def read_and_solve(self, frame, polygon):
warped = warp(frame, polygon,
((0, 0), (WARPED_SIZE, 0), (WARPED_SIZE, WARPED_SIZE),
(0, WARPED_SIZE)), (WARPED_SIZE, WARPED_SIZE))
no_grid = remove_grid(warped)
puzzle = np.zeros((9, 9))
for i in range(9):
for j in range(9):
square = no_grid[round(i * STEP):round((i + 1) * STEP),
j * STEP:(j + 1) * STEP]
found, digit = find_digit(square)
if found:
digit = pad(digit)
puzzle[i][j] = predict(digit)
to_solve = [str(int(s)) for s in puzzle.flatten()]
solved = solve(to_solve)
try:
solution = [*solved.values()]
solution = np.reshape(solution, (9, 9))
self.solution = solution
self.solved = True
except:
pass
def run(img, data_gen=False):
processed = preprocess(img)
contours, hierarchy = cv2.findContours(processed, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_NONE)
if contours:
biggest = sorted(contours, key=area, reverse=True)[:3]
for cnt in biggest:
polygon = cv2.approxPolyDP(cnt, .02 * cv2.arcLength(cnt, True),
True)
x, y, w, h = cv2.boundingRect(polygon)
if w / h < 0.7 or w / h > 1.3 or len(polygon) != 4:
continue
polygon = polygon.reshape(4, 2)
polygon = order_points(polygon)
break
warped = warp(img, polygon,
((0, 0), (WARPED_SIZE, 0), (WARPED_SIZE, WARPED_SIZE),
(0, WARPED_SIZE)), (WARPED_SIZE, WARPED_SIZE))
no_grid = remove_grid(warped)
step = WARPED_SIZE // 9
puzzle = np.zeros((9, 9))
for i in range(9):
for j in range(9):
square = no_grid[round(i * step):round((i + 1) * step),
j * step:(j + 1) * step]
found, digit = find_digit(square)
if found:
digit = pad(digit)
puzzle[i][j] = predict(digit)
to_solve = [str(int(s)) for s in puzzle.flatten()]
solved = solve(to_solve)
if type(solved) == bool:
print("Puzzle was read incorrectly, skipping...")
return
solution = [*solved.values()]
solution = np.reshape(solution, (9, 9))
blank = np.zeros((*img.shape[:2][::-1], 4), dtype=np.uint8)
for (x, y), num in np.ndenumerate(solution):
cv2.putText(blank, str(int(num)),
((y) * step + 12, (1 + x) * step - 10),
cv2.FONT_HERSHEY_PLAIN, 3, (255, 255, 255, 255), 3)
overlay = warp(blank, ((0, 0), (WARPED_SIZE, 0),
(WARPED_SIZE, WARPED_SIZE), (0, WARPED_SIZE)),
polygon, (img.shape[1], img.shape[0]))
img = cv2.cvtColor(img, cv2.COLOR_RGB2RGBA)
img = cv2.add(img, overlay)
cv2.imshow("process", processed)
cv2.imshow("warp", warped)
cv2.imshow("no grid", no_grid)
cv2.imshow("solved", img)
cv2.waitKey(0)
"""
print(pred)
"""
try:
grid_digits[i] = (str(int(pred[0]) + 1))
except:
pass
except:
pass
# Finally, we have the grid.
# Predict the solution using the Norvig Sudoku Solving Algorithm
if len(grid_digits) == 81:
solved = solve(grid_digits)
if solved != False:
solved = list(solved.values())
# Print the text on our image
for e in range(81):
if grid_digits[e] != '0':
continue
sudoku_clr = cv2.putText(
sudoku_clr,
solved[e],
((rois[e][2] + rois[e][3]) // 2, rois[e][1]),
cv2.FONT_HERSHEY_SIMPLEX,
1, (0, 0, 255),
thickness=2)
[[0, 0], [cropped.shape[0] - 1, 0],
[cropped.shape[0] - 1, cropped.shape[1] - 1],
[0, cropped.shape[1] - 1]])
squares = infer_grid(cropped)
side = cropped.shape[:1]
side = side[0] / 9
#fetch digit boxes
digits = get_digits(cropped, squares, 28)
if len(digits) == 81:
digits = np.array(digits).reshape(9, 9, 28, 28)
digits = np.transpose(digits, (1, 0, 2, 3)).reshape(81, 28, 28, 1)
grid, solved = solve(digits)
if grid == ".................................................................................":
continue
if solved:
digits = np.array(digits).reshape(9, 9, 28, 28)
digits = np.transpose(digits, (1, 0, 2, 3)).reshape(81, 28, 28)
display(solved)
solved = list(
(np.array(list(solved.values())).reshape(9,
9).T).reshape(81))
# Print the text on our image
for number in range(81):