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Made border detection work

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This commit is contained in:
Lukas Wölfer
2020-02-08 00:42:55 +01:00
parent cf89e4c694
commit 07f8cae238
7 changed files with 112 additions and 61 deletions
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53
shenzhen_solitaire/card_detection/adjustment.py
View File

@@ -10,31 +10,36 @@ import cv2
@dataclass
class Adjustment:
"""Configuration for a grid"""
x: int
y: int
w: int
h: int
dx: int
dy: int
x: int = 0
y: int = 0
w: int = 0
h: int = 0
dx: int = 0
dy: int = 0
def get_square(adjustment: Adjustment, index_x: int = 0,
index_y: int = 0) -> Tuple[int, int, int, int]:
def get_square(
adjustment: Adjustment, index_x: int = 0, index_y: int = 0
) -> Tuple[int, int, int, int]:
"""Get one square from index and adjustment"""
return (adjustment.x + adjustment.dx * index_x,
adjustment.y + adjustment.dy * index_y,
adjustment.x + adjustment.w + adjustment.dx * index_x,
adjustment.y + adjustment.h + adjustment.dy * index_y)
return (
adjustment.x + adjustment.dx * index_x,
adjustment.y + adjustment.dy * index_y,
adjustment.x + adjustment.w + adjustment.dx * index_x,
adjustment.y + adjustment.h + adjustment.dy * index_y,
)
def adjust_squares(
image: numpy.ndarray,
count_x: int,
count_y: int,
adjustment: Optional[Adjustment] = None) -> Adjustment:
image: numpy.ndarray,
count_x: int,
count_y: int,
adjustment: Optional[Adjustment] = None,
) -> Adjustment:
if not adjustment:
adjustment = Adjustment(0, 0, 0, 0, 0, 0)
adjustment = Adjustment(w=10, h=10)
def _adjustment_step(keycode: int) -> None:
assert adjustment is not None
@@ -59,21 +64,19 @@ def adjust_squares(
while True:
working_image = image.copy()
for index_x, index_y in itertools.product(
range(count_x), range(count_y)):
for index_x, index_y in itertools.product(range(count_x), range(count_y)):
square = get_square(adjustment, index_x, index_y)
cv2.rectangle(working_image,
(square[0], square[1]),
(square[2], square[3]),
(0, 0, 0))
cv2.imshow('Window', working_image)
cv2.rectangle(
working_image, (square[0], square[1]), (square[2], square[3]), (0, 0, 0)
)
cv2.imshow("Window", working_image)
keycode = cv2.waitKey(0)
print(keycode)
if keycode == 27:
break
_adjustment_step(keycode)
cv2.destroyWindow('Window')
cv2.destroyWindow("Window")
return adjustment

25
shenzhen_solitaire/card_detection/board_parser.py
View File

@@ -2,7 +2,7 @@
import numpy as np
from .configuration import Configuration
from ..board import Board, NumberCard, SpecialCard
from ..board import Board, NumberCard, SpecialCard, Card
from . import card_finder
import cv2
from typing import Iterable, Any, List, Tuple, Union
@@ -37,12 +37,13 @@ def get_square_iterator(
return zip(grouped_squares, grouped_border_squares)
def match_template(template: np.ndarray, search_image: np.ndarray) -> int:
def match_template(template: np.ndarray, search_image: np.ndarray) -> float:
"""Return matchiness for the template on the search image"""
res = cv2.matchTemplate(search_image, template, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
assert isinstance(max_val, int)
return max_val
assert isinstance(max_val, (int, float))
return float(max_val)
def parse_square(
@@ -70,13 +71,13 @@ def parse_square(
return (best_name, row_finished)
def parse_board(image: np.ndarray, conf: Configuration) -> Board:
def parse_field(image: np.ndarray, conf: Configuration) -> List[List[Card]]:
"""Parse a screenshot of the game, using a given configuration"""
square_iterator = get_square_iterator(
image, conf, row_count=Board.MAX_ROW_SIZE, column_count=8
image, conf, row_count=Board.MAX_ROW_SIZE, column_count=Board.MAX_COLUMN_SIZE
)
result = Board()
for group_index, (square_group, border_group) in enumerate(square_iterator):
result = []
for square_group, border_group in square_iterator:
group_field = []
for index, (square, border_square) in enumerate(
zip(square_group, border_group)
@@ -86,6 +87,12 @@ def parse_board(image: np.ndarray, conf: Configuration) -> Board:
if row_finished:
break
result.field[group_index] = group_field
result.append(group_field)
return result
def parse_board(image: np.ndarray, conf: Configuration) -> Board:
result = Board()
result.field = parse_field(image, conf)
return result

62
shenzhen_solitaire/card_detection/configuration.py
View File

@@ -14,8 +14,12 @@ from . import card_finder
from .. import board
ADJUSTMENT_FILE_NAME = "adjustment.json"
FIELD_ADJUSTMENT_KEY = "field"
BORDER_ADJUSTMENT_KEY = "border"
GOAL_ADJUSTMENT_KEY = "goal"
BUNKER_ADJUSTMENT_KEY = "bunker"
HUA_ADJUSTMENT_KEY = "hua"
TEMPLATES_DIRECTORY = "templates"
CARD_BORDER_DIRECTORY = "borders"
@@ -28,11 +32,26 @@ PICTURE_EXTENSION = "png"
class Configuration:
"""Configuration for solitaire cv"""
field_adjustment: adjustment.Adjustment
border_adjustment: adjustment.Adjustment
catalogue: List[Tuple[np.ndarray, Union[board.SpecialCard, board.NumberCard]]]
card_border: List[np.ndarray]
empty_card: List[np.ndarray]
field_adjustment: adjustment.Adjustment = dataclasses.field(
default_factory=adjustment.Adjustment
)
border_adjustment: adjustment.Adjustment = dataclasses.field(
default_factory=adjustment.Adjustment
)
goal_adjustment: adjustment.Adjustment = dataclasses.field(
default_factory=adjustment.Adjustment
)
bunker_adjustment: adjustment.Adjustment = dataclasses.field(
default_factory=adjustment.Adjustment
)
hua_adjustment: adjustment.Adjustment = dataclasses.field(
default_factory=adjustment.Adjustment
)
catalogue: List[
Tuple[np.ndarray, Union[board.SpecialCard, board.NumberCard]]
] = dataclasses.field(default_factory=list)
card_border: List[np.ndarray] = dataclasses.field(default_factory=list)
empty_card: List[np.ndarray] = dataclasses.field(default_factory=list)
meta: Dict[str, str] = dataclasses.field(default_factory=dict)
@@ -55,10 +74,9 @@ def _save_catalogue(
zip_file.write(
myfile, arcname=f"{TEMPLATES_DIRECTORY}/{file_name}.{PICTURE_EXTENSION}"
)
def _save_adjustments(
zip_file: zipfile.ZipFile, conf: Configuration
) -> None:
def _save_adjustments(zip_file: zipfile.ZipFile, conf: Configuration) -> None:
adjustments = {}
adjustments[FIELD_ADJUSTMENT_KEY] = dataclasses.asdict(conf.field_adjustment)
adjustments[BORDER_ADJUSTMENT_KEY] = dataclasses.asdict(conf.border_adjustment)
@@ -75,7 +93,7 @@ def save(conf: Configuration, filename: str) -> None:
with zipfile.ZipFile(zip_stream, "w") as zip_file:
_save_adjustments(zip_file, conf)
_save_catalogue(zip_file, conf.catalogue)
# TODO: Save card_borders and emtpy_card
with open(filename, "wb") as zip_archive:
zip_archive.write(zip_stream.getvalue())
@@ -98,7 +116,9 @@ def _load_catalogue(zip_file: zipfile.ZipFile,) -> List[Tuple[np.ndarray, board.
mydir = tempfile.mkdtemp()
for template_filename in (
x for x in zip_file.namelist() if x.startswith(TEMPLATES_DIRECTORY + "/")
x
for x in zip_file.namelist()
if x.startswith(TEMPLATES_DIRECTORY + "/") and x != TEMPLATES_DIRECTORY + "/"
):
myfile = zip_file.extract(template_filename, path=mydir)
catalogue.append((cv2.imread(myfile), _parse_file_name(template_filename),))
@@ -111,7 +131,9 @@ def _load_dir(zip_file: zipfile.ZipFile, dirname: str) -> List[np.ndarray]:
image_filenames = [
image_filename
for image_filename in (
x for x in zip_file.namelist() if x.startswith(dirname + "/")
x
for x in zip_file.namelist()
if x.startswith(dirname + "/") and x != dirname + "/"
)
]
images = [
@@ -127,18 +149,28 @@ def load(filename: str) -> Configuration:
with zipfile.ZipFile(filename, "r") as zip_file:
adjustment_dict = json.loads(zip_file.read(ADJUSTMENT_FILE_NAME))
return Configuration(
result = Configuration(
field_adjustment=adjustment.Adjustment(
**adjustment_dict[FIELD_ADJUSTMENT_KEY]
**adjustment_dict.get(FIELD_ADJUSTMENT_KEY, {})
),
border_adjustment=adjustment.Adjustment(
**adjustment_dict[BORDER_ADJUSTMENT_KEY]
**adjustment_dict.get(BORDER_ADJUSTMENT_KEY, {})
),
goal_adjustment=adjustment.Adjustment(
**adjustment_dict.get(GOAL_ADJUSTMENT_KEY, {})
),
bunker_adjustment=adjustment.Adjustment(
**adjustment_dict.get(BUNKER_ADJUSTMENT_KEY, {})
),
hua_adjustment=adjustment.Adjustment(
**adjustment_dict.get(HUA_ADJUSTMENT_KEY, {})
),
catalogue=_load_catalogue(zip_file),
card_border=_load_dir(zip_file, CARD_BORDER_DIRECTORY),
empty_card=_load_dir(zip_file, EMPTY_CARD_DIRECTORY),
meta={},
)
return result
def generate(image: np.ndarray) -> Configuration: