Worked on cv

shenzhen_solitaire/cv/card_finder.py

@@ -1,7 +1,9 @@
-from typing import List, Tuple
+from typing import List, Tuple, Optional, Dict
 import numpy
 from .adjustment import Adjustment, get_square
 from .. import board
+import enum
+import itertools
 
 
 def _extract_squares(image: numpy.ndarray,
@@ -20,3 +22,26 @@ def get_field_squares(image: numpy.ndarray,
         for iy in range(5):
             squares.append(get_square(adjustment, ix, iy))
     return _extract_squares(image, squares)
+
+
+class Cardcolor(enum.Enum):
+    Bai = (65, 65, 65)
+    Black = (0, 0, 0)
+    Red = (22, 48, 178)
+    Green = (76, 111, 19)
+    Background = (178, 194, 193)
+
+
+def simplify(image: numpy.ndarray) -> Dict[Cardcolor, int]:
+    result_dict: Dict[Cardcolor, int] = {c: 0 for c in Cardcolor}
+    for pixel in itertools.chain.from_iterable(image):
+        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:
+                best_color = (color, mse)
+        assert best_color
+        for i in range(3):
+            pixel[i] = best_color[0].value[i]
+        result_dict[best_color[0]] += 1
+    return result_dict

test/cv_helper.py

@@ -1,42 +1,45 @@
 from .context import shenzhen_solitaire
 from shenzhen_solitaire.cv import adjustment
 from shenzhen_solitaire.cv import card_finder
+from typing import Tuple, List, Dict
 import cv2
+import numpy
+import itertools
 
 A = cv2.imread("Solitaire.png")
 
-adj = adjustment.adjust_field(A)
-X = card_finder.get_field_squares(A, adj)
-for h in range(20):
-    p = {None: 0}
-    for x in X[h]:
-        for x2 in ((x1[0], x1[1], x1[2]) for x1 in x):
-            if x2 in p:
-                p[x2] += 1
-            else:
-                p[x2] = 1
-    B = sorted(p.items(), key=lambda x: x[1])
-    print(*B, sep='\n')
 
-    T = X[h].copy()
+def pixelcount(image: numpy.ndarray) -> List[Tuple[Tuple[int, int, int], int]]:
-    cv2.imshow("Window", T)
+    p: Dict[Tuple[int, int, int], int] = {(0, 0, 0): 0}
-    while cv2.waitKey(0) != 27:
+    for pixel in itertools.chain.from_iterable(image):
-        pass
+        x = tuple(pixel)
-    cv2.destroyWindow("Window")
+        if x in p:
-assert 0
+            p[x] += 1
-
-for ix, vx in enumerate(T):
-    for iy, vy in enumerate(vx):
-        if (vy[0] > 100) and (vy[1] > 100) and (vy[2] > 100):
-            T[ix, iy] = [255, 255, 255]
         else:
-            T[ix, iy] = [0, 0, 0]
+            p[x] = 1
+    B = sorted(p.items(), key=lambda x: x[1])
+    return B
 
-cv2.imshow("Window", T)
+def simplify(image: numpy.ndarray) -> None:
-cv2.waitKey(0)
+    cv2.imshow("Window", image)
-cv2.destroyWindow("Window")
+    cv2.waitKey(0)
+    cv2.destroyWindow("Window")
+    print(*card_finder.simplify(image).items(), sep='\n')
+    cv2.imshow("Window", image)
+    cv2.waitKey(0)
+    cv2.destroyWindow("Window")
 
 
-# for j in X:
+def main() -> None:
-#    cv2.imshow("Window", j)
+    adj = adjustment.adjust_field(A)
-#    cv2.waitKey(0)
+    image_squares = card_finder.get_field_squares(A, adj)
+    for img in image_squares:
+        print(*pixelcount(img), sep='\n')
+        cv2.imshow("Window", img)
+        cv2.waitKey(0)
+        cv2.destroyWindow("Window")
+        print()
+
+
+if __name__ == "__main__":
+    main()