import numpy as np
import cv2
import glob
import matplotlib.pyplot as plt
import pickle

def calibrate_camera(save_pickle =0):
    '''
    Function to run camera calibration on set of calibration test images. Saves
    the resulting camera matrix and distortion values to a pickle file. Modified
    from lecture notes.
    '''
    nx = 9
    ny = 6
    # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
    objp = np.zeros((nx*ny,3), np.float32)
    objp[:,:2] = np.mgrid[0:nx, 0:ny].T.reshape(-1,2)

    # Arrays to store object points and image points from all the images.
    objpoints = [] # 3d points in real world space
    imgpoints = [] # 2d points in image plane.

    # Make a list of calibration images
    images = glob.glob('camera_cal/calibration*.jpg')

    # Step through the list and search for chessboard corners
    for idx, fname in enumerate(images):
        img = cv2.imread(fname)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

        # Find the chessboard corners
        ret, corners = cv2.findChessboardCorners(gray, (nx,ny), None)

        # If found, add object points, image points
        if ret == True:
            objpoints.append(objp)
            imgpoints.append(corners)

            # Draw and display the corners
            cv2.drawChessboardCorners(img, (nx,ny), corners, ret)
            #write_name = 'corners_found'+str(idx)+'.jpg'
            #cv2.imwrite(write_name, img)
            cv2.imshow('img', img)
            cv2.waitKey(500)

    cv2.destroyAllWindows()

    # Test undistortion on an image
    img = cv2.imread('camera_cal/calibration1.jpg')
    img_size = (img.shape[1], img.shape[0])

    # Do camera calibration given object points and image points
    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, img_size,None,None)


    dst = cv2.undistort(img, mtx, dist, None, mtx)
    cv2.imwrite('camera_cal/test_undst_1.jpg',dst)

    # Save the camera calibration result for later use (we won't worry about rvecs / tvecs)
    dist_pickle = {}
    dist_pickle["mtx"] = mtx
    dist_pickle["dist"] = dist
    if save_pickle:
        pickle.dump( dist_pickle, open( "camera_cal/wide_dist_pickle.p", "wb" ) )
    return mtx,dist

if __name__ == "__main__":
    #dst = cv2.cvtColor(dst, cv2.COLOR_BGR2RGB)
    # Visualize undistortion
    f, (ax1, ax2) = plt.subplots(1, 2, figsize=(20,10))
    ax1.imshow(img)
    ax1.set_title('Original Image', fontsize=30)
    ax2.imshow(dst)
    ax2.set_title('Undistorted Image', fontsize=30)
    plt.show()

    # dist_pickle = pickle.load( open('camera_cal/wide_dist_pickle.p','rb'))
    # dst = cv2.undistort(img, dist_pickle['mtx'],dist_pickle['dist'], None,
    #                       dist_pickle['mtx'])
