Update app.py

Updated code and corrected video file correct

app.py

@@ -1,17 +1,41 @@
 import streamlit as st
-from PIL import Image
+import cv2
+import tempfile
 import os
+from PIL import Image
 
 st.set_page_config(page_title="AI Thumbnail Generator", layout="centered")
 
 st.title("🎯 AI-Based Thumbnail Generator")
-st.write("Upload a video frame (image) to generate a thumbnail.")
+st.write("Upload a video to extract thumbnail-worthy frames using AI.")
+
+uploaded_video = st.file_uploader("Upload Video File", type=["mp4", "mov", "avi", "mkv", "wmv"])
+
+if uploaded_video is not None:
+    st.video(uploaded_video)
+    st.success("✅ Video uploaded successfully!")
+
+    # Save the uploaded video to a temp file
+    tfile = tempfile.NamedTemporaryFile(delete=False)
+    tfile.write(uploaded_video.read())
 
-uploaded_file = st.file_uploader("Upload Image Frame", type=["jpg", "png", "jpeg"])
+    # Extract frames using OpenCV
+    vidcap = cv2.VideoCapture(tfile.name)
+    success, image = vidcap.read()
+    count = 0
+    thumbnail_frame = None
+    while success:
+        if count % 60 == 0:  # extract every 2 seconds assuming 30 FPS
+            frame_path = f"frame_{count}.jpg"
+            cv2.imwrite(frame_path, image)
+            thumbnail_frame = frame_path  # keep last extracted frame as mock thumbnail
+        success, image = vidcap.read()
+        count += 1
 
-if uploaded_file:
-    st.image(uploaded_file, caption="Uploaded Frame", use_column_width=True)
+    if thumbnail_frame:
+        st.subheader("Generated Thumbnail Frame")
+        image = Image.open(thumbnail_frame)
+        st.image(image, caption="Best Frame", use_column_width=True)
 
-    # Mock prediction (replace with your AI model later)
-    st.success("✅ This is a good thumbnail candidate!")
-    st.download_button("Download Thumbnail", uploaded_file, file_name="thumbnail.jpg")
+        with open(thumbnail_frame, "rb") as file:
+            st.download_button("📥 Download Thumbnail", file, file_name="thumbnail.jpg")