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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
@st.cache
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() |