Update app.py

app.py

@@ -6,8 +6,6 @@ import numpy as np
 import os
 import sqlite3
 from datetime import datetime
-from huggingface_hub import Repository
-import pandas as pd
 
 # Establish connection to SQLite database
 conn = sqlite3.connect('attendance.db')
@@ -46,43 +44,6 @@ def add_attendance(name):
     c.execute("INSERT INTO attendance (name, time) VALUES (?, ?)", (username, current_datetime))
     conn.commit()
 
-def addAttendance(name):
-    directory_name = "my_directory"
-
-    # Check if the repository exists, if not, create it
-    if not hf_repo_exists(directory_name):
-        hf_repo_create(directory_name)
-        print(f"Repository '{directory_name}' created successfully!")
-    else:
-        repo = Repository()
-    
-    # Create the directory
-    repo.create_directory(directory_name)
-    
-    # Define recognized results (example)
-    recognized_results = [
-        {"Name": "{name}", "Status": "Present"},
-        {"Name": "Alice", "Status": "Absent"},
-        {"Name": "Bob", "Status": "Present"}
-    ]
-    
-    # Convert recognized results to DataFrame
-    df = pd.DataFrame(recognized_results)
-    
-    # Define the path to save the Excel file
-    excel_file_path = "recognized_results.xlsx"
-    
-    # Save DataFrame to Excel file
-    df.to_excel(excel_file_path, index=False)
-    
-    # Define the destination path within the directory
-    destination_path = os.path.join(directory_name, excel_file_path)
-    
-    # Move the Excel file to the destination path
-    os.system(f"mv {excel_file_path} {destination_path}")
-    
-    print(f"Excel file '{excel_file_path}' added to directory '{directory_name}' successfully!")
-
 if file_name is not None:
     col1, col2 = st.columns(2)
 
@@ -123,7 +84,7 @@ if file_name is not None:
             cv2.putText(image, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
             
             # Store attendance in SQLite database
-            addAttendance(name)
+            add_attendance(name)
             
         # Display the image with recognized faces
         st.image(image, use_column_width=True, output_format="PNG")
@@ -134,4 +95,3 @@ if file_name is not None:
             st.write(f"Face {i+1}: {name}")
     else:
         st.warning("No faces detected in the image. Face recognition failed.")
-