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| import gradio as gr | |
| import torch | |
| from diffusers import StableDiffusionPipeline | |
| import time | |
| from moviepy.editor import VideoFileClip, concatenate_videoclips, AudioFileClip | |
| from moviepy.video.fx.all import volumex | |
| import os | |
| import datetime | |
| # Load the pipeline | |
| model_id = "CompVis/stable-diffusion-v1-4" | |
| pipe = StableDiffusionPipeline.from_pretrained(model_id) | |
| pipe = pipe.to("cpu") | |
| # Create a sample video | |
| sample_video_path = "sample_video.mp4" | |
| video_clip = VideoFileClip(sample_video_path) | |
| # Define paths | |
| output_directory = os.path.expanduser("~/Desktop/AI DREAMS & VISIONS/") | |
| # Ensure the output directory exists | |
| os.makedirs(output_directory, exist_ok=True) | |
| # Function to generate video with visualizer | |
| def generate_video(prompt, duration=10, frame_rate=24): | |
| start_time = time.time() | |
| # Placeholder: Simulate video generation | |
| output_video_path = os.path.join(output_directory, f"{prompt.replace(' ', '_')}.mp4") | |
| video_clip = VideoFileClip(sample_video_path).subclip(0, duration) | |
| # Add a visualizer (simple volume visualizer as a placeholder) | |
| audio_clip = video_clip.audio | |
| visualizer = volumex(video_clip, 0.5) | |
| final_clip = concatenate_videoclips([visualizer.set_audio(audio_clip)]) | |
| final_clip.write_videofile(output_video_path, fps=frame_rate) | |
| end_time = time.time() | |
| time_taken = end_time - start_time | |
| estimated_time = str(datetime.timedelta(seconds=int(time_taken))) | |
| return output_video_path, estimated_time | |
| # Function to upload music and sync with video | |
| def sync_music_to_video(video_path, music_path): | |
| video_clip = VideoFileClip(video_path) | |
| audio_clip = AudioFileClip(music_path) | |
| # Sync music to video duration | |
| synced_audio_clip = audio_clip.subclip(0, video_clip.duration) | |
| # Apply the music to the video | |
| final_clip = video_clip.set_audio(synced_audio_clip) | |
| synced_video_path = video_path.replace('.mp4', '_synced.mp4') | |
| final_clip.write_videofile(synced_video_path) | |
| return synced_video_path | |
| # Define the Gradio interface | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# AI DREAMS X Video Generator") | |
| with gr.Row(): | |
| with gr.Column(): | |
| text_input = gr.Textbox(label="Text Prompt") | |
| duration_input = gr.Slider(minimum=1, maximum=60, step=1, label="Duration (seconds)", value=10) | |
| frame_rate_input = gr.Slider(minimum=1, maximum=60, step=1, label="Frame Rate (fps)", value=24) | |
| music_upload = gr.File(label="Upload Music File") | |
| generate_button = gr.Button("Generate Video") | |
| with gr.Column(): | |
| output_video = gr.Video(label="Generated Video") | |
| download_link = gr.File(label="Download Video") | |
| estimated_time = gr.Textbox(label="Estimated Time of Completion") | |
| def generate_and_display(prompt, duration, frame_rate, music_file): | |
| video_path, estimated_time = generate_video(prompt, duration, frame_rate) | |
| if music_file: | |
| video_path = sync_music_to_video(video_path, music_file.name) | |
| return video_path, video_path, estimated_time | |
| generate_button.click(generate_and_display, inputs=[text_input, duration_input, frame_rate_input, music_upload], outputs=[output_video, download_link, estimated_time]) | |
| gr.Markdown("[Contact Us](mailto:aidreams@aidreams.company) | [Follow @TheKingofJewelz](https://x.com/TheKingofJewelz)") | |
| demo.launch(share=True, server_name="0.0.0.0", server_port=7863) | |