multimodalart HF staff commited on
Commit
0b7d3bf
1 Parent(s): e8b8dbb

Update app.py

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Files changed (1) hide show
  1. app.py +13 -6
app.py CHANGED
@@ -64,9 +64,9 @@ def load_model():
64
  model = load_model()
65
 
66
  # Text-to-video generation function
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- @spaces.GPU(duration=120)
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  def generate_video(prompt, image=None, duration=5, guidance_scale=9, video_guidance_scale=5, progress=gr.Progress(track_tqdm=True)):
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- multiplier = 2.4
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  temp = int(duration * multiplier) + 1
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  torch_dtype = torch.bfloat16 if MODEL_DTYPE == "bf16" else torch.float32
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  if(image):
@@ -97,23 +97,26 @@ def generate_video(prompt, image=None, duration=5, guidance_scale=9, video_guida
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  output_type="pil",
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  save_memory=True,
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  )
 
 
 
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  output_path = f"{str(uuid.uuid4())}_output_video.mp4"
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  export_to_video(frames, output_path, fps=24)
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- return output_path
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104
  # Gradio interface
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  with gr.Blocks() as demo:
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  gr.Markdown("# Pyramid Flow")
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  gr.Markdown("Pyramid Flow is a training-efficient Autoregressive Video Generation model based on Flow Matching. It is trained only on open-source datasets within 20.7k A100 GPU hours")
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  gr.Markdown("[[Paper](https://arxiv.org/pdf/2410.05954)], [[Model](https://huggingface.co/rain1011/pyramid-flow-sd3)], [[Code](https://github.com/jy0205/Pyramid-Flow)]")
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-
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  with gr.Row():
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  with gr.Column():
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  with gr.Accordion("Image to Video (optional)", open=False):
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  i2v_image = gr.Image(type="pil", label="Input Image")
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  t2v_prompt = gr.Textbox(label="Prompt")
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  with gr.Accordion("Advanced settings", open=False):
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- t2v_duration = gr.Slider(minimum=1, maximum=10, value=2 if is_canonical else 5, step=1, label="Duration (seconds)", visible=not is_canonical)
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  t2v_guidance_scale = gr.Slider(minimum=1, maximum=15, value=9, step=0.1, label="Guidance Scale")
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  t2v_video_guidance_scale = gr.Slider(minimum=1, maximum=15, value=5, step=0.1, label="Video Guidance Scale")
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  t2v_generate_btn = gr.Button("Generate Video")
@@ -142,7 +145,11 @@ with gr.Blocks() as demo:
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  t2v_generate_btn.click(
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  generate_video,
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  inputs=[t2v_prompt, i2v_image, t2v_duration, t2v_guidance_scale, t2v_video_guidance_scale],
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- outputs=t2v_output
 
 
 
 
146
  )
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148
  demo.launch()
 
64
  model = load_model()
65
 
66
  # Text-to-video generation function
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+ @spaces.GPU(duration=160)
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  def generate_video(prompt, image=None, duration=5, guidance_scale=9, video_guidance_scale=5, progress=gr.Progress(track_tqdm=True)):
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+ multiplier = 3
70
  temp = int(duration * multiplier) + 1
71
  torch_dtype = torch.bfloat16 if MODEL_DTYPE == "bf16" else torch.float32
72
  if(image):
 
97
  output_type="pil",
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  save_memory=True,
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  )
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+ return frames, gr.update()
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+
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+ def compose_video(frames):
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  output_path = f"{str(uuid.uuid4())}_output_video.mp4"
104
  export_to_video(frames, output_path, fps=24)
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+ return output_path
106
 
107
  # Gradio interface
108
  with gr.Blocks() as demo:
109
  gr.Markdown("# Pyramid Flow")
110
  gr.Markdown("Pyramid Flow is a training-efficient Autoregressive Video Generation model based on Flow Matching. It is trained only on open-source datasets within 20.7k A100 GPU hours")
111
  gr.Markdown("[[Paper](https://arxiv.org/pdf/2410.05954)], [[Model](https://huggingface.co/rain1011/pyramid-flow-sd3)], [[Code](https://github.com/jy0205/Pyramid-Flow)]")
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+ frames = gr.State()
113
  with gr.Row():
114
  with gr.Column():
115
  with gr.Accordion("Image to Video (optional)", open=False):
116
  i2v_image = gr.Image(type="pil", label="Input Image")
117
  t2v_prompt = gr.Textbox(label="Prompt")
118
  with gr.Accordion("Advanced settings", open=False):
119
+ t2v_duration = gr.Slider(minimum=1, maximum=2 if is_canonical else 10, value=2 if is_canonical else 5, step=1, label="Duration (seconds)")
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  t2v_guidance_scale = gr.Slider(minimum=1, maximum=15, value=9, step=0.1, label="Guidance Scale")
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  t2v_video_guidance_scale = gr.Slider(minimum=1, maximum=15, value=5, step=0.1, label="Video Guidance Scale")
122
  t2v_generate_btn = gr.Button("Generate Video")
 
145
  t2v_generate_btn.click(
146
  generate_video,
147
  inputs=[t2v_prompt, i2v_image, t2v_duration, t2v_guidance_scale, t2v_video_guidance_scale],
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+ outputs=[frames, t2v_output]
149
+ ).then(
150
+ compose_video,
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+ input=[frames],
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+ outouts=t2v_output
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  )
154
 
155
  demo.launch()