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 import reader st.markdown(""" """, unsafe_allow_html=True) 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(): teacher_code = st.text_input("Ogretmen kodu:",key=12) password = st.text_input("Sıfre:",key=17,type="password") teacher_code = str(teacher_code) password = str(password) 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: 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() if str(repo_df["ogrenci_no"][0]) == password: st.write("Giriş başarılı") exam_code = st.text_input("Sınav Kodu:",key=13,value=10) exam_code = int(exam_code) global myIndexs try: if myIndexs == None: st.write("Cevap Anahtari Yok") else: st.write("Cevap Anahtari Secili") except NameError: st.write("Cevap Anahtari Yok") if st.button("Cevap Anahtari Sec",key=51): image = Image.open(image_file) image = np.array(image.convert('RGB')) #(ans_txt,pathImage, save_images= True) resim_list,myIndexs =reader.reader(pathImage=image,save_images=False) col3,col4 = st.columns(2) with col3: if st.button("Tara ve Sonucu Goruntule",key=52): image = Image.open(image_file) image = np.array(image.convert('RGB')) #(ans_txt,pathImage, save_images= True) grading, wrong_ans, student_idFix, resim_list,empty_ans =optic1.optic1(ans_txt1=myIndexs[0], ans_txt2=myIndexs[1], ans_txt3=myIndexs[2], pathImage=image,save_images=False) #image_show(resim_list) if len(wrong_ans[0]) == 0: wrong_ans[0] = "0" wrong_ans_str = (str(wrong_ans[0])) st.write("Ogrenci Numarasi:",student_idFix) st.write("Ders1 Yanlis Yaptigi sorular:",(str(wrong_ans[0]))) st.write("Ders1 Bos Yaptigi sorular:",(str(empty_ans[0]))) st.write("Ders1 Notu:",int(grading[0])) st.write("Ders2 Yanlis Yaptigi sorular:",(str(wrong_ans[1]))) st.write("Ders2 Bos Yaptigi sorular:",(str(empty_ans[1]))) st.write("Ders2 Notu:",int(grading[1])) st.write("Ders3 Yanlis Yaptigi sorular:",(str(wrong_ans[2]))) st.write("Ders3 Bos Yaptigi sorular:",(str(empty_ans[2]))) st.write("Ders3 Notu:",int(grading[2])) 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 = (str(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',) else: st.write("Giris basarisiz kontrol ediniz.") #python -m streamlit run app.py if __name__ == '__main__': screen_scan_main()