Update app.py

app.py

@@ -1,74 +1,77 @@
-import streamlit as st
-import zipfile
-import os
-import shutil
-from moviepy.editor import VideoFileClip
-from main import *  # Ensure that `analyze_live_video` is properly imported
-import random
-import string
-
-# Generate a random string of length 6
-
-# Define paths
-zip_file_path = 'output.zip'
-output_folder = 'output'
-
-# Function to process video and save output
-def process_video(input_file_path, output_folder):
-    # Ensure the output folder exists
-    os.makedirs(output_folder, exist_ok=True)
-
-    # Load the video file
-    video = VideoFileClip(input_file_path)
-
-    # Example processing: Save each frame as an image (customize as needed)
-    for i, frame in enumerate(video.iter_frames()):
-        frame_path = os.path.join(output_folder, f'frame_{i:04d}.png')
-        # Save the frame as an image (you might need to use a library for this, e.g., PIL)
-        # Example: imageio.imwrite(frame_path, frame)
-    
-    # You can add more processing steps here
-
-# Streamlit app
-st.title("Interview assistant")
-
-# Upload video file
-uploaded_file = st.file_uploader("Upload a video file", type=["mp4", "avi", "mov"])
-
-if uploaded_file is not None:
-    # Save the uploaded file to a temporary location
-    temp_file_path = 'temp_video_file.mp4'
-    with open(temp_file_path, 'wb') as f:
-        f.write(uploaded_file.read())
-    
-    # Create a "Predict" button
-    if st.button("Predict"):
-        # Process the video and save output
-        uid = ''.join(random.choices(string.ascii_letters + string.digits, k=6))
-        analyze_live_video(temp_file_path, uid, 1, 1, True, print)
-        
-        # Compress the output folder into a ZIP file
-        def compress_folder(folder_path, zip_file_path):
-            with zipfile.ZipFile(zip_file_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
-                for root, dirs, files in os.walk(folder_path):
-                    for file in files:
-                        file_path = os.path.join(root, file)
-                        zipf.write(file_path, os.path.relpath(file_path, folder_path))        
-        compress_folder(output_folder, zip_file_path)
-        
-        # Read the ZIP file to be downloaded
-        with open(zip_file_path, 'rb') as file:
-            zip_data = file.read()
-
-        # Create a download button for the ZIP file
-        st.download_button(
-            label="Download Processed output",
-            data=zip_data,
-            file_name="output.zip",
-            mime="application/zip"
-        )
-        
-        # Clean up temporary files
-        os.remove(temp_file_path)
-        # shutil.rmtree(output_folder)
+import streamlit as st
+import zipfile
+import os
+import shutil
+from moviepy.editor import VideoFileClip
+from main import *  # Ensure that `analyze_live_video` is properly imported
+import random
+import string
+import nltk
+nltk.download('punkt')
+nltk.download('averaged_perceptron_tagger')
+
+# Generate a random string of length 6
+
+# Define paths
+zip_file_path = 'output.zip'
+output_folder = 'output'
+
+# Function to process video and save output
+def process_video(input_file_path, output_folder):
+    # Ensure the output folder exists
+    os.makedirs(output_folder, exist_ok=True)
+
+    # Load the video file
+    video = VideoFileClip(input_file_path)
+
+    # Example processing: Save each frame as an image (customize as needed)
+    for i, frame in enumerate(video.iter_frames()):
+        frame_path = os.path.join(output_folder, f'frame_{i:04d}.png')
+        # Save the frame as an image (you might need to use a library for this, e.g., PIL)
+        # Example: imageio.imwrite(frame_path, frame)
+    
+    # You can add more processing steps here
+
+# Streamlit app
+st.title("Interview assistant")
+
+# Upload video file
+uploaded_file = st.file_uploader("Upload a video file", type=["mp4", "avi", "mov"])
+
+if uploaded_file is not None:
+    # Save the uploaded file to a temporary location
+    temp_file_path = 'temp_video_file.mp4'
+    with open(temp_file_path, 'wb') as f:
+        f.write(uploaded_file.read())
+    
+    # Create a "Predict" button
+    if st.button("Predict"):
+        # Process the video and save output
+        uid = ''.join(random.choices(string.ascii_letters + string.digits, k=6))
+        analyze_live_video(temp_file_path, uid, 1, 1, True, print)
+        
+        # Compress the output folder into a ZIP file
+        def compress_folder(folder_path, zip_file_path):
+            with zipfile.ZipFile(zip_file_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
+                for root, dirs, files in os.walk(folder_path):
+                    for file in files:
+                        file_path = os.path.join(root, file)
+                        zipf.write(file_path, os.path.relpath(file_path, folder_path))        
+        compress_folder(output_folder, zip_file_path)
+        
+        # Read the ZIP file to be downloaded
+        with open(zip_file_path, 'rb') as file:
+            zip_data = file.read()
+
+        # Create a download button for the ZIP file
+        st.download_button(
+            label="Download Processed output",
+            data=zip_data,
+            file_name="output.zip",
+            mime="application/zip"
+        )
+        
+        # Clean up temporary files
+        os.remove(temp_file_path)
+        # shutil.rmtree(output_folder)
         os.remove(zip_file_path)