from dotenv import load_dotenv
import os

env = os.environ.get('env', 'dev')
load_dotenv(dotenv_path='.env.dev' if env == 'dev' else '.env', override=True)

import time
import traceback
import cv2
from helper.image_helper import pdf2image, image_orient_cls, page_detection_visual
from helper.page_detection.main import layout_analysis
from helper.content_recognition.main import rec
from helper.db_helper import insert_pdf2md_table
import tempfile
from loguru import logger
import datetime
import shutil


def _pdf2markdown_pipeline(pdf_path, tmp_dir):
    start_time = time.time()
    # 1. pdf -> images
    t1 = time.time()
    pdf2image(pdf_path, tmp_dir)
    t2 = time.time()

    # 2. 图片方向分类
    t3 = time.time()
    orient_cls_results = image_orient_cls(tmp_dir)
    t4 = time.time()
    for r in orient_cls_results:
        clsid = r[0]['class_ids'][0]
        filename = r[0]['filename']
        if clsid == 1 or clsid == 3:
            img = cv2.imread(filename)
            img = cv2.rotate(img, cv2.ROTATE_90_CLOCKWISE)
            cv2.imwrite(filename, img)
    
    filepaths = os.listdir(tmp_dir)
    filepaths.sort(key=lambda x: int(x.split('/')[-1].split('.')[0]))
    filepaths = [f'{tmp_dir}/{_}' for _ in filepaths]

    # filepaths = filepaths[250:251]

    # 3. 版面分析
    t5 = time.time()
    layout_detection_results = layout_analysis(filepaths)
    t6 = time.time()

    # 3.1 visual
    if int(os.environ['VISUAL']):
        visual_dir = './visual_images'
        for f in os.listdir(visual_dir):
            if f.endswith('.jpg'):
                os.remove(f'{visual_dir}/{f}')
        for i in range(len(layout_detection_results)):
            vis_img = page_detection_visual(layout_detection_results[i])
            cv2.imwrite(f'{visual_dir}/{i + 1}.jpg', vis_img)

    # 4. 内容识别
    t7 = time.time()
    layout_recognition_results = rec(layout_detection_results, tmp_dir)
    t8 = time.time()

    end_time = time.time()
    logger.info(f'{pdf_path} analysis completed in {round(end_time - start_time, 3)} seconds, including {round(t2 - t1, 3)} for pdf to image, {round(t4 - t3, 3)} second for image orient classification, {round(t6 - t5, 3)} seconds for page detection, and {round(t8 - t7, 3)} seconds for layout recognition, page number: {len(filepaths)}')

    return layout_recognition_results


def pdf2markdown_pipeline(pdf_path: str):
    pdf_name = pdf_path.split('/')[-1]
    start_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')
    process_status = 0
    tmp_dir = tempfile.mkdtemp()
    try:
        results = _pdf2markdown_pipeline(pdf_path, tmp_dir)
    except Exception:
        logger.error(f'analysis pdf error! \n{traceback.format_exc()}')
        process_status = 3
        end_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')
        insert_pdf2md_table(pdf_path, pdf_name, process_status, start_time, end_time, None)
        pdf_id = None
    else:
        process_status = 2
        end_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')
        pdf_id = insert_pdf2md_table(pdf_path, pdf_name, process_status, start_time, end_time, results)
    finally:
        shutil.rmtree(tmp_dir)
    return process_status, pdf_id


if __name__ == '__main__':
    pdf2markdown_pipeline('/mnt/pdf2markdown/龙源电力：2023年年度审计报告.PDF')