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import streamlit as st
from pathlib import Path
import torch
from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
from diffusers import StableDiffusionPipeline
from TTS.api import TTS
import cv2
import numpy as np
from PIL import Image
import tempfile
import os
from moviepy.editor import *
import base64
class VideoGenerator:
def __init__(self):
# Initialize text generation model
self.text_model = AutoModelForCausalLM.from_pretrained(
"facebook/opt-1.3b",
torch_dtype=torch.float16,
device_map="auto"
)
self.text_tokenizer = AutoTokenizer.from_pretrained("facebook/opt-1.3b")
# Initialize image generation model
self.image_generator = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
torch_dtype=torch.float16
).to("cuda")
# Initialize TTS model
self.tts = TTS(model_name="tts_models/en/ljspeech/tacotron2-DDC", progress_bar=False)
# Create temp directory
self.temp_dir = Path(tempfile.mkdtemp())
def generate_script(self, prompt):
"""Generate detailed script with facts and scenes"""
input_ids = self.text_tokenizer(
f"Generate a detailed video script with facts about: {prompt}. Include scene descriptions.",
return_tensors="pt"
).input_ids.to("cuda")
outputs = self.text_model.generate(
input_ids,
max_length=500,
temperature=0.7,
num_return_sequences=1
)
script = self.text_tokenizer.decode(outputs[0], skip_special_tokens=True)
return script
def generate_scene_images(self, scene_descriptions):
"""Generate images for each scene using Stable Diffusion"""
image_paths = []
for i, desc in enumerate(scene_descriptions):
image = self.image_generator(desc).images[0]
path = self.temp_dir / f"scene_{i}.png"
image.save(path)
image_paths.append(path)
return image_paths
def generate_voiceover(self, script):
"""Generate voice narration using TTS"""
audio_path = self.temp_dir / "voiceover.wav"
self.tts.tts_to_file(script, file_path=str(audio_path))
return audio_path
def create_video(self, image_paths, audio_path, duration_per_image=5):
"""Combine images and audio into video"""
clips = []
for img_path in image_paths:
clip = ImageClip(str(img_path)).set_duration(duration_per_image)
clips.append(clip)
video = concatenate_videoclips(clips)
audio = AudioFileClip(str(audio_path))
# Adjust video duration to match audio
video = video.set_duration(audio.duration)
final_video = video.set_audio(audio)
output_path = self.temp_dir / "output_video.mp4"
final_video.write_videofile(str(output_path), fps=24)
return output_path
def main():
st.set_page_config(page_title="AI Video Generator", layout="wide")
st.title("🎬 AI Text-to-Video Generator")
# Initialize session state
if 'video_generator' not in st.session_state:
st.session_state.video_generator = VideoGenerator()
# Input section
st.header("Enter Your Topic")
text_input = st.text_area(
"What would you like to create a video about?",
height=100,
placeholder="Example: Explain the process of photosynthesis in plants..."
)
# Generation settings
st.header("Video Settings")
col1, col2 = st.columns(2)
with col1:
video_length = st.slider("Approximate video length (seconds)", 30, 300, 60)
with col2:
style = st.selectbox(
"Video style",
["Educational", "Documentary", "Engaging", "Professional"]
)
# Generate button
if st.button("🎥 Generate Video"):
if text_input:
with st.spinner("🤖 Generating your video..."):
try:
# Progress bar
progress_bar = st.progress(0)
progress_text = st.empty()
# Generate script
progress_text.text("Generating script...")
script = st.session_state.video_generator.generate_script(text_input)
progress_bar.progress(25)
# Extract scene descriptions
progress_text.text("Processing scenes...")
scenes = [s.strip() for s in script.split("Scene:") if s.strip()]
progress_bar.progress(40)
# Generate images
progress_text.text("Creating visuals...")
image_paths = st.session_state.video_generator.generate_scene_images(scenes)
progress_bar.progress(60)
# Generate voiceover
progress_text.text("Generating voiceover...")
audio_path = st.session_state.video_generator.generate_voiceover(script)
progress_bar.progress(80)
# Create video
progress_text.text("Composing final video...")
video_path = st.session_state.video_generator.create_video(
image_paths,
audio_path,
duration_per_image=video_length/len(scenes)
)
progress_bar.progress(100)
progress_text.text("Video generation complete!")
# Display results
st.header("Generated Content")
# Show script
with st.expander("📝 Generated Script"):
st.write(script)
# Show video
st.header("🎥 Your Video")
video_file = open(str(video_path), 'rb')
video_bytes = video_file.read()
st.video(video_bytes)
# Download button
st.download_button(
label="Download Video",
data=video_bytes,
file_name="generated_video.mp4",
mime="video/mp4"
)
except Exception as e:
st.error(f"An error occurred: {str(e)}")
else:
st.warning("Please enter some text to generate a video!")
if __name__ == "__main__":
main() |