Create app.py

app.py

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+import streamlit as st
+from zipfile import ZipFile
+import os
+import pandas as pd
+
+# Helper functions for image and video captioning (to be implemented)
+def caption_images(image_folder):
+    # Dummy implementation, replace with actual model inference
+    captions = {"image1.jpg": "A beautiful scenery", "image2.jpg": "A cute puppy"}
+    return captions
+
+def caption_video(video_file):
+    # Dummy implementation, replace with actual model inference
+    return "A summary of the video content."
+
+# Main App
+st.title("Multimedia Captioning and Search App")
+
+# Sidebar options
+st.sidebar.header("Options")
+st.sidebar.subheader("Upload Files")
+uploaded_zip = st.sidebar.file_uploader("Upload a ZIP file of images", type="zip")
+uploaded_video = st.sidebar.file_uploader("Upload a video file", type=["mp4", "avi", "mov"])
+
+st.sidebar.subheader("Search")
+search_input = st.sidebar.text_input("Enter search term")
+
+# Handling image zip file upload
+if uploaded_zip is not None:
+    with ZipFile(uploaded_zip, 'r') as zip_ref:
+        zip_ref.extractall("uploaded_images")
+    st.write("Images extracted successfully!")
+    image_captions = caption_images("uploaded_images")
+    # Save captions to CSV
+    df_images = pd.DataFrame(list(image_captions.items()), columns=["Image", "Caption"])
+    df_images.to_csv("image_captions.csv", index=False)
+
+# Handling video file upload
+if uploaded_video is not None:
+    video_caption = caption_video(uploaded_video)
+    # Save caption to CSV
+    df_video = pd.DataFrame([["video_frame.jpg", video_caption]], columns=["Video Frame", "Caption"])
+    df_video.to_csv("video_captions.csv", index=False)
+    # Extract and display one frame from video (dummy implementation)
+    st.image("video_frame.jpg", caption=video_caption)
+
+# Display gallery of images and videos with captions
+st.subheader("Gallery")
+if os.path.exists("image_captions.csv"):
+    df_images = pd.read_csv("image_captions.csv")
+    for index, row in df_images.iterrows():
+        st.image(f"uploaded_images/{row['Image']}", caption=row["Caption"])
+
+if os.path.exists("video_captions.csv"):
+    df_video = pd.read_csv("video_captions.csv")
+    for index, row in df_video.iterrows():
+        st.image(row["Video Frame"], caption=row["Caption"])
+
+# Search functionality
+if search_input:
+    st.subheader("Search Results")
+    if os.path.exists("image_captions.csv"):
+        df_images = pd.read_csv("image_captions.csv")
+        search_results = df_images[df_images["Caption"].str.contains(search_input, case=False, na=False)]
+        for index, row in search_results.iterrows():
+            st.image(f"uploaded_images/{row['Image']}", caption=row["Caption"])
+    
+    if os.path.exists("video_captions.csv"):
+        df_video = pd.read_csv("video_captions.csv")
+        search_results = df_video[df_video["Caption"].str.contains(search_input, case=False, na=False)]
+        for index, row in search_results.iterrows():
+            st.image(row["Video Frame"], caption=row["Caption"])