import os
from PIL import Image, ImageOps
import numpy as np
import csv
from scipy.misc import imsave

input_folder = './input/ე' #needs to be filled

def cutImg(path, rotate, size):
    im = Image.open(path)
    rgb_im = im.convert('RGB')
    arr = np.array(rgb_im)

    startTop = 0
    endBot = arr.shape[1]
    letterFound = False

    for i in range(arr.shape[0]):
        isLetter = False
        for j in range(arr.shape[1]):
            if arr[i][j][0] <= 210 and arr[i][j][1] <= 210 and arr[i][j][2] <= 210:
                isLetter = True
                break

        if isLetter and not letterFound:
            letterFound = True
            startTop = i

        if not isLetter and letterFound:
            letterFound = False
            endBot = i

        letterFound = isLetter

    cropped = rgb_im.crop((0, startTop, arr.shape[1], endBot))

    if rotate == 1:
        arr1 = np.array(cropped)
        arr1 = np.rot90(arr1, axes=(0, -2))
        cropped = Image.fromarray(arr1)
    elif rotate == -1:
        arr1 = np.array(cropped)
        arr1 = np.rot90(arr1, axes=(-2, 0))
        cropped = Image.fromarray(arr1)

    if size != 0:
        cropped = cropped.resize((size, size), resample=Image.BILINEAR)

    cropped.save(path)


def cropImg(path):
    cutImg(path, 1, 0)
    cutImg(path, -1, 64)

def add_border(input_image, border, color=0):
    img = Image.open(input_image)
    if isinstance(border, int) or isinstance(border, tuple):
        bimg = ImageOps.expand(img, border=border, fill=color)
    else:
        raise RuntimeError('Border is not an integer or tuple!')
    return bimg

def binarize_array(numpy_array, threshold=180):
    for i in range(len(numpy_array)):
        for j in range(len(numpy_array[0])):
            if numpy_array[i][j] > threshold:
                numpy_array[i][j] = 255
            else:
                numpy_array[i][j] = 0
    return numpy_array

def convert_bw(img):
    image = img.convert('L')  # convert image to monochrome
    image_arr = np.array(image)
    image_arr = binarize_array(image_arr)
    return image_arr

def format_picture(image_path):
    img_borders = add_border(image_path, border=10, color='white')

    img_convert = img_borders.convert("RGBA")
    fff = Image.new('RGBA', img_convert.size, (255,)*4)
    out = Image.composite(img_convert, fff, img_convert)
    out = out.convert(img_borders.mode)

    img_bw = convert_bw(out)
    img_name = "{}.{}".format('test', 'jpg')
    save_path = "{}/{}".format(input_folder, img_name)

    imsave(save_path, img_bw)
    img = Image.open(save_path)
    img = img.resize((40, 40), resample=Image.BILINEAR)
    img.save(save_path)

    imsave("{}".format(save_path), img)
    cropImg("{}".format(save_path))
    image = Image.open(save_path)
    image = image.resize((40,40), resample = Image.BILINEAR)

    return convert_bw(image)

def generate_ans(image):
    arr = np.asarray(image)
    return arr

if __name__ == "__main__":
    image_files = os.listdir(input_folder)
    result = []
    for index in range(len(image_files)):
        image_array = format_picture('{}/{}'.format(input_folder, image_files[index]))
        image_array = image_array/255
        print(image_array.shape)
        ans = generate_ans(image_array)
        result += [[str(index), 'a']]
        break

    filename = 'result.csv'
    with open(filename, 'w') as f:
        csv.writer(f).writerows(result)