Update app.py

app.py

@@ -1,96 +1,125 @@
 import streamlit as st
 import requests
 from transformers import pipeline
-from PIL import Image
-import numpy as np
-import cv2
-import torch
-import torchvision.transforms as transforms
 from deepface import DeepFace
+from PIL import Image
+import io
 
-# Load Fake News Detection Model
-fake_news_pipeline = pipeline("text-classification", model="roberta-base-openai-detector")
+# Load Fake News Detection Model from Hugging Face
+fake_news_pipeline = pipeline("text-classification", model="mrm8488/bert-tiny-finetuned-fake-news-detection")
 
-# Function to classify text news
 def classify_text(news_text):
+    """Classifies text as Fake or Real with accuracy."""
     result = fake_news_pipeline(news_text)[0]
     label = result['label'].lower()
     score = result['score'] * 100  # Convert to percentage
     return ("Fake" if label == "fake" else "Real"), round(score, 2)
 
-# Function to verify news with Google Fact Check API
+def analyze_image(image):
+    """Analyzes image using DeepFace and provides a result."""
+    try:
+        analysis = DeepFace.analyze(image, actions=['emotion'])
+        dominant_emotion = analysis[0]['dominant_emotion']
+        return f"Analysis Complete - Dominant Emotion: {dominant_emotion}", 90.0  # Dummy Accuracy
+    except Exception as e:
+        return f"Error: {str(e)}", 0.0
+
 def verify_news(news_text):
-    search_url = f"https://toolbox.google.com/factcheck/explorer/search/{'+'.join(news_text.split())}"
+    """Generates a Google search link for verification."""
+    search_url = f"https://www.google.com/search?q={'+'.join(news_text.split())}"
     return search_url
 
-# Function to analyze deepfake images
-def analyze_image(image):
-    try:
-        result = DeepFace.analyze(np.array(image), actions=['age', 'gender', 'race', 'emotion'])
-        return f"✅ This image appears **real**! AI Analysis: {result}"
-    except Exception:
-        return "❌ This image might be **deepfake or manipulated**!"
-
-# Function to analyze video metadata
-def analyze_video(video_url):
-    api_url = f"https://noembed.com/embed?url={video_url}"
-    response = requests.get(api_url).json()
-
-    if "title" in response:
-        title = response["title"]
-        source = response["provider_name"]
-        verification_link = verify_news(title)
-        return f"🎥 Video Title: {title}\n🔗 Source: {source}\n[🔎 Verify this Video]({verification_link})"
-    else:
-        return "❌ Unable to fetch video details! Check if the link is correct."
+def check_video_fake_news(video_url):
+    """Uses Google Fact-Check API for video verification."""
+    api_url = f"https://factchecktools.googleapis.com/v1alpha1/claims:search?query={video_url}&key=YOUR_API_KEY"
+    response = requests.get(api_url)
+    
+    if response.status_code == 200:
+        data = response.json()
+        if 'claims' in data:
+            return "Fake", 85.0  # Fake News Detected (Dummy Value)
+        else:
+            return "Real", 92.0  # Seems Real (Dummy Value)
+    return "Unknown", 0.0  # Could Not Verify
 
 # Streamlit UI
 st.set_page_config(page_title="Fake News Detector", layout="wide")
 st.title("📰 Fake News Detector")
 
-# Sidebar Navigation
+# 🔹 Sidebar for Input Selection
 st.sidebar.title("Select Input Type")
 option = st.sidebar.radio("Choose an option", ["Text", "Image", "Video Link"])
 
-# Input Sections
-col1, col2, col3 = st.columns(3)
+# 🔹 Ensure session state variables are initialized
+for key in ["analyze_text", "result_text", "accuracy_text", "analyze_image", "analyze_video", "news_image", "video_url"]:
+    if key not in st.session_state:
+        st.session_state[key] = None
 
-# Text Analysis Section
-with col1:
-    st.subheader("📄 Text News Check")
-    news_text = st.text_area("Enter the news content:", height=200)
+# 🔹 Text Input Section
+if option == "Text":
+    news_text = st.text_area("Enter the news content to check:", height=200)
     if st.button("Analyze News"):
         if not news_text.strip():
             st.warning("Please enter some text.")
         else:
             result, accuracy = classify_text(news_text)
-            verification_link = verify_news(news_text)
+            st.session_state["result_text"] = result
+            st.session_state["accuracy_text"] = accuracy
 
-            if result == "Fake":
-                st.error(f"❌ Likely **Fake News**! (Confidence: {accuracy}%)")
-            else:
-                st.success(f"✅ Likely **Real News**! (Confidence: {accuracy}%)")
-
-            st.markdown(f"[🔎 Verify on Google Fact Check]({verification_link})")
-
-# Image Upload Section
-with col2:
-    st.subheader("🖼️ Image News Check")
+# 🔹 Image Upload Section
+elif option == "Image":
     uploaded_image = st.file_uploader("Upload a news image", type=["jpg", "png", "jpeg"])
     if uploaded_image and st.button("Analyze Image"):
         image = Image.open(uploaded_image)
-        st.image(image, caption="Uploaded Image", use_column_width=True)
-        result = analyze_image(image)
-        st.info(result)
+        st.session_state["news_image"] = image
+        result, accuracy = analyze_image(image)
+        st.session_state["result_text"] = result
+        st.session_state["accuracy_text"] = accuracy
 
-# Video Link Section
-with col3:
-    st.subheader("🎥 Video News Check")
+# 🔹 Video Link Section
+elif option == "Video Link":
     video_url = st.text_input("Enter the video link:")
     if st.button("Analyze Video"):
         if not video_url.strip():
             st.warning("Please enter a valid video link.")
         else:
-            st.video(video_url)
-            result = analyze_video(video_url)
-            st.info(result)
+            st.session_state["video_url"] = video_url
+            result, accuracy = check_video_fake_news(video_url)
+            st.session_state["result_text"] = result
+            st.session_state["accuracy_text"] = accuracy
+
+# 🔹 Results Section
+st.subheader("📊 Analysis Results")
+if st.session_state["result_text"]:
+    result = st.session_state["result_text"]
+    accuracy = st.session_state["accuracy_text"]
+    
+    if result == "Fake":
+        st.error(f"❌ This is likely **Fake News**! (Accuracy: {accuracy}%)", icon="⚠️")
+    else:
+        st.success(f"✅ This is likely **Real News**! (Accuracy: {accuracy}%)", icon="✅")
+
+    # 🔹 Verification Sources
+    st.subheader("🔍 Verification & Trusted Sources")
+    sources = [
+        "https://www.bbc.com/news",
+        "https://www.cnn.com",
+        "https://www.reuters.com",
+        "https://factcheck.org",
+        "https://www.snopes.com",
+        "https://www.politifact.com"
+    ]
+    for link in sources:
+        st.markdown(f"[🔗 {link}]({link})")
+
+    if option == "Text":
+        verification_link = verify_news(st.session_state["result_text"])
+        st.markdown(f"[🔎 Verify on Google]({verification_link})")
+
+# 🔹 Display Image if Uploaded
+if st.session_state["news_image"]:
+    st.image(st.session_state["news_image"], caption="Uploaded Image", use_column_width=True)
+
+# 🔹 Display Video if Entered
+if st.session_state["video_url"]:
+    st.video(st.session_state["video_url"])