Update app.py

app.py

@@ -1,44 +1,97 @@
-import streamlit as st
-import numpy as np
+# import streamlit as st
+# import numpy as np
+# import cv2
+# import tempfile
+# import os
+
+# # ---- Page Configuration ----
+# st.set_page_config(page_title="Fake & Deepfake Detection", layout="wide")
+
+# st.title("📰 Fake News & Deepfake Detection Tool")
+# st.write("🚀 Detect Fake News, Deepfake Images, and Videos using AI")
+
+# # ---- Fake News Detection Section ----
+# st.subheader("📝 Fake News Detection")
+# news_input = st.text_area("Enter News Text:", "Type here...")
+
+# if st.button("Check News"):
+#     st.write("🔍 Processing...")
+#     # Fake news detection logic (Placeholder)
+#     st.success("✅ Result: This news is FAKE.")  # Replace with ML Model
+
+# # ---- Deepfake Image Detection Section ----
+# st.subheader("📸 Deepfake Image Detection")
+# uploaded_image = st.file_uploader("Upload an Image", type=["jpg", "png", "jpeg"])
+
+# if uploaded_image is not None:
+#     st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
+#     if st.button("Analyze Image"):
+#         st.write("🔍 Processing...")
+#         # Deepfake detection logic (Placeholder)
+#         st.error("⚠️ Result: This image is a Deepfake.")  # Replace with model
+
+# # ---- Deepfake Video Detection Section ----
+# st.subheader("🎥 Deepfake Video Detection")
+# uploaded_video = st.file_uploader("Upload a Video", type=["mp4", "avi", "mov"])
+
+# if uploaded_video is not None:
+#     st.video(uploaded_video)
+#     if st.button("Analyze Video"):
+#         st.write("🔍 Processing...")
+#         # Deepfake video detection logic (Placeholder)
+#         st.warning("⚠️ Result: This video contains Deepfake elements.")  # Replace with model
+
+# st.markdown("🔹 **Developed for Fake News & Deepfake Detection Hackathon**")
+
+
+import gradio as gr
 import cv2
-import tempfile
-import os
-
-# ---- Page Configuration ----
-st.set_page_config(page_title="Fake & Deepfake Detection", layout="wide")
-
-st.title("📰 Fake News & Deepfake Detection Tool")
-st.write("🚀 Detect Fake News, Deepfake Images, and Videos using AI")
-
-# ---- Fake News Detection Section ----
-st.subheader("📝 Fake News Detection")
-news_input = st.text_area("Enter News Text:", "Type here...")
-
-if st.button("Check News"):
-    st.write("🔍 Processing...")
-    # Fake news detection logic (Placeholder)
-    st.success("✅ Result: This news is FAKE.")  # Replace with ML Model
-
-# ---- Deepfake Image Detection Section ----
-st.subheader("📸 Deepfake Image Detection")
-uploaded_image = st.file_uploader("Upload an Image", type=["jpg", "png", "jpeg"])
-
-if uploaded_image is not None:
-    st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
-    if st.button("Analyze Image"):
-        st.write("🔍 Processing...")
-        # Deepfake detection logic (Placeholder)
-        st.error("⚠️ Result: This image is a Deepfake.")  # Replace with model
-
-# ---- Deepfake Video Detection Section ----
-st.subheader("🎥 Deepfake Video Detection")
-uploaded_video = st.file_uploader("Upload a Video", type=["mp4", "avi", "mov"])
-
-if uploaded_video is not None:
-    st.video(uploaded_video)
-    if st.button("Analyze Video"):
-        st.write("🔍 Processing...")
-        # Deepfake video detection logic (Placeholder)
-        st.warning("⚠️ Result: This video contains Deepfake elements.")  # Replace with model
-
-st.markdown("🔹 **Developed for Fake News & Deepfake Detection Hackathon**")
+import numpy as np
+
+# ✅ Image Size Limit (MB) 
+MAX_IMAGE_SIZE_MB = 5  # 5MB se zyada allow nahi karega
+
+# ✅ Video Size Limit (MB) 
+MAX_VIDEO_SIZE_MB = 20  # 20MB se zyada allow nahi karega
+
+# ✅ Image Processing Function
+def process_image(image):
+    if image is None:
+        return "❌ No image uploaded!"
+    
+    # ✅ Image Resize (Optional: 512x512)
+    image = cv2.resize(image, (512, 512))  
+    return image
+
+# ✅ Video Processing Function
+def process_video(video_path):
+    if video_path is None:
+        return "❌ No video uploaded!"
+    
+    # ✅ Video Size Check
+    import os
+    file_size_mb = os.path.getsize(video_path) / (1024 * 1024)
+    if file_size_mb > MAX_VIDEO_SIZE_MB:
+        return f"❌ Video is too large! (Size: {file_size_mb:.2f}MB) - Limit: {MAX_VIDEO_SIZE_MB}MB"
+    
+    return f"✅ Video uploaded successfully! (Size: {file_size_mb:.2f}MB)"
+
+# ✅ Gradio Interface
+with gr.Blocks() as app:
+    gr.Markdown("## 🕵️‍♂️ Fake News & Deepfake Detection Tool")
+
+    with gr.Row():
+        img_input = gr.Image(type="numpy", label="🖼 Upload Image (Max: 5MB)")
+        img_output = gr.Image(label="📌 Processed Image")
+        img_button = gr.Button("🔍 Detect Image")
+
+    img_button.click(process_image, inputs=img_input, outputs=img_output)
+
+    with gr.Row():
+        video_input = gr.File(label="🎥 Upload Video (Max: 20MB)", file_types=[".mp4"])
+        video_output = gr.Textbox(label="📌 Video Status")
+        video_button = gr.Button("🔍 Detect Video")
+
+    video_button.click(process_video, inputs=video_input, outputs=video_output)
+
+app.launch()