Om-task2

import numpy as np
from PIL import Image, ImageOps


def detect(images):
    test_image = Image.open(images)
    test_image = ImageOps.grayscale(test_image)  # Converting to grayscale
    test_image = test_image.resize((500, 500))
    test_image = np.array(test_image)

    # To find those pixels which are different from black
    pts = np.argwhere(test_image > 0)
    ymin, xmin = pts.min(axis=0)
    ymax, xmax = pts.max(axis=0)

    # If the distance between the extreme points in X Direction is more than that in Y direction, then the arrow lies
    # in the horizontal direction, otherwise in the vertical direction
    X_dist = xmax - xmin
    Y_dist = ymax - ymin
    if X_dist > Y_dist:
        count1 = np.count_nonzero(np.where(pts == xmax))
        count2 = np.count_nonzero(np.where(pts == xmin))
        # If on the X axis there are greater number of points which are farther from the left edge of the window then
        # it means that the arrow is pointing left and vice versa
        if count1 > count2:
            return "LEFT"
        else:
            return "RIGHT"
    else:
        count1 = np.count_nonzero(np.where(pts == ymax))
        count2 = np.count_nonzero(np.where(pts == ymin))
        if count1 > count2:
            return "UP"
        else:
            return "DOWN"


if __name__ == '__main__':
    print("Enter the image file: ")
    images = input().split(" ")
    if len(images) == 1:
        ans = detect(images[0])
        print(ans)
    else:
        for i in images:
            with open("output.txt", 'a') as f:
                ans = detect(i)
                f.write(f"{ans}\n")