Create app.py

app.py

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+import streamlit as st
+from PIL import Image
+import torch
+import skvideo.io
+from diffusers import I2VGenXLPipeline
+from diffusers.utils import export_to_video, load_image
+import numpy as np
+import imageio
+from moviepy.editor import ImageSequenceClip
+from transformers import MusicgenForConditionalGeneration, AutoProcessor
+from scipy.io import wavfile
+import ffmpeg
+
+def generate_video(image, prompt, negative_prompt, video_length):
+    generator = torch.manual_seed(8888)
+    device = torch.device("mps" if torch.backends.mps.is_available() else "cpu")
+    print(f"Using device: {device}")
+    pipeline = I2VGenXLPipeline.from_pretrained("ali-vilab/i2vgen-xl", torch_dtype=torch.float32)
+    pipeline.to(device)
+    frames = pipeline(
+        prompt=prompt,
+        image=image,
+        num_inference_steps=2,
+        negative_prompt=negative_prompt,
+        guidance_scale=9.0,
+        generator=generator,
+        num_frames=video_length*20
+    ).frames[0]
+    return frames
+
+def export_frames_to_video(frames, output_file):
+    frames_np = [np.array(frame) for frame in frames]
+    clip = ImageSequenceClip(frames_np, fps=30)
+    clip.write_videofile(output_file, codec='libx264', audio=False)
+
+def generate_music(prompt, unconditional=False):
+    model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-small")
+    device = "cuda:0" if torch.cuda.is_available() else "cpu"
+    model.to(device)
+    if unconditional:
+        unconditional_inputs = model.get_unconditional_inputs(num_samples=1)
+        audio_values = model.generate(**unconditional_inputs, do_sample=True, max_new_tokens=256)
+    else:
+        processor = AutoProcessor.from_pretrained("facebook/musicgen-small")
+        inputs = processor(
+            text=prompt,
+            padding=True,
+            return_tensors="pt",
+        )
+        audio_values = model.generate(**inputs.to(device), do_sample=True, guidance_scale=3, max_new_tokens=256)
+    sampling_rate = model.config.audio_encoder.sampling_rate
+    return audio_values[0].cpu().numpy(), sampling_rate
+
+def combine_audio_video(audio_file, video_file, output_file):
+    audio = ffmpeg.input(audio_file)
+    video = ffmpeg.input(video_file)
+    output = ffmpeg.output(video, audio, output_file, vcodec='copy', acodec='aac')
+    ffmpeg.run(output)
+
+st.title("AI-Powered Video and Music Generation")
+
+st.sidebar.title("Options")
+
+st.sidebar.subheader("Video Generation")
+image = st.sidebar.file_uploader("Upload an image", type=["jpg", "png"])
+prompt = st.sidebar.text_input("Enter the prompt")
+negative_prompt = st.sidebar.text_input("Enter the negative prompt")
+video_length = st.sidebar.number_input("Enter the video length (seconds)", min_value=1, value=10)
+
+st.sidebar.subheader("Music Generation")
+music_prompt = st.sidebar.text_input("Enter the music prompt")
+unconditional = st.sidebar.checkbox("Generate unconditional music")
+
+if st.sidebar.button("Generate Video and Music"):
+    if image is not None:
+        image = Image.open(image)
+        frames = generate_video(image, prompt, negative_prompt, video_length)
+        export_frames_to_video(frames, "output_video.mp4")
+        st.video("output_video.mp4")
+
+    audio_values, sampling_rate = generate_music(music_prompt, unconditional)
+    wavfile.write("musicgen_out.wav", sampling_rate, audio_values)
+    st.audio("musicgen_out.wav")
+
+    combine_audio_video("musicgen_out.wav", "output_video.mp4", "combined_output.mp4")
+    st.video("combined_output.mp4")