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| import gradio as gr | |
| from easyocr import Reader | |
| from PIL import Image | |
| import io | |
| import json | |
| import csv | |
| import openai | |
| import ast | |
| import os | |
| openai.api_key = os.getenv('API_KEY') | |
| reader = Reader(["tr"]) | |
| def get_parsed_address(input_img): | |
| address_full_text = get_text(input_img) | |
| return openai_response(address_full_text) | |
| def get_text(input_img): | |
| result = reader.readtext(input_img, detail=0) | |
| return " ".join(result) | |
| 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 text_dict_il(input): | |
| eval_result = ast.literal_eval(input)["il"] | |
| return eval_result | |
| def text_dict_mahalle(input): | |
| eval_result = ast.literal_eval(input)["mahalle"] | |
| return eval_result | |
| def text_dict_ilce(input): | |
| eval_result = ast.literal_eval(input)["ilçe"] | |
| return eval_result | |
| def text_dict_sokak(input): | |
| eval_result = ast.literal_eval(input)["sokak"] | |
| return eval_result | |
| def text_dict_no(input): | |
| eval_result = ast.literal_eval(input)["no"] | |
| return eval_result | |
| def text_dict_tel(input): | |
| eval_result = ast.literal_eval(input)["tel"] | |
| return eval_result | |
| def text_dict_isim(input): | |
| eval_result = ast.literal_eval(input)["isim_soyisim"] | |
| return eval_result | |
| def text_dict_adres(input): | |
| eval_result = ast.literal_eval(input)["adres"] | |
| return eval_result | |
| def openai_response(ocr_input): | |
| prompt = f"""Tabular Data Extraction | |
| You are a highly intelligent and accurate tabular data extractor from plain text input and especially from emergency text that carries address information, your inputs can be text of arbitrary size, but the output should be in [{{'tabular': {{'entity_type': 'entity'}} }}] JSON format | |
| Force it to only extract keys that are shared as an example in the examples section, if a key value is not found in the text input, then it should be ignored and should be returned as an empty string | |
| Have only il, ilçe, mahalle, sokak, no, tel, isim_soyisim, adres | |
| Examples: | |
| Input: Deprem sırasında evimizde yer alan adresimiz: İstanbul, Beşiktaş, Yıldız Mahallesi, Cumhuriyet Caddesi No: 35, cep telefonu numaram 5551231256, adim Ahmet Yilmaz | |
| Output: [{{'Tabular': '{{'il': 'İstanbul', 'ilçe': 'Beşiktaş', 'mahalle': 'Yıldız Mahallesi', 'sokak': 'Cumhuriyet Caddesi', 'no': 35, 'tel': 5551231256, 'isim_soyisim': 'Ahmet Yılmaz', 'adres': 'İstanbul, Beşiktaş, Yıldız Mahallesi, Cumhuriyet Caddesi No: 35'}}' }}] | |
| Input: {ocr_input} | |
| Output: | |
| """ | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=prompt, | |
| temperature=0, | |
| max_tokens=300, | |
| top_p=1, | |
| frequency_penalty=0.0, | |
| presence_penalty=0.0, | |
| stop=["\n"], | |
| ) | |
| resp = response["choices"][0]["text"] | |
| resp = eval(resp.replace("'{", "{").replace("}'", "}")) | |
| resp = resp[0]["Tabular"] | |
| return resp | |
| with gr.Blocks() as demo: | |
| gr.Markdown("""## Enkaz Bildirme""") | |
| gr.Markdown("Bu uygulamada ekran görüntüsü sürükleyip bırakarak AFAD'a enkaz bildirimi yapabilirsiniz.") | |
| with gr.Row(): | |
| img_area = gr.Image(label="Ekran Görüntüsü") | |
| ocr_result = gr.Textbox(label="Metin") | |
| open_api_text = gr.Textbox(label="Tam Adres") | |
| submit_button = gr.Button(label="Görüntüyü Yükle") | |
| with gr.Column(): | |
| with gr.Row(): | |
| il = gr.Textbox(label="İl") | |
| ilce = gr.Textbox(label="İlçe") | |
| with gr.Row(): | |
| mahalle = gr.Textbox(label="Mahalle") | |
| sokak = gr.Textbox(label="Sokak/Cadde/Bulvar") | |
| with gr.Row(): | |
| no = gr.Textbox(label="No") | |
| tel = gr.Textbox(label="Telefon") | |
| with gr.Row(): | |
| isim_soyisim = gr.Textbox(label="İsim Soyisim") | |
| adres = gr.Textbox(label="Adres") | |
| submit_button.click(get_text, inputs = img_area, outputs = open_api_text, api_name="upload_image") | |
| ocr_result.change(openai_response, ocr_result, open_api_text, api_name="upload-text") | |
| open_api_text.change(text_dict_il, [open_api_text], il) | |
| open_api_text.change(text_dict_ilce, [open_api_text], ilce) | |
| open_api_text.change(text_dict_mahalle, [open_api_text], mahalle) | |
| open_api_text.change(text_dict_sokak, [open_api_text], sokak) | |
| open_api_text.change(text_dict_no, [open_api_text], no) | |
| open_api_text.change(text_dict_adres, [open_api_text], adres) | |
| open_api_text.change(text_dict_tel, [open_api_text], tel) | |
| open_api_text.change(text_dict_isim, [open_api_text], isim_soyisim) | |
| # json_out = gr.Textbox() | |
| # csv_out = gr.Textbox() | |
| # adres_submit = gr.Button() | |
| # adres_submit.click(get_json, [mahalle, il, sokak, apartman], json_out) | |
| # adres_submit.click(save_csv, [mahalle, il, sokak, apartman], csv_out) | |
| if __name__ == "__main__": | |
| demo.launch() | |