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freecell_image_loader.py
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freecell_image_loader.py
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#!/usr/bin/env python
from __future__ import print_function
from PIL import Image
import os
import sys
import math
import numpy as np
from collections import defaultdict
import click
def _scan_border(gen):
bright, dark = -1, -1
borders = []
for i, (r, g, b) in enumerate(gen):
if (r + g + b) > 650:
if bright != i-1: borders.append((True, i))
bright = i
dark = -1
else:
if dark != i-1: borders.append((False, i))
bright = -1
dark = i
return borders
def _render(borders):
_tmp = []
bright_from = -1
for onoff, i in borders:
if onoff == True:
bright_from = i
else:
_tmp.append((bright_from, i))
bright_from = -1
print(_tmp)
def scan_border_vert(im, x):
width, height = im.size
borders = _scan_border(im.getpixel((x, y)) for y in range(height))
_render( borders )
def scan_border_horiz(im, y):
width, height = im.size
borders = _scan_border(im.getpixel((x, y)) for x in range(width))
_render( borders )
def check_is_red(im, left, top, right, bottom):
st = defaultdict(int)
for y in range(top, bottom, 10):
for x in range(left, right, 10):
r, g, b = im.getpixel((x, y))
if r > 153 and g > 153 and b > 153:
st['white'] += 1
elif r > 102 and g < 102 and b < 102:
st['red'] += 1
elif r < 102 and g < 102 and b < 102:
st['black'] += 1
is_red = ('red' in st)
return is_red
def scan_image(pix, left, top, right, bottom, step=2):
width, height = right - left, bottom - top
_X = []
for y in range(top, bottom, step):
row = []
for x in range(left, right, step):
r, g, b = pix[x, y]
# avg = float(r + g + b) / 3 / 256 # [0.0, 1.9)
# avg = math.sqrt(avg)
# c = int(avg * scale)
if r >= 128 and g >= 128 and b >= 128: # white
c = 1
else: # red/black
c = 0
row.append(c)
_X.append(row)
return np.array(_X)
pix_mode = True # 0.452
# pix_mode = False # 0.513
def scan_freecell_image(image_path, step=2):
assert os.path.exists(image_path)
im = Image.open(image_path)
width, height = im.size
assert (width, height) == (750, 1334)
pix = im.load()
# scan_border_horiz(im, height/3)
# 24 (96) 114 (186) 204 (276) 294 (366) 384 (456) 474 (546) 564 (636) 654 (726)
data = []
num_processed = 0
for r in range(7):
top = 338 + 35*r
bottom = top + 35
row = []
for c in range(8 if r < 6 else 4):
left = 24 + 90*c # 24, 114, ..., 654 (-96)
right = left + 72 # 96, 186, ..., 726 (-24)
middle = (left + right) / 2
# scan_border_vert(im, left + 3)
# print((c, r))
img_left = scan_image(pix, left, top, middle, bottom, step)
img_right = scan_image(pix, middle, top, right, bottom, step)
row.append((img_left, img_right))
num_processed += 1
data.append(row)
assert num_processed == 52
return data
def visualize(X):
H, W = X.shape
for y in range(H):
for x in range(W):
c = X[y][x]
sys.stdout.write(".*"[c])
sys.stdout.write('\n')
sys.stdout.write('\n')
@click.command()
@click.argument('image-path', type=click.Path(exists=True, readable=True), default='freecell_snapshots/game_8758887.png')
# @click.argument('scale', type=int, default=2)
@click.argument('step', type=int, default=2)
def main(image_path, step):
def flatten_2d(mx):
return np.array([item for row in mx for item in row])
Xs = flatten_2d(scan_freecell_image(image_path, step=step))
X_nums, X_suites = [np.array(x) for x in zip(*Xs)]
for X_num, X_suite in zip(X_nums, X_suites):
visualize(X_num)
visualize(X_suite)
if __name__ == '__main__':
main()