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app_df.py
CHANGED
@@ -27,7 +27,7 @@ def generate_diffusion_forced_video(
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shift=8.0,
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inference_steps=30,
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use_usp=False,
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offload=
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fps=24,
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seed=None,
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prompt_enhancer=False,
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@@ -128,32 +128,74 @@ def generate_diffusion_forced_video(
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resolution_options = ["540P", "720P"]
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model_options = ["Skywork/SkyReels-V2-DF-1.3B-540P"] # Update if there are more
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gr.
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gr.
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shift=8.0,
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inference_steps=30,
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use_usp=False,
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offload=True,
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fps=24,
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seed=None,
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prompt_enhancer=False,
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resolution_options = ["540P", "720P"]
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model_options = ["Skywork/SkyReels-V2-DF-1.3B-540P"] # Update if there are more
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with gr.Blocks() as demo:
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with gr.Column():
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gr.Markdown("# SkyReels V2")
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with gr.Row():
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with gr.Column():
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prompt = gr.Textbox(label="Prompt")
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model_id = gr.Dropdown(choices=model_options, value=model_options[0], label="Model ID")
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resolution = gr.Radio(choices=resolution_options, value="540P", label="Resolution", interactive=False)
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num_frames = gr.Slider(minimum=16, maximum=200, value=97, step=1, label="Number of Frames")
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image = gr.Image(type="filepath", label="Input Image (optional)")
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with gr.Accordion("Advanced Settings", open=False):
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ar_step = gr.Number(label="AR Step", value=0)
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causal_attention = gr.Checkbox(label="Causal Attention")
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causal_block_size = gr.Number(label="Causal Block Size", value=1)
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base_num_frames = gr.Number(label="Base Num Frames", value=97)
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overlap_history = gr.Number(label="Overlap History (set for long videos)", value=None)
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addnoise_condition = gr.Number(label="AddNoise Condition", value=0)
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guidance_scale = gr.Slider(minimum=1.0, maximum=20.0, value=6.0, step=0.1, label="Guidance Scale")
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shift = gr.Slider(minimum=0.0, maximum=20.0, value=8.0, step=0.1, label="Shift")
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inference_steps = gr.Slider(minimum=1, maximum=100, value=30, step=1, label="Inference Steps")
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use_usp = gr.Checkbox(label="Use USP")
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offload = gr.Checkbox(label="Offload", value=True, interactive=False)
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fps = gr.Slider(minimum=1, maximum=60, value=24, step=1, label="FPS")
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seed = gr.Number(label="Seed (optional)", precision=0)
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prompt_enhancer = gr.Checkbox(label="Prompt Enhancer")
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use_teacache = gr.Checkbox(label="Use TeaCache")
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teacache_thresh = gr.Slider(minimum=0.0, maximum=1.0, value=0.2, step=0.01, label="TeaCache Threshold")
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use_ret_steps = gr.Checkbox(label="Use Retention Steps")
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submit_btn = gr.Button("Generate")
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with gr.Column():
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output_video = gr.Video(label="Generated Video")
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submit_btn.click(
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fn = generate_diffusion_forced_video,
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inputs = [
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prompt,
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model_id,
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resolution,
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num_frames,
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image,
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ar_step,
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causal_attention,
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causal_block_size,
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base_num_frames,
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overlap_history,
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addnoise_condition,
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guidance_scale,
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shift,
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inference_steps,
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use_usp,
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offload,
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fps,
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seed,
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prompt_enhancer,
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teacache,
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teacache_thresh,
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use_ret_steps
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],
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outputs = [
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output_video
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]
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)
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demo.launch(show_error=True, show_api=False, share=False)
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