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Linting, worked on catalogization

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Lukas Wölfer
2019-04-23 02:46:41 +02:00
parent 1ce1d55705
commit 36884dcb14
4 changed files with 92 additions and 42 deletions
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74
shenzhen_solitaire/cv/card_finder.py
View File

@@ -6,6 +6,7 @@ import itertools
import numpy as np # type: ignore
import cv2 # type: ignore
from .adjustment import Adjustment, get_square
from ..board import Card, NumberCard, SpecialCard
def _extract_squares(image: np.ndarray,
@@ -71,20 +72,20 @@ def get_simplified_squares(image: np.ndarray,
def _find_single_square(search_square: np.ndarray,
template_square: np.ndarray) -> Tuple[int, Tuple[int, int]]:
assert search_square.shape[0] <= template_square.shape[0]
assert search_square.shape[1] <= template_square.shape[1]
assert search_square.shape[0] >= template_square.shape[0]
assert search_square.shape[1] >= template_square.shape[1]
best_result: Optional[Tuple[int, Tuple[int, int]]] = None
for x, y in itertools.product(
range(template_square.shape[0], search_square.shape[0] - 1, -1),
range(template_square.shape[1], search_square.shape[1] - 1, -1)):
p = template_square[x - search_square.shape[0]:x,
y - search_square.shape[1]:y] - search_square
range(search_square.shape[0], template_square.shape[0] - 1, -1),
range(search_square.shape[1], template_square.shape[1] - 1, -1)):
p = search_square[x - template_square.shape[0]:x,
y - template_square.shape[1]:y] - template_square
count = cv2.countNonZero(p)
if not best_result or count < best_result[0]:
best_result = (
count,
(x - search_square.shape[0],
y - search_square.shape[1]))
(x - template_square.shape[0],
y - template_square.shape[1]))
assert best_result
return best_result
@@ -96,19 +97,58 @@ def find_square(search_square: np.ndarray,
best_count = 0
best_coord: Optional[Tuple[int, int]] = None
for square in squares:
count, coord = _find_single_square(square, search_square)
count, coord = _find_single_square(search_square, square)
if not best_set or count < best_count:
best_set = True
best_square = square
best_count = count
best_coord = coord
assert isinstance(best_square, np.ndarray)
assert isinstance(best_coord, tuple)
cv2.imshow("Window", best_square -
search_square[best_coord[0]:best_coord[0] +
best_square.shape[0], best_coord[1]:best_coord[1] +
best_square.shape[1]])
while cv2.waitKey(0) != 27:
pass
cv2.destroyWindow("Window")
return (best_square, best_count)
def catalague_cards(squares: List[np.ndarray]) -> List[Tuple[np.ndarray, Card]]:
cv2.namedWindow("Catalogue", cv2.WINDOW_NORMAL)
cv2.waitKey(1)
result: List[Tuple[np.ndarray, Card]] = []
print(
"Card ID is [B]ai, [Z]hong, [F]a, [H]ua, [R]ed, [G]reen, [B]arkblack")
print("Numbercard e.g. R3")
special_card_map = {
'b': SpecialCard.Bai,
'z': SpecialCard.Zhong,
'f': SpecialCard.Fa,
'h': SpecialCard.Hua}
suit_map = {
'r': NumberCard.Suit.Red,
'g': NumberCard.Suit.Green,
'b': NumberCard.Suit.Black}
for square in squares:
while True:
cv2.imshow("Catalogue", cv2.resize(square, (500, 500)))
cv2.waitKey(1)
card_id = input("Card ID:").lower()
card_type: Optional[Card] = None
if len(card_id) == 1:
if card_id not in special_card_map:
print("hi")
continue
card_type = special_card_map[card_id]
elif len(card_id) == 2:
if not card_id[0] in suit_map:
continue
if not card_id[1].isdigit():
continue
if card_id[1] == '0':
continue
card_type = NumberCard(number=int(
card_id[1]), suit=suit_map[card_id[0]])
else:
continue
assert card_type is not None
result.append((square, card_type))
break
cv2.destroyWindow("Catalogue")
assert result is not None
return result

41
test/cv_helper.py
View File

@@ -1,14 +1,15 @@
import itertools
from typing import Tuple, List, Dict
import numpy # type: ignore
import numpy as np # type: ignore
import cv2 # type: ignore
import zipfile
from .context import shenzhen_solitaire
from shenzhen_solitaire.cv import adjustment
from shenzhen_solitaire.cv import card_finder
def pixelcount(image: numpy.ndarray) -> List[Tuple[Tuple[int, int, int], int]]:
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)
@@ -20,22 +21,40 @@ def pixelcount(image: numpy.ndarray) -> List[Tuple[Tuple[int, int, int], int]]:
return B
def simplify(image: numpy.ndarray) -> None:
def simplify(image: np.ndarray) -> None:
cv2.imshow("Window", image)
cv2.waitKey(0)
cv2.destroyWindow("Window")
print(*card_finder.simplify(image).items(), sep='\n')
print(*card_finder.simplify(image)[1].items(), sep='\n')
cv2.imshow("Window", image)
cv2.waitKey(0)
cv2.destroyWindow("Window")
def main() -> None:
image = cv2.imread("Solitaire.png")
image2 = cv2.imread("Solitaire2.png")
image2 = cv2.resize(image2, (1000, 629))
#image = cv2.imread("Solitaire.png")
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)
#image2 = cv2.imread("Solitaire2.png")
#image2 = cv2.resize(image2, (1000, 629))
image2 = cv2.imread("Solitaire.png")
adj = adjustment.adjust_field(image)
squares = card_finder.get_field_squares(image, adj)
print(squares[0])
np.save('0.dat', squares[0], allow_pickle=False)
assert 0
with open("0.dat", 'wb') as fd:
fd.write(squares[0].tobytes())
catalogue = card_finder.catalague_cards(squares[:5])
my_zip = zipfile.ZipFile('myzip.zip', mode='w')
for index, x in enumerate(catalogue):
my_zip.writestr(f"{index}.dat", x[0].tobytes())
my_zip.close()
assert 0
squares = card_finder.get_simplified_squares(image, adj)
print("Simplified")
@@ -50,7 +69,13 @@ def main() -> None:
print("Finding...")
found_image, certainty = card_finder.find_square(
image_squares[i], squares)
print(certainty)
def main2() -> None:
A = np.load('0.dat.npy')
print(A)
if __name__ == "__main__":
main()
main2()

15
test/helper.py
View File

@@ -1,15 +0,0 @@
from .context import shenzhen_solitaire
from shenzhen_solitaire import solver
from .boards import my_board
def main() -> None:
A = solver.solve(my_board)
for _, B in zip(range(1), A):
print(*B, sep='\n')
print(f"Solution: {len(B)}")
if __name__ == "__main__":
main()