screen/screen_scan.py

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,save_and_push
import os
from huggingface_hub import Repository



def pull_read(DATASET_REPO_URL,HF_TOKEN,DATA_FILE):
    
    repo = Repository(
        local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
        )
    
    with open(DATA_FILE) as csvfile:
        df = pd.read_csv(csvfile) 
        df = pd.DataFrame(df)
    
    return repo, df

@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")
    teacher_code = st.text_input("Ogretmen kodu:",key=12)
    exam_code = st.text_input("Sınav Kodu:",key=13,value=10)

    exam_code = int(exam_code)
    teacher_code = str(teacher_code)
    DATA_FILENAME = f"{teacher_code}.csv"
    DATA_FILENAME = str(DATA_FILENAME)
    
    image_file = st.file_uploader(
        "Upload image for testing", type=['jpeg', 'png', 'jpg', 'webp'])
    
    
    if image_file != None:
        
        if st.button("Process"):
            repo, repo_df = pull_read(DATASET_REPO_URL = "https://huggingface.co/datasets/mertbozkurt/school_data",
                                      DATA_FILE = os.path.join("data", DATA_FILENAME),
                                      HF_TOKEN = "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")
            repo.git_pull()
            image = Image.open(image_file)
            image = np.array(image.convert('RGB'))
            #(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(sinav_kodu=exam_code, ogrenci_no=int(student_idFix),
                                     notu=grading[0],yanlislar=wrong_ans[0])
            
            st.dataframe(new_data)
            updated = update(new_data=new_data,ex_df=repo_df)
            st.dataframe(updated,use_container_width=True)
            save_and_push(dataFrame=updated,repo=repo,fileName=f"data/{DATA_FILENAME}")
            
            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()