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import streamlit as st
import openai
import torch
from transformers import pipeline
from deepface import DeepFace
import cv2
import numpy as np
import random
import os
from moviepy.editor import *
from faster_whisper import WhisperModel
from insightface.app import FaceAnalysis
import shutil
import tempfile
# Set Streamlit Page
st.set_page_config(page_title="DeepFlick: AI Face Swap & Voice Clone", layout="wide")
st.title("🎭 DeepFlick: AI-Powered Face Swap & Voice Clone")
# Load Face Swap Model
face_app = FaceAnalysis(name="buffalo_l")
face_app.prepare(ctx_id=0, det_size=(640, 640))
# Text-to-Speech Model
tts_pipeline = pipeline("text-to-speech", model="coqui-ai/TTS")
# Whisper Model for Auto-Captions
whisper_model = WhisperModel("base", device="cuda" if torch.cuda.is_available() else "cpu")
# Function to Swap Faces
def swap_faces(source_img_path, target_img_path, output_path):
source_img = cv2.imread(source_img_path)
target_img = cv2.imread(target_img_path)
# Detect faces
source_faces = face_app.get(source_img)
target_faces = face_app.get(target_img)
if len(source_faces) == 0 or len(target_faces) == 0:
return None
# Swap faces
swapped_img = DeepFace.swap(source_img, target_img, model_name="insightface")
# Save output
cv2.imwrite(output_path, swapped_img)
return output_path
# Function to Generate Voiceover
def generate_voice(script_text):
audio_path = f"output_{random.randint(1000,9999)}.wav"
tts_audio = tts_pipeline(script_text)
with open(audio_path, "wb") as f:
f.write(tts_audio["audio"])
return audio_path
# Function to Generate Captions
def generate_captions(audio_path):
segments, _ = whisper_model.transcribe(audio_path)
captions = "\n".join([segment.text for segment in segments])
return captions
# User Inputs
st.sidebar.subheader("🎭 Upload Images")
source_img = st.sidebar.file_uploader("Upload Your Face (Source)", type=["jpg", "png"])
target_img = st.sidebar.file_uploader("Upload Target Face", type=["jpg", "png"])
st.sidebar.subheader("🎙️ AI Voice Options")
script_text = st.sidebar.text_area("Enter Video Script:", "Type something interesting here...")
use_ai_voice = st.sidebar.checkbox("Use AI Voice Clone", value=True)
# Process Button
if st.sidebar.button("🎬 Generate AI Video"):
if source_img and target_img and script_text:
with st.spinner("Processing AI Face Swap & Voice Clone... 🚀"):
# Save temp images
temp_source = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg")
temp_target = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg")
temp_source.write(source_img.read())
temp_target.write(target_img.read())
# Perform Face Swap
output_img_path = "swapped_face.jpg"
swapped_face = swap_faces(temp_source.name, temp_target.name, output_img_path)
if swapped_face:
st.image(swapped_face, caption="AI-Swapped Face", use_column_width=True)
# Generate AI Voice
if use_ai_voice:
audio_path = generate_voice(script_text)
st.audio(audio_path, format="audio/wav")
# Generate Captions
captions = generate_captions(audio_path)
st.write("📝 **Auto-Generated Captions:**", captions)
# Convert Swapped Image to Video
video_clip = ImageSequenceClip([swapped_face] * 30, fps=10)
video_audio = AudioFileClip(audio_path) if use_ai_voice else None
final_video_path = f"deepflick_output_{random.randint(1000,9999)}.mp4"
if video_audio:
video_clip = video_clip.set_audio(video_audio)
video_clip.write_videofile(final_video_path, codec="libx264")
st.video(final_video_path)
else:
st.error("Face swap failed! Try using clearer images.")
# Cleanup temp files
temp_source.close()
temp_target.close()
os.remove(temp_source.name)
os.remove(temp_target.name)
else:
st.warning("⚠️ Please upload both images and enter a script.")
# Search Functionality
st.markdown("---")
st.subheader("🔍 Search AI-Generated Videos")
search_query = st.text_input("Search for a video by script content:")
if st.button("🔍 Search"):
# Simulated Search (Replace with a database search)
dummy_videos = {
"Funny AI Skit": "deepflick_output_1234.mp4",
"AI Meme Video": "deepflick_output_5678.mp4"
}
found_videos = {title: path for title, path in dummy_videos.items() if search_query.lower() in title.lower()}
if found_videos:
for title, path in found_videos.items():
st.markdown(f"### 🎥 {title}")
st.video(path)
else:
st.write("❌ No videos found matching your search.") |