Files
shenzhen-solitaire/test/cv_helper.py
2019-04-23 11:24:31 +02:00

81 lines
2.2 KiB
Python

import itertools
from typing import Tuple, List, Dict
import zipfile
import io
import json
import dataclasses
import numpy as np # type: ignore
import cv2 # type: ignore
from .context import shenzhen_solitaire
from shenzhen_solitaire.cv import adjustment
from shenzhen_solitaire.cv import card_finder
def pixelcount(image: np.ndarray) -> List[Tuple[Tuple[int, int, int], int]]:
p: Dict[Tuple[int, int, int], int] = {(0, 0, 0): 0}
for pixel in itertools.chain.from_iterable(image):
x = tuple(pixel)
if x in p:
p[x] += 1
else:
p[x] = 1
B = sorted(p.items(), key=lambda x: x[1])
return B
def simplify(image: np.ndarray) -> None:
cv2.imshow("Window", image)
cv2.waitKey(0)
cv2.destroyWindow("Window")
print(*card_finder.simplify(image)[1].items(), sep='\n')
cv2.imshow("Window", image)
cv2.waitKey(0)
cv2.destroyWindow("Window")
def calibrate(image: np.ndarray) -> None:
adj = adjustment.adjust_field(image)
squares = card_finder.get_field_squares(image, adj)
catalogue = card_finder.catalague_cards(squares)
simplified_catalogue = []
for square, card in catalogue:
simplified_catalogue.append((card_finder.simplify(square), card))
zip_stream = io.BytesIO()
with zipfile.ZipFile(zip_stream, "w") as zip_file:
zip_file.writestr('adjustment.json', json.dumps(dataclasses.asdict(adj)))
file_stream = io.BytesIO()
np.save(file_stream, squares[0], allow_pickle=False)
print(file_stream.getvalue())
zip_file.writestr('0.dat', file_stream.getvalue())
print()
print(zip_stream.getvalue())
with open('myzip.zip', 'wb') as fd:
fd.write(zip_stream.getvalue())
def main() -> None:
with open("Solitaire.png", 'rb') as fd:
img_str = fd.read()
nparr = np.frombuffer(img_str, np.uint8)
image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
#print(squares[0])
def main2() -> None:
file_stream = None
with zipfile.ZipFile('myzip.zip', "r") as zip_file:
file_stream = io.BytesIO(zip_file.read('0.dat'))
A = np.load(file_stream)
print(A)
if __name__ == "__main__":
main()
main2()