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Made image detection work

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This commit is contained in:
Lukas Wölfer
2020-02-05 01:51:30 +01:00
parent 7e18f1db1c
commit c1026c0640
7 changed files with 208 additions and 144 deletions
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114
shenzhen_solitaire/card_detection/card_finder.py
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@@ -3,25 +3,23 @@
from typing import List, Tuple, Optional, Dict
import enum
import itertools
import numpy as np # type: ignore
import cv2 # type: ignore
import numpy as np
import cv2
from .adjustment import Adjustment, get_square
from ..board import Card, NumberCard, SpecialCard
def _extract_squares(image: np.ndarray,
squares: List[Tuple[int,
int,
int,
int]]) -> List[np.ndarray]:
return [image[square[1]:square[3], square[0]:square[2]].copy()
for square in squares]
def _extract_squares(
image: np.ndarray, squares: List[Tuple[int, int, int, int]]
) -> List[np.ndarray]:
return [
image[square[1] : square[3], square[0] : square[2]].copy() for square in squares
]
def get_field_squares(image: np.ndarray,
adjustment: Adjustment,
count_x: int,
count_y: int) -> List[np.ndarray]:
def get_field_squares(
image: np.ndarray, adjustment: Adjustment, count_x: int, count_y: int
) -> List[np.ndarray]:
"""Return all squares in the field, according to the adjustment"""
squares = []
for index_x, index_y in itertools.product(range(count_y), range(count_x)):
@@ -31,64 +29,43 @@ def get_field_squares(image: np.ndarray,
class Cardcolor(enum.Enum):
"""Relevant colors for different types of cards"""
Bai = (65, 65, 65)
Black = (0, 0, 0)
Red = (22, 48, 178)
Green = (76, 111, 19)
Background = (178, 194, 193)
GREYSCALE_COLOR = {
Cardcolor.Bai: 50,
Cardcolor.Black: 100,
Cardcolor.Red: 150,
Cardcolor.Green: 200,
Cardcolor.Background: 250}
def simplify(image: np.ndarray) -> Tuple[np.ndarray, Dict[Cardcolor, int]]:
"""Reduce given image to the colors in Cardcolor"""
result_image: np.ndarray = np.zeros(
(image.shape[0], image.shape[1]), np.uint8)
result_dict: Dict[Cardcolor, int] = {c: 0 for c in Cardcolor}
for pixel_x, pixel_y in itertools.product(
range(result_image.shape[0]),
range(result_image.shape[1])):
pixel = image[pixel_x, pixel_y]
best_color: Optional[Tuple[Cardcolor, int]] = None
for color in Cardcolor:
mse = sum((x - y) ** 2 for x, y in zip(color.value, pixel))
if not best_color or best_color[1] > mse: #pylint: disable=E1136
best_color = (color, mse)
assert best_color
result_image[pixel_x, pixel_y] = GREYSCALE_COLOR[best_color[0]]
result_dict[best_color[0]] += 1
return (result_image, result_dict)
def _find_single_square(search_square: np.ndarray,
template_square: np.ndarray) -> Tuple[int, Tuple[int, int]]:
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]
best_result: Optional[Tuple[int, Tuple[int, int]]] = None
for margin_x, margin_y in itertools.product(
range(search_square.shape[0], template_square.shape[0] - 1, -1),
range(search_square.shape[1], template_square.shape[1] - 1, -1)):
search_region = search_square[margin_x -
template_square.shape[0]:margin_x, margin_y -
template_square.shape[1]:margin_y]
range(search_square.shape[0], template_square.shape[0] - 1, -1),
range(search_square.shape[1], template_square.shape[1] - 1, -1),
):
search_region = search_square[
margin_x - template_square.shape[0] : margin_x,
margin_y - template_square.shape[1] : margin_y,
]
count = cv2.countNonZero(search_region - template_square)
if not best_result or count < best_result[0]: #pylint: disable=E1136
if not best_result or count < best_result[0]: # pylint: disable=E1136
best_result = (
count,
(margin_x - template_square.shape[0],
margin_y - template_square.shape[1]))
(
margin_x - template_square.shape[0],
margin_y - template_square.shape[1],
),
)
assert best_result
return best_result
def find_square(search_square: np.ndarray,
squares: List[np.ndarray]) -> Tuple[np.ndarray, int]:
def find_square(
search_square: np.ndarray, squares: List[np.ndarray]
) -> Tuple[np.ndarray, int]:
"""Compare all squares in squares with search_square, return best matching one.
Requires all squares to be simplified."""
best_set = False
@@ -104,24 +81,24 @@ def find_square(search_square: np.ndarray,
return (best_square, best_count)
def catalogue_cards(squares: List[np.ndarray]
) -> List[Tuple[np.ndarray, Card]]:
def catalogue_cards(squares: List[np.ndarray]) -> List[Tuple[np.ndarray, Card]]:
"""Run manual cataloging for given squares"""
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]lack")
print("Card ID is [B]ai, [Z]hong, [F]a, [H]ua, [R]ed, [G]reen, [B]lack")
print("Numbercard e.g. R3")
special_card_map = {
'b': SpecialCard.Bai,
'z': SpecialCard.Zhong,
'f': SpecialCard.Fa,
'h': SpecialCard.Hua}
"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}
"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)))
@@ -137,10 +114,11 @@ def catalogue_cards(squares: List[np.ndarray]
continue
if not card_id[1].isdigit():
continue
if card_id[1] == '0':
if card_id[1] == "0":
continue
card_type = NumberCard(number=int(
card_id[1]), suit=suit_map[card_id[0]])
card_type = NumberCard(
number=int(card_id[1]), suit=suit_map[card_id[0]]
)
else:
continue
assert card_type is not None