154 lines
5.6 KiB
Python
154 lines
5.6 KiB
Python
"""Functions to detect card value"""
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from typing import List, Tuple, Optional, Dict
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import enum
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import itertools
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import numpy as np # type: ignore
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import cv2 # type: ignore
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from .adjustment import Adjustment, get_square
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from ..board import Card, NumberCard, SpecialCard
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def _extract_squares(image: np.ndarray,
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squares: List[Tuple[int,
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int,
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int,
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int]]) -> List[np.ndarray]:
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return [image[square[1]:square[3], square[0]:square[2]].copy()
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for square in squares]
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def get_field_squares(image: np.ndarray,
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adjustment: Adjustment,
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count_x: int,
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count_y: int) -> List[np.ndarray]:
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"""Return all squares in the field, according to the adjustment"""
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squares = []
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for index_x, index_y in itertools.product(range(count_y), range(count_x)):
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squares.append(get_square(adjustment, index_x, index_y))
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return _extract_squares(image, squares)
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class Cardcolor(enum.Enum):
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"""Relevant colors for different types of cards"""
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Bai = (65, 65, 65)
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Black = (0, 0, 0)
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Red = (22, 48, 178)
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Green = (76, 111, 19)
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Background = (178, 194, 193)
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GREYSCALE_COLOR = {
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Cardcolor.Bai: 50,
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Cardcolor.Black: 100,
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Cardcolor.Red: 150,
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Cardcolor.Green: 200,
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Cardcolor.Background: 250}
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def simplify(image: np.ndarray) -> Tuple[np.ndarray, Dict[Cardcolor, int]]:
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"""Reduce given image to the colors in Cardcolor"""
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result_image: np.ndarray = np.zeros(
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(image.shape[0], image.shape[1]), np.uint8)
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result_dict: Dict[Cardcolor, int] = {c: 0 for c in Cardcolor}
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for pixel_x, pixel_y in itertools.product(
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range(result_image.shape[0]),
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range(result_image.shape[1])):
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pixel = image[pixel_x, pixel_y]
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best_color: Optional[Tuple[Cardcolor, int]] = None
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for color in Cardcolor:
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mse = sum((x - y) ** 2 for x, y in zip(color.value, pixel))
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if not best_color or best_color[1] > mse: #pylint: disable=E1136
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best_color = (color, mse)
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assert best_color
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result_image[pixel_x, pixel_y] = GREYSCALE_COLOR[best_color[0]]
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result_dict[best_color[0]] += 1
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return (result_image, result_dict)
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def _find_single_square(search_square: np.ndarray,
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template_square: np.ndarray) -> Tuple[int, Tuple[int, int]]:
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assert search_square.shape[0] >= template_square.shape[0]
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assert search_square.shape[1] >= template_square.shape[1]
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best_result: Optional[Tuple[int, Tuple[int, int]]] = None
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for margin_x, margin_y in itertools.product(
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range(search_square.shape[0], template_square.shape[0] - 1, -1),
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range(search_square.shape[1], template_square.shape[1] - 1, -1)):
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search_region = search_square[margin_x -
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template_square.shape[0]:margin_x, margin_y -
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template_square.shape[1]:margin_y]
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count = cv2.countNonZero(search_region - template_square)
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if not best_result or count < best_result[0]: #pylint: disable=E1136
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best_result = (
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count,
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(margin_x - template_square.shape[0],
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margin_y - template_square.shape[1]))
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assert best_result
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return best_result
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def find_square(search_square: np.ndarray,
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squares: List[np.ndarray]) -> Tuple[np.ndarray, int]:
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"""Compare all squares in squares with search_square, return best matching one.
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Requires all squares to be simplified."""
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best_set = False
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best_square: Optional[np.ndarray] = None
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best_count = 0
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for square in squares:
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count, _ = _find_single_square(search_square, square)
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if not best_set or count < best_count:
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best_set = True
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best_square = square
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best_count = count
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assert isinstance(best_square, np.ndarray)
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return (best_square, best_count)
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def catalogue_cards(squares: List[np.ndarray]
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) -> List[Tuple[np.ndarray, Card]]:
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"""Run manual cataloging for given squares"""
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cv2.namedWindow("Catalogue", cv2.WINDOW_NORMAL)
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cv2.waitKey(1)
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result: List[Tuple[np.ndarray, Card]] = []
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print(
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"Card ID is [B]ai, [Z]hong, [F]a, [H]ua, [R]ed, [G]reen, [B]lack")
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print("Numbercard e.g. R3")
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special_card_map = {
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'b': SpecialCard.Bai,
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'z': SpecialCard.Zhong,
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'f': SpecialCard.Fa,
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'h': SpecialCard.Hua}
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suit_map = {
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'r': NumberCard.Suit.Red,
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'g': NumberCard.Suit.Green,
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'b': NumberCard.Suit.Black}
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for square in squares:
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while True:
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cv2.imshow("Catalogue", cv2.resize(square, (500, 500)))
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cv2.waitKey(1)
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card_id = input("Card ID:").lower()
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card_type: Optional[Card] = None
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if len(card_id) == 1:
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if card_id not in special_card_map:
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continue
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card_type = special_card_map[card_id]
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elif len(card_id) == 2:
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if not card_id[0] in suit_map:
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continue
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if not card_id[1].isdigit():
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continue
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if card_id[1] == '0':
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continue
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card_type = NumberCard(number=int(
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card_id[1]), suit=suit_map[card_id[0]])
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else:
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continue
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assert card_type is not None
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print(card_type)
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result.append((square, card_type))
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break
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cv2.destroyWindow("Catalogue")
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assert result is not None
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return result
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