append((x,0))
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row.append((x, 0))
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else:
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row.append((x,0))
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row.append((x, 0))
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dots.append(row)
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return dots
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@ -150,110 +155,110 @@ def connectdots(dots):
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print("connecting contour points...")
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contours = []
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for y in range(len(dots)):
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for x,v in dots[y]:
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for x, v in dots[y]:
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if v > -1:
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if y == 0:
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contours.append([(x,y)])
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contours.append([(x, y)])
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else:
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closest = -1
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cdist = 100
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for x0,v0 in dots[y-1]:
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if abs(x0-x) < cdist:
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cdist = abs(x0-x)
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for x0, v0 in dots[y-1]:
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if abs(x0 - x) < cdist:
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cdist = abs(x0 - x)
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closest = x0
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if cdist > 3:
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contours.append([(x,y)])
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contours.append([(x, y)])
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else:
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found = 0
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for i in range(len(contours)):
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if contours[i][-1] == (closest,y-1):
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contours[i].append((x,y,))
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if contours[i][-1] == (closest, y-1):
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contours[i].append((x, y,))
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found = 1
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break
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if found == 0:
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contours.append([(x,y)])
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contours.append([(x, y)])
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for c in contours:
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if c[-1][1] < y-1 and len(c)<4:
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if c[-1][1] < y-1 and len(c) < 4:
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contours.remove(c)
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return contours
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def getcontours(IM,sc=2):
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def getcontours(image, sc=2):
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print("generating contours...")
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IM = find_edges(IM)
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IM1 = IM.copy()
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IM2 = IM.rotate(-90,expand=True).transpose(Image.FLIP_LEFT_RIGHT)
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dots1 = getdots(IM1)
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image = find_edges(image)
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image1 = IM.copy()
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image2 = image.rotate(-90, expand=True).transpose(Image.FLIP_LEFT_RIGHT)
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dots1 = getdots(image1)
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contours1 = connectdots(dots1)
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dots2 = getdots(IM2)
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dots2 = getdots(image2)
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contours2 = connectdots(dots2)
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for i in range(len(contours2)):
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contours2[i] = [(c[1],c[0]) for c in contours2[i]]
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contours = contours1+contours2
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contours2[i] = [(c[1], c[0]) for c in contours2[i]]
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contours = contours1 + contours2
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for i in range(len(contours)):
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for j in range(len(contours)):
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if len(contours[i]) > 0 and len(contours[j])>0:
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if distsum(contours[j][0],contours[i][-1]) < 8:
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contours[i] = contours[i]+contours[j]
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if len(contours[i]) > 0 and len(contours[j]) > 0:
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if distsum(contours[j][0], contours[i][-1]) < 8:
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contours[i] = contours[i] + contours[j]
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contours[j] = []
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for i in range(len(contours)):
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contours[i] = [contours[i][j] for j in range(0,len(contours[i]),8)]
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contours[i] = [contours[i][j] for j in range(0, len(contours[i]), 8)]
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contours = [c for c in contours if len(c) > 1]
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for i in range(0,len(contours)):
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contours[i] = [(v[0]*sc,v[1]*sc) for v in contours[i]]
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for i in range(0, len(contours)):
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contours[i] = [(v[0] * sc, v[1] * sc) for v in contours[i]]
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for i in range(0,len(contours)):
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for j in range(0,len(contours[i])):
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contours[i][j] = int(contours[i][j][0]+10),int(contours[i][j][1]+10)
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for i in range(0, len(contours)):
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for j in range(0, len(contours[i])):
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contours[i][j] = int(contours[i][j][0] + 10), int(contours[i][j][1] + 10)
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return contours
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def hatch(IM,sc=16):
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def hatch(image, sc=16):
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print("hatching...")
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PX = IM.load()
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w,h = IM.size
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PX = image.load()
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w,h = image.size
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lg1 = []
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lg2 = []
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for x0 in range(w):
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for y0 in range(h):
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x = x0*sc
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y = y0*sc
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if PX[x0,y0] > 144:
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x = x0 * sc
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y = y0 * sc
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if PX[x0, y0] > 144:
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pass
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elif PX[x0,y0] > 64:
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lg1.append([(x,y+sc/4),(x+sc,y+sc/4)])
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elif PX[x0,y0] > 16:
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lg1.append([(x,y+sc/4),(x+sc,y+sc/4)])
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lg2.append([(x+sc,y),(x,y+sc)])
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elif PX[x0, y0] > 64:
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lg1.append([(x, y+sc/4), (x+sc, y+sc/4)])
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elif PX[x0, y0] > 16:
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lg1.append([(x, y+sc/4), (x+sc, y+sc/4)])
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lg2.append([(x+sc, y), (x, y+sc)])
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else:
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lg1.append([(x,y+sc/4),(x+sc,y+sc/4)])
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lg1.append([(x,y+sc/2+sc/4),(x+sc,y+sc/2+sc/4)])
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lg2.append([(x+sc,y),(x,y+sc)])
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lg1.append([(x, y+sc/4), (x+sc, y+sc/4)])
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lg1.append([(x, y+sc/2 + sc/4), (x+sc, y+sc/2 + sc/4)])
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lg2.append([(x+sc, y), (x, y+sc)])
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lines = [lg1,lg2]
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for k in range(0,len(lines)):
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for i in range(0,len(lines[k])):
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for j in range(0,len(lines[k])):
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lines = [lg1, lg2]
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for k in range(0, len(lines)):
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for i in range(0, len(lines[k])):
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for j in range(0, len(lines[k])):
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if lines[k][i] != [] and lines[k][j] != []:
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if lines[k][i][-1] == lines[k][j][0]:
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lines[k][i] = lines[k][i]+lines[k][j][1:]
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lines[k][i] = lines[k][i] + lines[k][j][1:]
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lines[k][j] = []
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lines[k] = [l for l in lines[k] if len(l) > 0]
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lines = lines[0]+lines[1]
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lines = lines[0] + lines[1]
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for i in range(0,len(lines)):
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for j in range(0,len(lines[i])):
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lines[i][j] = int(lines[i][j][0]+sc),int(lines[i][j][1]+sc)-j
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for i in range(0, len(lines)):
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for j in range(0, len(lines[i])):
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lines[i][j] = int(lines[i][j][0] + sc), int(lines[i][j][1] + sc) - j
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return lines
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@ -268,6 +273,7 @@ def sketch(path, export_path=None, resolution=1024, hatch_size=16, contour_simpl
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width = int(resolution/contour_simplify)
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height = int(resolution/contour_simplify*image.size[0]/image.size[1])
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lines += getcontours(image.resize((width, height)), contour_simplify)
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if draw_hatch:
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width = int(resolution/hatch_size)
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height = int(resolution/hatch_size*image.size[0]/image.size[1])
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