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from easyocr import Reader | |
import gradio as gr | |
import openai | |
import ast | |
import os | |
from openai_api import OpenAI_API | |
import utils | |
openai.api_key = os.getenv("API_KEY") | |
reader = Reader(["tr"]) | |
def get_text(input_img): | |
result = reader.readtext(input_img, detail=0) | |
return " ".join(result) | |
# Submit button | |
def get_parsed_address(input_img): | |
address_full_text = utils.get_text(input_img) | |
return openai_response(address_full_text) | |
# Open API on change | |
def text_dict(input): | |
eval_result = ast.literal_eval(input) | |
utils.write_db(eval_result) | |
return ( | |
str(eval_result["city"]), | |
str(eval_result["distinct"]), | |
str(eval_result["neighbourhood"]), | |
str(eval_result["street"]), | |
str(eval_result["address"]), | |
str(eval_result["tel"]), | |
str(eval_result["name_surname"]), | |
str(eval_result["no"]), | |
) | |
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. Have only city, distinct, neighbourhood, | |
street, no, tel, name_surname, address Examples: Input: Deprem sırasında evimizde yer alan adresimiz: İstanbul, | |
Beşiktaş, Yıldız Mahallesi, Cumhuriyet Caddesi No: 35, cep telefonu numaram 5551231256, adim Ahmet Yilmaz | |
Output: {{'city': 'İstanbul', 'distinct': 'Beşiktaş', 'neighbourhood': 'Yıldız Mahallesi', 'street': 'Cumhuriyet Caddesi', 'no': '35', 'tel': '5551231256', 'name_surname': 'Ahmet Yılmaz', 'address': 'İstanbul, Beşiktaş, Yıldız Mahallesi, Cumhuriyet Caddesi No: 35'}} | |
Input: {ocr_input} | |
Output: | |
""" | |
openai_client = OpenAI_API() | |
response = openai_client.single_request(prompt) | |
resp = response["choices"][0]["text"] | |
print(resp) | |
resp = eval(resp.replace("'{", "{").replace("}'", "}")) | |
resp["input"] = ocr_input | |
dict_keys = [ | |
"city", | |
"distinct", | |
"neighbourhood", | |
"street", | |
"no", | |
"tel", | |
"name_surname", | |
"address", | |
"input", | |
] | |
for key in dict_keys: | |
if key not in resp.keys(): | |
resp[key] = "" | |
return resp | |
# User Interface | |
with gr.Blocks() as demo: | |
gr.Markdown( | |
""" | |
# Enkaz Bildirme Uygulaması | |
""" | |
) | |
gr.Markdown( | |
"Bu uygulamada ekran görüntüsü sürükleyip bırakarak AFAD'a enkaz bildirimi yapabilirsiniz. Mesajı metin olarak da girebilirsiniz, tam adresi ayrıştırıp döndürür. API olarak kullanmak isterseniz sayfanın en altında use via api'ya tıklayın." | |
) | |
with gr.Row(): | |
img_area = gr.Image(label="Ekran Görüntüsü yükleyin 👇") | |
ocr_result = gr.Textbox(label="Metin yükleyin 👇 ") | |
open_api_text = gr.Textbox(label="Tam Adres") | |
submit_button = gr.Button(label="Yükle") | |
with gr.Column(): | |
with gr.Row(): | |
city = gr.Textbox(label="İl") | |
distinct = gr.Textbox(label="İlçe") | |
with gr.Row(): | |
neighbourhood = gr.Textbox(label="Mahalle") | |
street = gr.Textbox(label="Sokak/Cadde/Bulvar") | |
with gr.Row(): | |
tel = gr.Textbox(label="Telefon") | |
with gr.Row(): | |
name_surname = gr.Textbox(label="İsim Soyisim") | |
address = gr.Textbox(label="Adres") | |
with gr.Row(): | |
no = gr.Textbox(label="Kapı No") | |
submit_button.click( | |
get_parsed_address, | |
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, | |
open_api_text, | |
[city, distinct, neighbourhood, street, address, tel, name_surname, no], | |
) | |
if __name__ == "__main__": | |
demo.launch() | |