import sys

import cv2
import numpy as np
from image_utils import find_outer_corner, point_on_axis, point_respect_line


class Stitch:
    def __init__(self, left_image, right_image):
        self.im_left = left_image
        self.im_right = right_image
        self.result = None

    def compute_matches(self):
        pass

    def merge(self):
        self.result = np.concatenate((self.im_left, self.im_right), axis=1)
        return self.result

    def transform(self):
        pts1 = np.float32([[180, 450], [5, 116], [338, 396]])
        pts2 = np.float32([[205, 370], [618, 126], [311, 407]])
        matrix = cv2.getAffineTransform(pts1, pts2)
        cols, rows, ch = self.im_right.shape

        warped_affine = cv2.warpAffine(self.im_right, matrix, (rows * 2, cols * 2))
        top_pnt, right_pnt, bottom_pnt, left_pnt = find_outer_corner(warped_affine)

        return warped_affine[top_pnt[1]:bottom_pnt[1], left_pnt[0]:right_pnt[0]]

    def perspective_trans(self):
        pts1 = np.float32([[250, 392], [412, 96], [640, 112], [0, 282]])
        pts2 = np.float32([[480, 640], [0, 0], [480, 0], [0, 640]])
        M = cv2.getPerspectiveTransform(pts1, pts2)
        self.im_left = cv2.warpPerspective(self.im_left, M, (480, 640))

    def split_image_1(self, image, point1=(618, 126), point2=(254, 388)):
        pnt1, pnt2 = point_on_axis(point1, point2)
        cv2.line(image, pnt1, pnt2, (0, 255, 0), 2)
        cv2.imshow('line', image)

    def split_image(self):
        pnt1, pnt2 = point_on_axis((618, 126), (254, 388))
        h, w = self.im_left.shape[:2]
        for x in range(w):
            for y in range(h):
                if point_respect_line((x, y), (pnt1, pnt2)) > 0:
                    self.im_left[y, x] = (255, 255, 255)

        pnt1, pnt2 = point_on_axis((5, 116), (267, 424))

        h, w = self.im_right.shape[:2]
        for x in range(w):
            for y in range(h):
                if point_respect_line((x, y), (pnt1, pnt2)) < 0:
                    self.im_right[y, x] = (255, 255, 255)

    def stitch(self):
        # self.split_image_1(self.im_left)
        self.split_image()
        # self.perspective_trans()
        cv2.imwrite('left.jpg', self.im_left)
        cv2.imwrite('right.jpg', self.im_right)
        # wraped = self.transform()

        # H = matcher.match(self.im_left, wraped)

        # print("Homography is : ", H)

        # cv2.imshow("warped", wraped)
        # cv2.waitKey(0)
        return None

    def imshow(self):
        cv2.imshow("left image", self.im_left)
        cv2.imshow("right Image", self.im_right)
        cv2.waitKey(0)


def read_images_from_file(file_paths='images.txt'):
    fp = open(file_paths, 'r')
    filenames = [each.rstrip('\r\n') for each in fp.readlines()]
    print(filenames)
    images = [cv2.resize(cv2.imread(each), (640, 480)) for each in filenames]
    return images


if __name__ == '__main__':
    try:
        args = sys.argv[1]
    except:
        args = "files_1.txt"

    image_list = read_images_from_file(args)

    s = Stitch(image_list[0], image_list[1])
    result = s.stitch()
    s.imshow()
    # cv2.namedWindow('result', cv2.WINDOW_AUTOSIZE)

    # cv2.imshow('result', result)
    cv2.waitKey(0)
    print("done")
    print("image written")
    cv2.destroyAllWindows()

import sys

import cv2
import numpy as np
from image_utils import find_outer_corner, point_on_axis, point_respect_line


class Stitch:
    def __init__(self, left_image, right_image):
        self.im_left = left_image
        self.im_right = right_image
        self.result = None

    def compute_matches(self):
        pass

    def merge(self):
        self.result = np.concatenate((self.im_left, self.im_right), axis=1)
        return self.result

    def transform(self):
        pts1 = np.float32([[180, 450], [5, 116], [338, 396]])
        pts2 = np.float32([[205, 370], [618, 126], [311, 407]])
        matrix = cv2.getAffineTransform(pts1, pts2)
        cols, rows, ch = self.im_right.shape

        warped_affine = cv2.warpAffine(self.im_right, matrix, (rows * 2, cols * 2))
        top_pnt, right_pnt, bottom_pnt, left_pnt = find_outer_corner(warped_affine)

        return warped_affine[top_pnt[1]:bottom_pnt[1], left_pnt[0]:right_pnt[0]]

    def perspective_trans(self):
        pts1 = np.float32([[250, 392], [412, 96], [640, 112], [0, 282]])
        pts2 = np.float32([[480, 640], [0, 0], [480, 0], [0, 640]])
        M = cv2.getPerspectiveTransform(pts1, pts2)
        self.im_left = cv2.warpPerspective(self.im_left, M, (480, 640))

    def split_image_1(self, image, point1=(618, 126), point2=(254, 388)):
        pnt1, pnt2 = point_on_axis(point1, point2)
        cv2.line(image, pnt1, pnt2, (0, 255, 0), 2)
        cv2.imshow('line', image)

    def split_image(self):
        pnt1, pnt2 = point_on_axis((618, 126), (254, 388))
        h, w = self.im_left.shape[:2]
        for x in range(w):
            for y in range(h):
                if point_respect_line((x, y), (pnt1, pnt2)) > 0:
                    self.im_left[y, x] = (255, 255, 255)

        pnt1, pnt2 = point_on_axis((5, 116), (267, 424))

        h, w = self.im_right.shape[:2]
        for x in range(w):
            for y in range(h):
                if point_respect_line((x, y), (pnt1, pnt2)) < 0:
                    self.im_right[y, x] = (255, 255, 255)

    def stitch(self):
        # self.split_image_1(self.im_left)
        self.split_image()
        # self.perspective_trans()
        cv2.imwrite('left.jpg', self.im_left)
        cv2.imwrite('right.jpg', self.im_right)
        # wraped = self.transform()

        # H = matcher.match(self.im_left, wraped)

        # print("Homography is : ", H)

        # cv2.imshow("warped", wraped)
        # cv2.waitKey(0)
        return None

    def imshow(self):
        cv2.imshow("left image", self.im_left)
        cv2.imshow("right Image", self.im_right)
        cv2.waitKey(0)


def read_images_from_file(file_paths='images.txt'):
    fp = open(file_paths, 'r')
    filenames = [each.rstrip('\r\n') for each in fp.readlines()]
    print(filenames)
    images = [cv2.resize(cv2.imread(each), (640, 480)) for each in filenames]
    return images


if __name__ == '__main__':
    try:
        args = sys.argv[1]
    except:
        args = "files_1.txt"

    image_list = read_images_from_file(args)

    s = Stitch(image_list[0], image_list[1])
    result = s.stitch()
    s.imshow()
    # cv2.namedWindow('result', cv2.WINDOW_AUTOSIZE)

    # cv2.imshow('result', result)
    cv2.waitKey(0)
    print("done")
    print("image written")
    cv2.destroyAllWindows()

# self.split_image_1(self.im_left) # self.perspective_trans() # wraped = self.transform() # H = matcher.match(self.im_left, wraped) # print("Homography is : ", H) # cv2.imshow("warped", wraped) # cv2.waitKey(0) # cv2.namedWindow('result', cv2.WINDOW_AUTOSIZE) # cv2.imshow('result', result)