hr-ocr-cet/markdown/use_new.py

from markdown.new import DataSet,MarkdownTable
from pathlib import Path

import numpy as np
from mdutils.mdutils import MdUtils
import cv2
import requests
import json
import time
import base64
from itertools import chain


def send_request(str64, send_address='local', image_type=None):
    # sourcery skip: move-assign
    url_local = 'http://192.168.199.249:18050/ocr_system/cet'

    token_ts = '9679c2b3-b90b-4029-a3c7-f347b4d242f7'
    url_ts = 'http://aihub-test.digitalyili.com/aiSquare/openApi/reasoning-services/rlocrxm/cettest/cet'

    token_sb = 'dcae8cc6-0e49-4db8-a2d2-94ef84da3636'
    url_sb = 'http://aihub.digitalyili.com/aiSquare/openApi/reasoning-services/rlocrxm/cettest/cet'
    if image_type:
        json = {'image': str64, 'image_type': image_type}
    else:
        json = {'image': str64}
    if send_address == 'local':
        url = url_local
        headers = {"content-type": "application/json"}
    elif send_address == 'test':
        url = url_ts
        headers = {'Authorization': f"Bearer {token_ts}", 'content-type': "application/json"}
    elif send_address == 'sb':
        url = url_sb
        headers = {'Authorization': f"Bearer {token_sb}", 'content-type': "application/json"}

    return requests.post(url, json=json, headers=headers).json()


dataset = DataSet('/Users/zeke/work/sx/OCR/HROCR/hr-ocr-cet/images/cet6')
mt = MarkdownTable('英语等级证书_CET4')

images = dataset.images
for image, paths in images.items():
    print(image)
    for b64 in dataset.image_2_base64(image):
        res_dict = dataset.res_2_dict(send_request(b64))
        json_dict = dataset.json_2_dict(image)
        dataset.compare_dict(mt, res_dict, json_dict, paths[0])

mt.add_field_table(dataset.field_rate_2_list)
mt.mdFile.new_header(level=1, title=mt.name)
mt.mdFile.new_paragraph("{:.2f}%".format(np.mean([float(mt.field_table[i][:-1]) for i in range(3, len(mt.field_table), 2)])))

mt.mdFile.new_header(level=1, title='True')
mt.mdFile.new_table(columns=2, rows=len(mt.true_table) // 2, text=mt.true_table, text_align='center')

mt.mdFile.new_header(level=1, title='False')
mt.mdFile.new_table(columns=2, rows=len(mt.field_table) // 2, text=mt.field_table, text_align='center')

mt.mdFile.create_md_file()