from PIL import Image
from pylab import *


def point(img_path):
    Image.MAX_IMAGE_PIXELS = 100000000000
    # im = array(Image.open('best_result.png'))
    im = array(Image.open(img_path))
    imshow(im)
    print('Please click 2 points')
    x = ginput(2)
    # show()
    return x


if __name__ == '__main__':
    x = point('cut_orchard2.png')
    print('you clicked:', x)

import cv2
import numpy as np

img = cv2.imread('C:\\Users\\mimi\\Desktop\\1.jpg')
a = []
b = []


def on_EVENT_LBUTTONDOWN(event, x, y, flags, param):
    if event == cv2.EVENT_LBUTTONDOWN:
        xy = "%d,%d" % (x, y)
        a.append(x)
        b.append(y)
        cv2.circle(img, (x, y), 1, (255, 0, 0), thickness=-1)
        cv2.putText(img, xy, (x, y), cv2.FONT_HERSHEY_PLAIN,
                    1.0, (0, 0, 0), thickness=1)
        cv2.imshow("image", img)


cv2.namedWindow("image")
cv2.setMouseCallback("image", on_EVENT_LBUTTONDOWN)
cv2.imshow("image", img)
cv2.waitKey(0)
print(a[0], b[0])

img[b[0]:b[1], a[0]:a[1], :] = 0  # 注意是 行，列（y軸的，X軸）
cv2.imshow("image", img)
cv2.waitKey(0)
print(a, b)

from point import point
import cv2
import numpy as np


# 輸入兩個對角點的坐標，裁剪圖片
def cut_pic(img_path, point_list):
    [(x1, y1), (x2, y2)] = point_list
    img = cv2.imread(img_path)
    # img = np.array(img)
    # 新圖片
    print(img.shape)
    # 此處注意opencv的順序是先h，后w，然后c。
    img_new = img[y1:y2, x1:x2, :]
    cv2.imwrite("save.png", img_new)


if __name__ == '__main__':
    # img_path = "xiatian_qingwa.jpg"
    img_path = "best_result1.png"
    # ----------------------------
    # 得到兩個對角點的坐標
    point_two = point(img_path)
    point_two_new = []
    # 清空列表
    # point_two.clear()
    for i in point_two:
        i_new = list(map(int, i))
        point_two_new.append(i_new)
    # [(4393, 426), (12439, 12439)]
    print(point_two_new)
    # ----------------------------
    # point_two_new = [(4393, 426), (12439, 12439)]
    cut_pic(img_path, point_two_new)

from PIL import Image
Image.MAX_IMAGE_PIXELS = 2300000000

from PIL import ImageFile, Image
ImageFile.LOAD_TRUNCATED_IMAGES = True
Image.MAX_IMAGE_PIXELS = None