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():
    
    col1,col2 = st.columns(2)
    with col1:
        teacher_code = st.text_input("Ogretmen kodu:",key=12)
    with col2:
        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(
        "Tarama Yapmak Icin Optigi Yukleyin", type=['jpeg', 'png', 'jpg', 'webp'])
    
    
    if image_file != None:
        col3,col4 = st.columns(2)
        with col3:
            
            if st.button("Tara ve Sonucu Goruntule"):
                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)
                if len(wrong_ans[0]) == 0:
                    wrong_ans[0] = "0"
                wrong_ans_str = ','.join(wrong_ans[0])
                st.write("Notu:",int(grading[0]))
                st.write("Yanlis Yaptigi sorular:",wrong_ans_str)
                st.write("Ogrenci Numarasi:",student_idFix)
        
        with col4:
            if st.button("Tara ve Sonucu Kaydet"):
                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)
                if len(wrong_ans[0]) == 0:
                    wrong_ans[0] = "0"
                wrong_ans_str = ','.join(wrong_ans[0])
                new_data = make_new_data(sinav_kodu=exam_code, ogrenci_no=int(student_idFix),
                                     notu=int(grading[0]),yanlislar=str(wrong_ans_str))
            
                #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="Tum verileri indirmek icin tiklayin",data=convert_df_to_csv(updated),
                               file_name=f'{teacher_code}.csv',mime='text/csv',)        
            
#python -m streamlit run app.py
if __name__ == '__main__':
    screen_scan_main()