Spaces:
Running
on
Zero
Running
on
Zero
Update
Browse files
app.py
CHANGED
@@ -12,13 +12,6 @@ from PIL import Image
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# Constants
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base = "frankjoshua/toonyou_beta6"
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repo = "ByteDance/AnimateDiff-Lightning"
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checkpoints = {
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"1-Step" : ["animatediff_lightning_1step_diffusers.safetensors", 1],
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"2-Step" : ["animatediff_lightning_2step_diffusers.safetensors", 2],
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"4-Step" : ["animatediff_lightning_4step_diffusers.safetensors", 4],
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"8-Step" : ["animatediff_lightning_8step_diffusers.safetensors", 8],
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}
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loaded = None
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# Ensure model and scheduler are initialized in GPU-enabled function
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@@ -33,24 +26,21 @@ else:
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# Function
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@spaces.GPU(enable_queue=True)
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def generate_image(prompt,
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global loaded
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print(prompt,
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pipe.unet.load_state_dict(load_file(hf_hub_download(repo, checkpoint), device=device), strict=False)
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loaded = num_inference_steps
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output = pipe(prompt=prompt, guidance_scale=1.0, num_inference_steps=num_inference_steps)
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name = str(uuid.uuid4()).replace("-", "")
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path = f"/tmp/{name}.mp4"
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export_to_video(output.frames[0], path, fps=10)
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return path
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@@ -62,10 +52,28 @@ with gr.Blocks(css="style.css") as demo:
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gr.HTML("<p><center>Lightning-fast text-to-video generation</center></p><p><center><a href='https://huggingface.co/ByteDance/AnimateDiff-Lightning'>https://huggingface.co/ByteDance/AnimateDiff-Lightning</a></center></p>")
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with gr.Group():
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with gr.Row():
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prompt = gr.Textbox(
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prompt.submit(
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fn=generate_image,
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# Constants
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base = "frankjoshua/toonyou_beta6"
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loaded = None
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# Ensure model and scheduler are initialized in GPU-enabled function
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# Function
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@spaces.GPU(enable_queue=True)
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def generate_image(prompt, step):
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global loaded
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print(prompt, step)
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if loaded != step:
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repo = "ByteDance/AnimateDiff-Lightning"
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ckpt = f"animatediff_lightning_{step}step_diffusers.safetensors"
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pipe.unet.load_state_dict(load_file(hf_hub_download(repo, ckpt), device=device), strict=False)
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loaded = step
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output = pipe(prompt=prompt, guidance_scale=1.0, num_inference_steps=step)
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name = str(uuid.uuid4()).replace("-", "")
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path = f"/tmp/{name}.mp4"
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export_to_video(output.frames[0], path, fps=10)
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return path
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gr.HTML("<p><center>Lightning-fast text-to-video generation</center></p><p><center><a href='https://huggingface.co/ByteDance/AnimateDiff-Lightning'>https://huggingface.co/ByteDance/AnimateDiff-Lightning</a></center></p>")
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with gr.Group():
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with gr.Row():
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prompt = gr.Textbox(
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label='Enter your prompt (English)',
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scale=8
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)
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ckpt = gr.Dropdown(
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label='Select inference steps',
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choices=[
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('1-Step', 1),
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('2-Step', 2),
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('4-Step', 4),
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('8-Step', 8)],
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value='4-Step',
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interactive=True
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)
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submit = gr.Button(
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scale=1,
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variant='primary'
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)
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video = gr.Video(
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label='AnimateDiff-Lightning',
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autoplay=True,
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)
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prompt.submit(
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fn=generate_image,
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