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| import cv2 | |
| import csv | |
| import json | |
| from deta import Deta | |
| import os | |
| import requests | |
| def preprocess_img(inp_image): | |
| gray = cv2.cvtColor(inp_image, cv2.COLOR_BGR2GRAY) | |
| gray_img = cv2.bitwise_not(gray) | |
| return gray_img | |
| def save_csv(mahalle, il, sokak, apartman): | |
| adres_full = [mahalle, il, sokak, apartman] | |
| with open("adress_book.csv", "a", encoding="utf-8") as f: | |
| write = csv.writer(f) | |
| write.writerow(adres_full) | |
| return adres_full | |
| def get_json(mahalle, il, sokak, apartman): | |
| adres = {"mahalle": mahalle, "il": il, "sokak": sokak, "apartman": apartman} | |
| dump = json.dumps(adres, indent=4, ensure_ascii=False) | |
| return dump | |
| def write_db(data_dict): | |
| # 2) initialize with a project key | |
| deta_key = os.getenv("DETA_KEY") | |
| deta = Deta(deta_key) | |
| # 3) create and use as many DBs as you want! | |
| users = deta.Base("deprem-ocr") | |
| users.insert(data_dict) | |
| def ner_response(ocr_input): | |
| API_URL = "https://api-inference.huggingface.co/models/deprem-ml/deprem-ner" | |
| headers = {"Authorization": "Bearer xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"} | |
| def query(payload): | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| return response.json() | |
| output = query( | |
| { | |
| "inputs": ocr_input, | |
| } | |
| ) | |
| return output | |