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.ipynb_checkpoints/app-checkpoint.py

@@ -2,9 +2,37 @@ import gradio as gr
 import torch
 from torch import autocast
 from diffusers import StableDiffusionPipeline
+import argparse
+from moviepy.editor import AudioFileClip, ImageClip
 
+parser = argparse.ArgumentParser()
+setshare = parser.add_argument('--setshare', default=True, action=argparse.BooleanOptionalAction)
 
-def get_stable_diffusion_random_image(prompt):
+def process_inputs(prompt, audio):
+    image = get_stable_diffusion_image(prompt)
+    video = add_static_image_to_audio(image, audio)
+    return video
+
+
+
+def add_static_image_to_audio(image, audio):
+    """Create and save a video file to `output_path` after 
+    combining a static image that is located in `image_path` 
+    with an audio file in `audio_path`"""
+    # create the audio clip object
+    audio_clip = AudioFileClip(audio)
+    # create the image clip object
+    image_clip = ImageClip(image)
+    # use set_audio method from image clip to combine the audio with the image
+    video_clip = image_clip.set_audio(audio)
+    # specify the duration of the new clip to be the duration of the audio clip
+    video_clip.duration = audio.duration
+    # set the FPS to 1
+    video_clip.fps = 1
+    # write the resuling video clip
+    return video_clip
+
+def get_stable_diffusion_image(prompt):
     model_id = "CompVis/stable-diffusion-v1-4"
     device = "cuda"
     pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True)
@@ -13,7 +41,7 @@ def get_stable_diffusion_random_image(prompt):
         image = pipe(prompt, guidance_scale=7.5)["sample"][0]
         print(image)
         return image
+    
 
-
-iface = gr.Interface(fn=get_stable_diffusion_random_image, inputs=["text", "audio"], outputs="video")
-iface.launch(share=True)
+iface = gr.Interface(fn=process_inputs, inputs=["text", "audio"], outputs="video")
+iface.launch(share=setshare)

app.py

@@ -2,9 +2,37 @@ import gradio as gr
 import torch
 from torch import autocast
 from diffusers import StableDiffusionPipeline
+import argparse
+from moviepy.editor import AudioFileClip, ImageClip
 
+parser = argparse.ArgumentParser()
+setshare = parser.add_argument('--setshare', default=True, action=argparse.BooleanOptionalAction)
 
-def get_stable_diffusion_random_image(prompt):
+def process_inputs(prompt, audio):
+    image = get_stable_diffusion_image(prompt)
+    video = add_static_image_to_audio(image, audio)
+    return video
+
+
+
+def add_static_image_to_audio(image, audio):
+    """Create and save a video file to `output_path` after 
+    combining a static image that is located in `image_path` 
+    with an audio file in `audio_path`"""
+    # create the audio clip object
+    audio_clip = AudioFileClip(audio)
+    # create the image clip object
+    image_clip = ImageClip(image)
+    # use set_audio method from image clip to combine the audio with the image
+    video_clip = image_clip.set_audio(audio)
+    # specify the duration of the new clip to be the duration of the audio clip
+    video_clip.duration = audio.duration
+    # set the FPS to 1
+    video_clip.fps = 1
+    # write the resuling video clip
+    return video_clip
+
+def get_stable_diffusion_image(prompt):
     model_id = "CompVis/stable-diffusion-v1-4"
     device = "cuda"
     pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True)
@@ -13,7 +41,7 @@ def get_stable_diffusion_random_image(prompt):
         image = pipe(prompt, guidance_scale=7.5)["sample"][0]
         print(image)
         return image
+    
 
-
-iface = gr.Interface(fn=get_stable_diffusion_random_image, inputs=["text", "audio"], outputs="video")
-iface.launch(share=True)
+iface = gr.Interface(fn=process_inputs, inputs=["text", "audio"], outputs="video")
+iface.launch(share=setshare)

packages.txt

@@ -0,0 +1 @@
+ffmpeg

requirements.txt

@@ -3,3 +3,5 @@ transformers
 nvidia-ml-py3
 ftfy
 --extra-index-url https://download.pytorch.org/whl/cu113 torch
+argparse
+moviepy