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| import gradio as gr | |
| import torch | |
| from diffusers import StableDiffusionPipeline | |
| import moviepy.editor as mp | |
| import os | |
| from pathlib import Path | |
| def generate_image(prompt): | |
| try: | |
| print("Generating image...") | |
| model_id = "runwayml/stable-diffusion-v1-5" | |
| pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32) | |
| pipe.to("cpu") | |
| # Generate image | |
| image = pipe(prompt).images[0] | |
| # Create output directory if it doesn't exist | |
| output_dir = Path("outputs") | |
| output_dir.mkdir(exist_ok=True) | |
| # Save image with timestamp to avoid conflicts | |
| image_path = output_dir / "generated_image.png" | |
| image.save(image_path) | |
| print(f"Image saved at {image_path}") | |
| return str(image_path) | |
| except Exception as e: | |
| print(f"Error generating image: {str(e)}") | |
| return None | |
| def create_video(image_path, duration=5): | |
| try: | |
| if not image_path or not os.path.exists(image_path): | |
| return None | |
| print("Creating video...") | |
| # Create video path in outputs directory | |
| output_dir = Path("outputs") | |
| video_path = output_dir / "output_video.mp4" | |
| # Create video clip | |
| clip = mp.ImageClip(image_path, duration=duration) | |
| clip = clip.set_fps(24) | |
| clip.write_videofile(str(video_path), codec='libx264') | |
| clip.close() | |
| print(f"Video saved at {video_path}") | |
| return str(video_path) | |
| except Exception as e: | |
| print(f"Error creating video: {str(e)}") | |
| return None | |
| def text_to_video(prompt): | |
| # Generate image | |
| image_path = generate_image(prompt) | |
| if not image_path: | |
| return "❌ Error generating image. Please try again with a different prompt." | |
| # Create video | |
| video_path = create_video(image_path) | |
| # Clean up image file | |
| try: | |
| if image_path and os.path.exists(image_path): | |
| os.remove(image_path) | |
| except Exception as e: | |
| print(f"Warning: Could not delete image file: {e}") | |
| if not video_path: | |
| return "❌ Error creating video. Please try again." | |
| return video_path | |
| # Create outputs directory if it doesn't exist | |
| Path("outputs").mkdir(exist_ok=True) | |
| # Create the Gradio interface | |
| with gr.Blocks() as demo: | |
| gr.Markdown(""" | |
| # Text to AI Video Generator | |
| Create a video from text using Stable Diffusion and MoviePy | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| prompt_input = gr.Textbox( | |
| label="Enter your prompt", | |
| placeholder="Describe the image you want to generate...", | |
| lines=3 | |
| ) | |
| generate_btn = gr.Button("Generate Video", variant="primary") | |
| with gr.Column(): | |
| output_video = gr.Video( | |
| label="Generated Video", | |
| format="mp4", | |
| interactive=False | |
| ) | |
| status = gr.Textbox(label="Status", interactive=False) | |
| # Examples | |
| gr.Examples( | |
| examples=[ | |
| "A beautiful sunset over mountains", | |
| "An astronaut riding a horse on Mars", | |
| "A futuristic city with flying cars" | |
| ], | |
| inputs=prompt_input | |
| ) | |
| # Button click handler | |
| generate_btn.click( | |
| fn=text_to_video, | |
| inputs=prompt_input, | |
| outputs=[output_video, status], | |
| api_name="generate" | |
| ) | |
| # Launch the app | |
| if __name__ == "__main__": | |
| demo.launch( | |
| server_name="0.0.0.0", | |
| server_port=7860, | |
| share=True, | |
| debug=True | |
| ) |