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import streamlit as st
import os
import sys
import torch
import pickle
import numpy
print(numpy.__version__)
import librosa
print(librosa.__version__)
import numpy
print(numpy.__version__)
path_to_add = os.path.join(os.path.dirname(__file__), "Wav2Lip")
if path_to_add not in sys.path:
sys.path.insert(0, path_to_add)
from avatar import Avatar
options = ['Aude', 'Kyla', 'Liv']
images = ['ref_videos/Aude.png', 'ref_videos/Kyla.png', 'ref_videos/Liv.png']
if 'is_initialized' not in st.session_state:
st.session_state.avatar = Avatar()
st.session_state.avatar.export_video = False
st.session_state.avatar.load_model("checkpoint/wav2lip_gan.pth")
print("load model finished")
st.session_state.avatar.device = 'cuda' if torch.cuda.is_available() else 'cpu'
print(st.session_state.avatar.device)
st.session_state.avatar.output_audio_path = "audio/"
st.session_state.avatar.output_audio_filename = "result.wav"
st.session_state.avatar.temp_lip_video_no_voice_path = "temp/"
st.session_state.avatar.temp_lip_video_no_voice_filename = "result.avi"
st.session_state.avatar.output_video_path = "results/"
st.session_state.avatar.output_video_name = "result_voice.mp4"
st.session_state.selected_option = "Liv"
st.session_state.avatar.ref_video_path_and_filename = f"ref_videos/{st.session_state.selected_option}.mp4"
st.session_state.avatar.get_video_full_frames(st.session_state.avatar.ref_video_path_and_filename)
st.session_state.avatar.face_detect_batch_size = 16
# avatar.create_face_detection_results(avatar.video_full_frames,True)
print("load face detection result")
st.session_state.face_det_results_dict={}
for option in options:
with open(f'ref_videos/{option}_face_det_result.pkl', 'rb') as file:
st.session_state.face_det_results_dict[option] = pickle.load(file)
st.session_state.avatar.face_detect_img_results =st.session_state.face_det_results_dict[st.session_state.selected_option]
#st.session_state.avatar.face_det_results_path_and_name = 'ref_videos/Liv_face_det_result.pkl'
#st.session_state.avatar.load_face_detection_results()
# def load_face_detection_results(self):
# with open(self.face_det_results_path_and_name, 'rb') as file:
# self.face_detect_img_results = pickle.load(file)
input_text = "Hi How are you?"
st.session_state.avatar.text_to_lip_video(input_text)
print("load face detection result done")
st.session_state['is_initialized'] = True
# Create the radio button group
selected_option = st.radio("Choose an option:", options, index=options.index(st.session_state.selected_option))
st.image(images[options.index(selected_option)])
if st.session_state.selected_option != selected_option:
print("The selected option has changed!")
st.session_state.selected_option = selected_option
st.session_state.avatar.ref_video_path_and_filename = f"ref_videos/{st.session_state.selected_option}.mp4"
st.session_state.avatar.get_video_full_frames(st.session_state.avatar.ref_video_path_and_filename)
st.session_state.avatar.face_detect_img_results =st.session_state.face_det_results_dict[st.session_state.selected_option]
from avatar import Avatar
# Create a text input box and store the input in a variable
user_input = st.text_input("Enter your text:")
if user_input:
st.session_state.avatar.dir_clean_up()
# Display the entered text
st.write("You entered:", user_input)
st.session_state.avatar.export_video=True
st.session_state.avatar.text_to_lip_video(user_input)
st.video(st.session_state.avatar.output_video_path +st.session_state.avatar.output_video_name) |