Create app.py

app.py

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+import gradio as gr
+from diffusers import StableDiffusionPipeline
+import openai
+import moviepy.editor as mp
+import torch
+import os
+from datetime import datetime
+import librosa
+
+# Ensure the desktop folder exists
+desktop_path = os.path.join(os.path.expanduser("~"), "Desktop", "DREAMS & VISIONS")
+os.makedirs(desktop_path, exist_ok=True)
+
+# Check for GPU availability
+if torch.cuda.is_available():
+    device = "cuda"
+    dtype = torch.float16
+else:
+    device = "cpu"
+    dtype = torch.float32
+
+# Initialize the Stable Diffusion pipeline
+pipeline = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=dtype).to(device)
+print("Stable Diffusion pipeline initialized.")
+
+# Set OpenAI API key
+openai.api_key = "sk-proj-niE4nhCiKxdCoXu4gBjKT3BlbkFJARCQWnAE8VAUtQ55bVcC"
+print("OpenAI API key set.")
+
+def get_unique_filename(directory, base_name, extension):
+    """
+    Generate a unique filename by appending a number if the file already exists.
+    """
+    counter = 1
+    filename = f"{base_name}.{extension}"
+    while os.path.exists(os.path.join(directory, filename)):
+        filename = f"{base_name}_{counter}.{extension}"
+        counter += 1
+    return filename
+
+def generate_text(prompt):
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            messages=[{"role": "user", "content": prompt}],
+            max_tokens=150
+        )
+        narrative = response['choices'][0]['message']['content'].strip()
+        print(f"Narrative generated: {narrative}")
+        return narrative
+    except Exception as e:
+        print(f"Error generating text: {e}")
+        return "Error generating narrative text."
+
+def generate_images(prompt, num_images):
+    try:
+        images = []
+        for _ in range(num_images):
+            image = pipeline(prompt).images[0]
+            images.append(image)
+        print(f"{len(images)} images generated.")
+        return images
+    except Exception as e:
+        print(f"Error generating images: {e}")
+        return []
+
+def sync_video_with_audio(prompt, duration, frame_rate, audio_path=None):
+    try:
+        # Generate video clips based on the prompt, duration, and frame rate
+        num_frames = int(duration * frame_rate)
+        images = generate_images(prompt, num_frames)
+
+        # Save images as frames
+        frame_paths = []
+        for i, image in enumerate(images):
+            frame_path = os.path.join(desktop_path, f"frame_{i:04d}.png")
+            image.save(frame_path)
+            frame_paths.append(frame_path)
+        
+        # Create video clips from frames
+        clips = [mp.ImageClip(frame).set_duration(1 / frame_rate) for frame in frame_paths]
+        video = mp.concatenate_videoclips(clips, method="compose")
+        
+        # Sync video with audio if provided
+        if audio_path:
+            y, sr = librosa.load(audio_path)
+            tempo, beat_frames = librosa.beat.beat_track(y=y, sr=sr)
+            beat_times = librosa.frames_to_time(beat_frames, sr=sr)
+
+            synced_clips = []
+            for i, beat_time in enumerate(beat_times[:-1]):
+                start_time = beat_time
+                end_time = beat_times[i + 1]
+                clip = video.subclip(start_time, end_time)
+                synced_clips.append(clip)
+
+            final_video = mp.concatenate_videoclips(synced_clips)
+            audio = mp.AudioFileClip(audio_path)
+            final_video = final_video.set_audio(audio)
+        else:
+            final_video = video
+
+        # Save final video
+        final_video_path = os.path.join(desktop_path, get_unique_filename(desktop_path, "final_synced_video", "mp4"))
+        final_video.write_videofile(final_video_path, codec="libx264", audio_codec="aac", fps=frame_rate)
+
+        print(f"Final synced video saved to: {final_video_path}")
+        return final_video_path, final_video_path
+
+    except Exception as e:
+        print(f"Error syncing video with audio: {e}")
+        return None, None
+
+def manual_edit_video(video_path, effects, transitions):
+    try:
+        video = mp.VideoFileClip(video_path)
+        
+        if "fade_in" in effects:
+            video = video.fadein(1)
+        if "fade_out" in effects:
+            video = video.fadeout(1)
+        if "black_and_white" in effects:
+            video = video.fx(mp.vfx.blackwhite)
+        if "mirror" in effects:
+            video = video.fx(mp.vfx.mirror_x)
+        if "rotate" in effects:
+            video = video.fx(mp.vfx.rotate, 180)
+        
+        if "crossfade" in transitions:
+            video = video.crossfadein(1)
+        if "slide" in transitions:
+            video = video.fx(mp.vfx.slide_in, 'left')
+
+        edited_video_path = os.path.join(desktop_path, get_unique_filename(desktop_path, "edited_video", "mp4"))
+        video.write_videofile(edited_video_path, codec="libx264", audio_codec="aac")
+        
+        print(f"Edited video saved to: {edited_video_path}")
+        return edited_video_path, edited_video_path
+
+    except Exception as e:
+        print(f"Error editing video: {e}")
+        return None, None
+
+with gr.Blocks() as demo:
+    gr.Markdown("# AI DREAMS & VISIONS Music Video Creator")
+    gr.Markdown("Bring your dreams and visions to life with our AI-powered music video creator. Upload a song, image, or video and create a stunning, synchronized music video with AI-driven enhancements. Contact us at [aidreams@aidreams.company](mailto:aidreams@aidreams.company) for any inquiries. Follow us on [X @TheKingofJewelz](https://x.com/TheKingofJewelz) and get a chance to have your video featured!")
+
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(label="Text Prompt", placeholder="Enter your video description here...")
+            duration = gr.Slider(label="Duration (seconds)", minimum=1, maximum=30, step=1, value=10)
+            frame_rate = gr.Slider(label="Frame Rate", minimum=1, maximum=60, step=1, value=24)
+            audio_file = gr.Audio(label="Upload Audio (Optional)")
+            image_file = gr.Image(label="Upload Image (Optional)", type="filepath")
+            video_file = gr.Video(label="Upload Video (Optional)")
+            generate_btn = gr.Button("Generate Video")
+
+        with gr.Column():
+            video_output = gr.Video(label="Generated Video")
+            download_link = gr.File(label="Download Video")
+
+    generate_btn.click(
+        sync_video_with_audio,
+        inputs=[prompt, duration, frame_rate, audio_file],
+        outputs=[video_output, download_link],
+    )
+
+    gr.Markdown("### Manual Video Editing")
+    with gr.Row():
+        with gr.Column():
+            video_input = gr.File(label="Upload Video for Editing", type="filepath")
+            effects = gr.CheckboxGroup(label="Select Effects", choices=["fade_in", "fade_out", "black_and_white", "mirror", "rotate"])
+            transitions = gr.CheckboxGroup(label="Select Transitions", choices=["crossfade", "slide"])
+            edit_btn = gr.Button("Edit Video")
+
+        with gr.Column():
+            edited_video_output = gr.Video(label="Edited Video")
+            download_edited_link = gr.File(label="Download Edited Video")
+
+    edit_btn.click(
+        manual_edit_video,
+        inputs=[video_input, effects, transitions],
+        outputs=[edited_video_output, download_edited_link],
+    )
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=8888, share=True)