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| import csv | |
| import streamlit as st | |
| import numpy as np | |
| import cv2 | |
| from PIL import Image | |
| import optic1 | |
| from functions import image_show | |
| import pandas as pd | |
| from data_func import make_new_data,update | |
| def convert_df_to_csv(df): | |
| # IMPORTANT: Cache the conversion to prevent computation on every rerun | |
| return df.to_csv().encode('utf-8') | |
| def screen_scan_main(): | |
| st.title("Optik Okuma") | |
| dataFrame = pd.read_csv('data/temp.csv') | |
| sinif_kodu = int(st.text_input("Sınıf Kodu",value=10)) | |
| ders_kodu = int(st.text_input("Ders Kodu",value=10)) | |
| image_file = st.file_uploader( | |
| "Upload image for testing", type=['jpeg', 'png', 'jpg', 'webp']) | |
| st.dataframe(dataFrame) | |
| if image_file != None: | |
| image = Image.open(image_file) | |
| image = np.array(image.convert('RGB')) | |
| if st.button("Process"): | |
| #(ans_txt,pathImage, save_images= True) | |
| grading, wrong_ans, student_idFix, resim_list =optic1.optic1(ans_txt1="cevapanahtari/cevapanahtari_ders1.txt", | |
| ans_txt2="cevapanahtari/cevapanahtari_ders2.txt", | |
| ans_txt3="cevapanahtari/cevapanahtari_ders3.txt", | |
| pathImage=image,save_images=False) | |
| image_show(resim_list) | |
| st.write("Notu:",grading[0]) | |
| st.write("Yanlis Yaptigi sorular:",wrong_ans[0]) | |
| st.write("Ogrenci Numarasi:",student_idFix) | |
| new_data = make_new_data(sinif_kodu=sinif_kodu,ders_kodu=ders_kodu, ogrenci_no=int(student_idFix), | |
| notu=grading[0],yanlislar=wrong_ans[0]) | |
| st.dataframe(new_data) | |
| updated = update(new_data=new_data,ex_df=dataFrame) | |
| st.dataframe(updated,use_container_width=True) | |
| updated.to_csv("data/temp.csv",index=False) | |
| st.download_button(label="Download data as CSV",data=convert_df_to_csv(updated), | |
| file_name='large_df.csv',mime='text/csv',) | |
| #python -m streamlit run app.py | |
| if __name__ == '__main__': | |
| screen_scan_main() |