new update

data

@@ -1 +1 @@
-Subproject commit 15af2cacd27fc180a93ccc0904359de7b1f16481
+Subproject commit b733259fe70abefb6c892ca9617793f81ab0b2dd

functions.py

@@ -84,16 +84,7 @@ def grading(answers,num_questions,myAnswers):
         else:
             grading.append(0)
             wrong_ans.append(x+1)
-            if myAnswers[x]== 1:
-                wrong_ans.append("A")
-            if myAnswers[x]== 2:
-                wrong_ans.append("B")
-            if myAnswers[x]== 3:
-                wrong_ans.append("C")
-            if myAnswers[x]== 4:
-                wrong_ans.append("D")
-            if myAnswers[x]== 5:
-                wrong_ans.append("E")
+
         
     score = (sum(grading)/num_questions)*100 
     return score ,wrong_ans

screen/screen_scan.py

@@ -11,7 +11,6 @@ import os
 from huggingface_hub import Repository
 
 
-
 def pull_read(DATASET_REPO_URL,HF_TOKEN,DATA_FILE):
     
     repo = Repository(
@@ -27,12 +26,15 @@ def pull_read(DATASET_REPO_URL,HF_TOKEN,DATA_FILE):
 @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')
+  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)
+    
+    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)
@@ -40,39 +42,62 @@ def screen_scan_main():
     DATA_FILENAME = str(DATA_FILENAME)
     
     image_file = st.file_uploader(
-        "Upload image for testing", type=['jpeg', 'png', 'jpg', 'webp'])
+        "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] = " "
+                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)
         
-        if st.button("Process"):
-            repo, repo_df = pull_read(DATASET_REPO_URL = "https://huggingface.co/datasets/mertbozkurt/school_data",
+        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",
+                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}")
+                #image_show(resim_list)
+                if len(wrong_ans[0]) == 0:
+                    wrong_ans[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=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="Download data as CSV",data=convert_df_to_csv(updated),
-                               file_name='large_df.csv',mime='text/csv',)        
+                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__':