Update app.py

app.py

@@ -1,64 +1,54 @@
 import streamlit as st
-import pandas as pd
+import cv2
 import numpy as np
 
-# Set up the user interface
-st.title("Personal Finance Manager")
-st.write("Welcome to your personal finance manager!")
-
-# Input fields for user information
-st.text_input("Enter your name:", "")
-st.text_input("Enter your email address:", "")
-
-# Selectors for financial data sources
-st.selectbox("Choose a financial institution:", ["Bank A", "Bank B", "Credit Card"])
-st.selectbox("Choose an investment account:", ["Brokerage A", "Brokerage B"])
-
-# Date range picker
-st.date_picker("Select a date range:", datetime.date.today() - timedelta(days=30), datetime.date.today())
-
-# Button to retrieve financial data
-st.button("Retrieve Financial Data")
-
-# Output section
-st.write("")
-
-# Define functions to retrieve financial data and calculate statistics
-def retrieve_financial_data():
-    # Retrieve financial data from APIs or databases
-    bank_accounts = get_bank_accounts()
-    credit_card_accounts = get_credit_card_accounts()
-    investment_accounts = get_investment_accounts()
-    
-    # Combine data into a single dataframe
-    financial_data = pd.concat([bank_accounts, credit_card_accounts, investment_accounts], axis=1)
-    
-    # Calculate statistics
-    total_net_worth = financial_data["Net Worth"].sum()
-    total_income = financial_data["Income"].sum()
-    total_expenses = financial_data["Expenses"].sum()
-    net_worth_change = financial_data["Net Worth Change"].sum()
-    
-    # Return the calculated statistics
-    return total_net_worth, total_income, total_expenses, net_worth_change
-
-def get_bank_accounts():
-    # Retrieve bank account data from API or database
-    return pd.DataFrame({"Account Name": ["Checking", "Savings"], "Balance": [1000, 500]})
-
-def get_credit_card_accounts():
-    # Retrieve credit card account data from API or database
-    return pd.DataFrame({"Account Name": ["Card A", "Card B"], "Balance": [500, 2000]})
-
-def get_investment_accounts():
-    # Retrieve investment account data from API or database
-    return pd.DataFrame({"Account Name": ["Stock Portfolio", "Mutual Fund"], "Balance": [10000, 5000]})
-
-# Call functions to retrieve financial data and calculate statistics
-total_net_worth, total_income, total_expenses, net_worth_change = retrieve_financial_data()
-
-# Print statistics to output section
-st.write("Total Net Worth: $", format(total_net_worth, ".2f"))
-st.write("Total Income: $", format(total_income, ".2f"))
-st.write("Total Expenses: $", format(total_expenses, ".2f"))
-st.write("Net Worth Change: $", format(net_worth_change, ".2f"))
+def cartoonize_image(image):
+    # Convert the image to grayscale
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Apply a bilateral filter to reduce noise while preserving edges
+    smooth = cv2.bilateralFilter(gray, 9, 300, 300)
+
+    # Apply an edge-preserving filter to get the edges
+    edges = cv2.adaptiveThreshold(smooth, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 9, 3)
+
+    # Combine the edges with the original image to create a cartoon effect
+    cartoon = cv2.bitwise_and(image, image, mask=edges)
+
+    return cartoon
+
+def main():
+    st.title("Video to Cartoon Converter")
+
+    # Upload a video file
+    video_file = st.file_uploader("Choose a video file", type=["mp4"])
+
+    if video_file is not None:
+        # Read the video file
+        video = cv2.VideoCapture(video_file)
+
+        # Get video details
+        fps = video.get(cv2.CAP_PROP_FPS)
+        width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
+        height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
+
+        # Create a placeholder to display the processed video
+        cartoon_output = st.empty()
+
+        # Process each frame of the video
+        while True:
+            ret, frame = video.read()
+
+            if not ret:
+                break
+
+            # Cartoonize the frame
+            cartoon_frame = cartoonize_image(frame)
+
+            # Display the cartoonized frame
+            cartoon_output.image(cartoon_frame, channels="BGR", use_column_width=True)
+
+        st.video(video_file, format="video/mp4", start_time=0)
+
+if __name__ == "__main__":
+    main()