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Browse files- demo/MotionDirector_gradio.py +5 -4
- demo/motiondirector.py +3 -2
demo/MotionDirector_gradio.py
CHANGED
@@ -64,11 +64,11 @@ with gr.Blocks() as demo:
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"3-4: [Sports Concepts] -- Playing Golf",
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"3-5: [Sports Concepts] -- Skateboarding",
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],
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label="MotionDirector",
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info="Which MotionDirector would you like to use!"
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)
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text_pormpt = gr.Textbox(label="Text Prompt", value='', placeholder="Input your text prompt here!")
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neg_text_pormpt = gr.Textbox(label="Negative Text Prompt", value='', placeholder="default: None")
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submit = gr.Button("Generate")
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@@ -80,18 +80,19 @@ with gr.Blocks() as demo:
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[generated_video, generated_video_baseline]
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)
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# Examples
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gr.Markdown("## Examples")
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gr.Examples(
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fn=motiondirector,
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examples=[
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["1-1: [Cinematic Shots] -- Zoom Out", "A spaceman standing on the moon captured with a zoom out.",
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-
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["1-2: [Cinematic Shots] -- Zoom In", "A polar bear standing at the top of a snowy mountain captured with a zoom in.", 7938587],
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["1-3: [Cinematic Shots] -- Dolly Zoom (Hitchcockian Zoom) 1", "A panda standing in front of an ancient Chinese temple captured with a dolly zoom.", 8238823],
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["1-4: [Cinematic Shots] -- Dolly Zoom (Hitchcockian Zoom) 2", "A lion sitting on top of a cliff captured with a dolly zoom.", 1675932],
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["1-5: [Cinematic Shots] -- Follow", "A fireman is walking through fire captured with a follow cinematic shot.", 2927089],
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["1-6: [Cinematic Shots] -- Reverse Follow", "A fireman is walking through fire captured with a reverse follow cinematic shot.",
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["1-7: [Cinematic Shots] -- Chest Transition", "An ancient Roman soldier walks through the crowd on the street captured with a chest transition cinematic shot.", 3982271],
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["1-8: [Cinematic Shots] -- Mini Jib Reveal",
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"A British Redcoat soldier is walking through the mountains captured with a mini jib reveal cinematic shot.",
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"3-4: [Sports Concepts] -- Playing Golf",
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"3-5: [Sports Concepts] -- Skateboarding",
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],
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+
label="Select MotionDirector *",
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info="Which MotionDirector would you like to use!"
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)
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+
text_pormpt = gr.Textbox(label="Text Prompt *", value='', placeholder="Input your text prompt here!")
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neg_text_pormpt = gr.Textbox(label="Negative Text Prompt", value='', placeholder="default: None")
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submit = gr.Button("Generate")
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[generated_video, generated_video_baseline]
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)
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gr.Markdown("Note: * denotes required field. Tips: More detailed text prompt is helpful for generating better results.")
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# Examples
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gr.Markdown("## Examples")
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gr.Examples(
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fn=motiondirector,
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examples=[
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["1-1: [Cinematic Shots] -- Zoom Out", "A spaceman standing on the moon captured with a zoom out.",
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+
5894219],
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["1-2: [Cinematic Shots] -- Zoom In", "A polar bear standing at the top of a snowy mountain captured with a zoom in.", 7938587],
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["1-3: [Cinematic Shots] -- Dolly Zoom (Hitchcockian Zoom) 1", "A panda standing in front of an ancient Chinese temple captured with a dolly zoom.", 8238823],
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["1-4: [Cinematic Shots] -- Dolly Zoom (Hitchcockian Zoom) 2", "A lion sitting on top of a cliff captured with a dolly zoom.", 1675932],
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["1-5: [Cinematic Shots] -- Follow", "A fireman is walking through fire captured with a follow cinematic shot.", 2927089],
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["1-6: [Cinematic Shots] -- Reverse Follow", "A fireman is walking through fire captured with a reverse follow cinematic shot.", 271723],
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["1-7: [Cinematic Shots] -- Chest Transition", "An ancient Roman soldier walks through the crowd on the street captured with a chest transition cinematic shot.", 3982271],
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["1-8: [Cinematic Shots] -- Mini Jib Reveal",
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"A British Redcoat soldier is walking through the mountains captured with a mini jib reveal cinematic shot.",
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demo/motiondirector.py
CHANGED
@@ -96,6 +96,7 @@ def prepare_input_latents(
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else:
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random_seed = random.randint(100, 10000000)
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torch.manual_seed(random_seed)
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if '1-' in model_select:
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noise_prior = 0.3
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elif '2-' in model_select:
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@@ -122,7 +123,7 @@ def prepare_input_latents(
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latents = torch.randn(shape, dtype=torch.half)
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latents_base = latents
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return latents, latents_base
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class MotionDirector():
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with torch.autocast(device, dtype=torch.half):
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# prepare input latents
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with torch.no_grad():
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init_latents,init_latents_base = prepare_input_latents(
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pipe=self.pipe,
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batch_size=1,
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num_frames=16,
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else:
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random_seed = random.randint(100, 10000000)
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torch.manual_seed(random_seed)
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print(f"random_seed: {random_seed}")
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if '1-' in model_select:
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noise_prior = 0.3
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elif '2-' in model_select:
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latents = torch.randn(shape, dtype=torch.half)
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latents_base = latents
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return latents, latents_base, random_seed
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class MotionDirector():
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with torch.autocast(device, dtype=torch.half):
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# prepare input latents
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with torch.no_grad():
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init_latents, init_latents_base, random_seed = prepare_input_latents(
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pipe=self.pipe,
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batch_size=1,
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num_frames=16,
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