update

app.py

@@ -62,85 +62,8 @@
 
 ###########################
 
-# import streamlit as st
-# import os
-# from utils.demo import load_video, ctc_decode
-# from utils.two_stream_infer import load_model
-# from scripts.extract_lip_coordinates import generate_lip_coordinates
-# import options as opt
-
-# st.set_page_config(layout="wide")
-
-# model = load_model()
-
-# st.title("Lipreading final year project Demo")
-
-# st.info(
-#     "The inference speed is very slow on Huggingface spaces due to it being processed entirely on CPU ",
-#     icon="ℹ️",
-# )
-
-# # Generating a list of options or videos
-# options = sorted(os.listdir(os.path.join("app_input")))  # Ensure the list is sorted
-# selected_video = st.selectbox("Choose video", options)
-
-# # Find the index of the selected video and calculate the index of the next video
-# selected_index = options.index(selected_video)
-# next_video_index = (selected_index + 1) % len(options)  # Ensures looping back to start
-# next_video = options[next_video_index]
-
-# col1, col2 = st.columns(2)
-
-# # Function to display video in a column
-# def display_video(column, video_path, video_name):
-#     os.system(f"ffmpeg -i {video_path} -vcodec libx264 {video_name}.mp4 -y")
-#     video = open(f"{video_name}.mp4", "rb")
-#     video_bytes = video.read()
-#     column.video(video_bytes)
-
-# # Displaying the selected video in the first column
-# with col1:
-#     file_path = os.path.join("app_input", selected_video)
-#     video_name = selected_video.split(".")[0]
-#     display_video(col1, file_path, video_name)
-# # Displaying the next video in the second column
-# with col2:
-#     st.info("Expected Result !")
-#     next_file_path = os.path.join("app_input", next_video)
-#     next_video_name = next_video.split(".")[0]
-#     display_video(col2, next_file_path, next_video_name)
-
-
-# # Assuming further processing (like generating predictions) is only intended for the first (selected) video
-# with col1, st.spinner("Processing video..."):
-#     video, img_p, files = load_video(f"{video_name}.mp4", opt.device)
-#     coordinates = generate_lip_coordinates(f"{video_name}_samples")
-#     # Assuming 'frames_generated' and 'coordinates_generated' are used for control flow or further processing
-#     frames_generated = True
-#     coordinates_generated = True
-#     if frames_generated and coordinates_generated:
-#         st.markdown(f"Frames Generated for {video_name}:\n{files}")
-#         st.markdown(f"Coordinates Generated for {video_name}:\n{coordinates}")
-
-# with col2:
-#     st.info("Ready to make prediction!")
-#     generate = st.button("Generate")
-#     if generate:
-#         with st.spinner("Generating..."):
-#             y = model(
-#                 video[None, ...].to(opt.device),
-#                 coordinates[None, ...].to(opt.device),
-#             )
-#             txt = ctc_decode(y[0])
-#             st.text(txt[-1])
-
-# st.info("Author ©️ : Wissem Karous ")
-# st.info("Made with ❤️")
-##################
-
 import streamlit as st
 import os
-import cv2
 from utils.demo import load_video, ctc_decode
 from utils.two_stream_infer import load_model
 from scripts.extract_lip_coordinates import generate_lip_coordinates
@@ -150,7 +73,7 @@ st.set_page_config(layout="wide")
 
 model = load_model()
 
-st.title("Lipreading Final Year Project Demo")
+st.title("Lipreading final year project Demo")
 
 st.info(
     "The inference speed is very slow on Huggingface spaces due to it being processed entirely on CPU ",
@@ -168,27 +91,18 @@ next_video = options[next_video_index]
 
 col1, col2 = st.columns(2)
 
-# Function to display video in a column with resizing
+# Function to display video in a column
 def display_video(column, video_path, video_name):
-    cap = cv2.VideoCapture(video_path)
-    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-    new_width = 320  # Adjust this value for desired width
-    new_height = int((new_width / width) * height)
-    while cap.isOpened():
-        ret, frame = cap.read()
-        if not ret:
-            break
-        frame = cv2.resize(frame, (new_width, new_height))
-        column.image(frame, channels="BGR")
-    cap.release()
+    os.system(f"ffmpeg -i {video_path} -vcodec libx264 {video_name}.mp4 -y")
+    video = open(f"{video_name}.mp4", "rb")
+    video_bytes = video.read()
+    column.video(video_bytes)
 
 # Displaying the selected video in the first column
 with col1:
     file_path = os.path.join("app_input", selected_video)
     video_name = selected_video.split(".")[0]
     display_video(col1, file_path, video_name)
-
 # Displaying the next video in the second column
 with col2:
     st.info("Expected Result !")
@@ -196,6 +110,7 @@ with col2:
     next_video_name = next_video.split(".")[0]
     display_video(col2, next_file_path, next_video_name)
 
+
 # Assuming further processing (like generating predictions) is only intended for the first (selected) video
 with col1, st.spinner("Processing video..."):
     video, img_p, files = load_video(f"{video_name}.mp4", opt.device)
@@ -221,4 +136,6 @@ with col2:
 
 st.info("Author ©️ : Wissem Karous ")
 st.info("Made with ❤️")
+##################
+