def solve_monkey(dist = False):
path = 'screenshots/%s.png' % datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
print('Taking screenshot')
call(['monkeyrunner', 'monkeyscreen.py', path])
print('Rotating')
call(['convert', '-rotate', '90', path, path])
print('Starting image solver')
val, xmarks, ymarks = solve_image(path, dist)
print('Generating solution path')
pathparts = splitext(path)
pathsol = '%s.sol_path.txt' % pathparts[0]
solfile = open(pathsol, 'w')
level = Level()
level.rows = len(val)
level.cols = len(val[0])
for x, y in product(range(level.cols), range(level.rows)):
c, t = val[y][x][0]
if t != 0:
continue
#print('Tracing color', c)
# Found a dot, start
cx, cy, ct = x, y, 0
while True:
# Print current
#print(cx, cy, ct)
solfile.write('%d %d\n' % (avg([xmarks[cx], xmarks[cx+1]]), avg([ymarks[cy], ymarks[cy+1]])))
# Find next
cx2, cy2, ct2 = -1, -1, -1
for nx, ny in level.neighbors(cx, cy):
nc, nt = val[ny][nx][0]
if nc >= 0 and connects(cx, cy, ct, nx, ny, nt):
cx2 = nx
cy2 = ny
ct2 = nt
break
# Found nothing - done
if cx2 == -1:
break
# Delete current and replace with next
val[cy][cx][0] = -1, -1
cx = cx2
cy = cy2
ct = ct2
# Delete last
val[cy][cx][0] = -1, -1
solfile.write('0 0\n')
solfile.close()
print('Solving on device')
call(['monkeyrunner', 'monkeypath.py', pathsol])
print('DONE')
def parse_image(path, pathcrop):
img = Image.open(path)
pix = img.load()
# TODO proper line detection instead of color matching
#border_color = (131, 97, 66) # brown
#border_color = (123, 125, 66) # green
border_color = pix[2, 180]
border_threshold = 128
xbuckets = defaultdict(int)
ybuckets = defaultdict(int)
# Find borders
for pos in product(xrange(img.size[0]), xrange(img.size[1])):
col = pix[pos]
dist2 = color_dist2(col, border_color)
if dist2 < border_threshold:
xbuckets[pos[0]] += 1
ybuckets[pos[1]] += 1
# Throw away below average (keeps the main lines)
xbuckets = {k:v for k,v in xbuckets.items() if v > avg(xbuckets.values())}
ybuckets = {k:v for k,v in ybuckets.items() if v > avg(ybuckets.values())}
# Merge neighbor buckets
xmarks = sorted(merge_buckets(xbuckets).keys())
ymarks = sorted(merge_buckets(ybuckets).keys())
#pprint(xmarks)
#pprint(ymarks)
# Figure out coordinates
minx, miny, maxx, maxy = avg([xmarks[0], xmarks[1]]), avg([ymarks[0], ymarks[1]]), avg([xmarks[-1], xmarks[-2]]), avg([ymarks[-1], ymarks[-2]])
xsize = len(xmarks) - 1
ysize = len(ymarks) - 1
level = Level()
level.cols = xsize
level.rows = ysize
level.tiles = [[None for i in range(xsize)] for j in range(ysize)]
circle_ratio = 0.4
out_ratio = 0.8
circle_threshold = 128
out_threshold = 1024
color_map = {}
map_threshold = 32
for i, j in product(range(xsize), range(ysize)):
x, y = avg([xmarks[i], xmarks[i+1]]), avg([ymarks[j], ymarks[j+1]])
w = min(xmarks[i+1] - xmarks[i], ymarks[j+1] - ymarks[j])
# Ignore empty
if pix[x, y] == (0, 0, 0):
continue
center = avg_color([pix[x+a, y+b] for a,b in product([-1, 0, 1], [-1, 0, 1])])
inside = sample(pix, x, y, w*circle_ratio/2, 8)
inside_dist2 = avg([color_dist2(center, ic) for ic in inside])
if inside_dist2 > circle_threshold:
#print('IN Rejecting ', i, j)
#print(inside)
#print(inside_dist2)
continue
outside = sample(pix, x, y, w*out_ratio/2, 8)
outside_dist2 = avg([color_dist2(center, oc) for oc in outside])
if outside_dist2 < out_threshold:
#print('OUT Rejecting ', i, j)
#print(outside)
#print(outside_dist2)
continue
id = None
for k, v in color_map.items():
if color_dist2(k, center) < map_threshold:
id = v
#print(x,y, 'id=', v)
if id is None:
id = len(color_map)
color_map[center] = id
level.tiles[j][i] = id
ImageDraw.Draw(img).ellipse((x-w/5-1, y-w/5-1, x+w/5+1, y+w/5+1), fill = 'black')
ImageDraw.Draw(img).ellipse((x-w/5, y-w/5, x+w/5, y+w/5), fill = 'white')
ImageDraw.Draw(img).text((x+1, y), str(id), fill = 'black')
ImageDraw.Draw(img).text((x-1, y), str(id), fill = 'black')
ImageDraw.Draw(img).text((x, y+1), str(id), fill = 'black')
ImageDraw.Draw(img).text((x, y-1), str(id), fill = 'black')
ImageDraw.Draw(img).text((x, y), str(id), fill = 'white')
level.colors = len(color_map)
img = img.crop((xmarks[0], ymarks[0], xmarks[-1], ymarks[-1]))
img = img.resize((int(img.size[0]*0.75), int(img.size[1]*0.75)))
img.show()
img.save(pathcrop)
return (level, {v:k for k,v in color_map.items()}, xmarks, ymarks)
