import xml.etree.ElementTree as ET
from pathlib import Path

import cv2
import pandas as pd
from tqdm import tqdm

from manga_ocr_dev.env import MANGA109_ROOT


def get_books():
    root = MANGA109_ROOT / 'Manga109s_released_2021_02_28'
    books = (root / 'books.txt').read_text().splitlines()
    books = pd.DataFrame({
        'book': books,
        'annotations': [str(root / 'annotations' / f'{book}.xml') for book in books],
        'images': [str(root / 'images' / book) for book in books],
    })

    return books


def export_frames():
    books = get_books()

    data = []
    for book in tqdm(books.itertuples(), total=len(books)):
        tree = ET.parse(book.annotations)
        root = tree.getroot()
        for page in root.findall('./pages/page'):
            for frame in page.findall('./frame'):
                row = {}
                row['book'] = book.book
                row['page_index'] = int(page.attrib['index'])
                row['page_path'] = str(Path(book.images) / f'{row["page_index"]:03d}.jpg')
                row['page_width'] = int(page.attrib['width'])
                row['page_height'] = int(page.attrib['height'])
                row['id'] = frame.attrib['id']
                row['xmin'] = int(frame.attrib['xmin'])
                row['ymin'] = int(frame.attrib['ymin'])
                row['xmax'] = int(frame.attrib['xmax'])
                row['ymax'] = int(frame.attrib['ymax'])
                data.append(row)
    data = pd.DataFrame(data)

    data.page_path = data.page_path.apply(lambda x: '/'.join(Path(x).parts[-4:]))
    data.to_csv(MANGA109_ROOT / 'frames.csv', index=False)


def export_crops():
    crops_root = MANGA109_ROOT / 'crops'
    crops_root.mkdir(parents=True, exist_ok=True)
    margin = 10

    books = get_books()

    data = []
    for book in tqdm(books.itertuples(), total=len(books)):
        tree = ET.parse(book.annotations)
        root = tree.getroot()
        for page in root.findall('./pages/page'):
            for text in page.findall('./text'):
                row = {}
                row['book'] = book.book
                row['page_index'] = int(page.attrib['index'])
                row['page_path'] = str(Path(book.images) / f'{row["page_index"]:03d}.jpg')
                row['page_width'] = int(page.attrib['width'])
                row['page_height'] = int(page.attrib['height'])
                row['id'] = text.attrib['id']
                row['text'] = text.text
                row['xmin'] = int(text.attrib['xmin'])
                row['ymin'] = int(text.attrib['ymin'])
                row['xmax'] = int(text.attrib['xmax'])
                row['ymax'] = int(text.attrib['ymax'])
                data.append(row)
    data = pd.DataFrame(data)

    n_test = int(0.1 * len(data))
    data['split'] = 'train'
    data.loc[data.sample(len(data)).iloc[:n_test].index, 'split'] = 'test'

    data['crop_path'] = str(crops_root) + '\\' + data.id + '.png'

    data.page_path = data.page_path.apply(lambda x: '/'.join(Path(x).parts[-4:]))
    data.crop_path = data.crop_path.apply(lambda x: '/'.join(Path(x).parts[-2:]))
    data.to_csv(MANGA109_ROOT / 'data.csv', index=False)

    for page_path, boxes in tqdm(data.groupby('page_path'), total=data.page_path.nunique()):
        img = cv2.imread(str(MANGA109_ROOT / page_path))

        for box in boxes.itertuples():
            xmin = max(box.xmin - margin, 0)
            xmax = min(box.xmax + margin, img.shape[1])
            ymin = max(box.ymin - margin, 0)
            ymax = min(box.ymax + margin, img.shape[0])
            crop = img[ymin:ymax, xmin:xmax]
            out_path = (crops_root / box.id).with_suffix('.png')
            cv2.imwrite(str(out_path), crop)


if __name__ == '__main__':
    export_frames()
    export_crops()

import xml.etree.ElementTree as ET
from pathlib import Path

import cv2
import pandas as pd
from tqdm import tqdm

from manga_ocr_dev.env import MANGA109_ROOT


def get_books():
    root = MANGA109_ROOT / 'Manga109s_released_2021_02_28'
    books = (root / 'books.txt').read_text().splitlines()
    books = pd.DataFrame({
        'book': books,
        'annotations': [str(root / 'annotations' / f'{book}.xml') for book in books],
        'images': [str(root / 'images' / book) for book in books],
    })

    return books


def export_frames():
    books = get_books()

    data = []
    for book in tqdm(books.itertuples(), total=len(books)):
        tree = ET.parse(book.annotations)
        root = tree.getroot()
        for page in root.findall('./pages/page'):
            for frame in page.findall('./frame'):
                row = {}
                row['book'] = book.book
                row['page_index'] = int(page.attrib['index'])
                row['page_path'] = str(Path(book.images) / f'{row["page_index"]:03d}.jpg')
                row['page_width'] = int(page.attrib['width'])
                row['page_height'] = int(page.attrib['height'])
                row['id'] = frame.attrib['id']
                row['xmin'] = int(frame.attrib['xmin'])
                row['ymin'] = int(frame.attrib['ymin'])
                row['xmax'] = int(frame.attrib['xmax'])
                row['ymax'] = int(frame.attrib['ymax'])
                data.append(row)
    data = pd.DataFrame(data)

    data.page_path = data.page_path.apply(lambda x: '/'.join(Path(x).parts[-4:]))
    data.to_csv(MANGA109_ROOT / 'frames.csv', index=False)


def export_crops():
    crops_root = MANGA109_ROOT / 'crops'
    crops_root.mkdir(parents=True, exist_ok=True)
    margin = 10

    books = get_books()

    data = []
    for book in tqdm(books.itertuples(), total=len(books)):
        tree = ET.parse(book.annotations)
        root = tree.getroot()
        for page in root.findall('./pages/page'):
            for text in page.findall('./text'):
                row = {}
                row['book'] = book.book
                row['page_index'] = int(page.attrib['index'])
                row['page_path'] = str(Path(book.images) / f'{row["page_index"]:03d}.jpg')
                row['page_width'] = int(page.attrib['width'])
                row['page_height'] = int(page.attrib['height'])
                row['id'] = text.attrib['id']
                row['text'] = text.text
                row['xmin'] = int(text.attrib['xmin'])
                row['ymin'] = int(text.attrib['ymin'])
                row['xmax'] = int(text.attrib['xmax'])
                row['ymax'] = int(text.attrib['ymax'])
                data.append(row)
    data = pd.DataFrame(data)

    n_test = int(0.1 * len(data))
    data['split'] = 'train'
    data.loc[data.sample(len(data)).iloc[:n_test].index, 'split'] = 'test'

    data['crop_path'] = str(crops_root) + '\\' + data.id + '.png'

    data.page_path = data.page_path.apply(lambda x: '/'.join(Path(x).parts[-4:]))
    data.crop_path = data.crop_path.apply(lambda x: '/'.join(Path(x).parts[-2:]))
    data.to_csv(MANGA109_ROOT / 'data.csv', index=False)

    for page_path, boxes in tqdm(data.groupby('page_path'), total=data.page_path.nunique()):
        img = cv2.imread(str(MANGA109_ROOT / page_path))

        for box in boxes.itertuples():
            xmin = max(box.xmin - margin, 0)
            xmax = min(box.xmax + margin, img.shape[1])
            ymin = max(box.ymin - margin, 0)
            ymax = min(box.ymax + margin, img.shape[0])
            crop = img[ymin:ymax, xmin:xmax]
            out_path = (crops_root / box.id).with_suffix('.png')
            cv2.imwrite(str(out_path), crop)


if __name__ == '__main__':
    export_frames()
    export_crops()
