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import numpy as np
import logging
from raspberryturk import lib_path, RaspberryTurkError, setup_console_logging
def _chessboard_perspective_transform_path():
return lib_path('chessboard_perspective_transform.npy')
def get_chessboard_perspective_transform():
M = np.load(_chessboard_perspective_transform_path())
return M
except IOError:
raise RaspberryTurkError("No chessboard perspective transform found. Camera position recalibration required.")
def recalibrate_camera_position():
import cv2
from itertools import product
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import PolynomialFeatures
from scipy.spatial.distance import euclidean
board_size = (7,7)
_, frame = cv2.VideoCapture(0).read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
found, corners = cv2.findChessboardCorners(gray, board_size, flags=cv2.CALIB_CB_NORMALIZE_IMAGE|cv2.CALIB_CB_ADAPTIVE_THRESH)
assert found, "Couldn't find chessboard."
z = corners.reshape((49,2))
board_center = z[24]
frame_center = frame.shape[1] / 2.0, frame.shape[0] / 2.0
assert euclidean(board_center, frame_center) < 20.0, "Camera is not centered over chessboard."
X_train = np.array(list(product(np.linspace(-3, 3, 7), np.linspace(-3, 3, 7))))
poly = PolynomialFeatures(degree=4)
X_train = poly.fit_transform(X_train)
m_x = LinearRegression(), z[:, 0])
m_y = LinearRegression(), z[:, 1])
def predict(i, j):
features = poly.fit_transform(np.array([i, j]))
return m_x.predict(features), m_y.predict(features)
P = []
Q = []
P.append(predict(-4.0, -4.0))
Q.append((0.0, 0.0))
P.append(predict(-4.0, 4.0))
Q.append((0.0, 480.0))
P.append(predict(4.0, -4.0))
Q.append((480.0, 0.0))
P.append(predict(4.0, 4.0))
Q.append((480.0, 480.0))
Q = np.array(Q, np.float32)
P = np.array(P, np.float32).reshape(Q.shape)
ind = np.lexsort((P[:,1],P[:,0]))
P = P[ind]
M = cv2.getPerspectiveTransform(P, Q), M)
def main():
logger = logging.getLogger(__name__)"Begin camera position recalibration...")
except AssertionError as e:
else:"Camera position recalibration successful.")
if __name__ == '__main__':