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Update app.py
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app.py
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@@ -1,6 +1,7 @@
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import gradio as gr
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import numpy as np
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from PIL import Image
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from share_btn import community_icon_html, loading_icon_html, share_js
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import torch
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from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
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@@ -15,7 +16,13 @@ pipe_xl.to("cuda")
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def infer(prompt, video_in):
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#del pipe
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#pipe_xl.to("cuda")
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video_frames = pipe_xl(prompt, video=video, strength=0.6).frames
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@@ -102,7 +109,7 @@ with gr.Blocks(css=css) as demo:
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"""
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)
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video_in = gr.Video(type="
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prompt_in = gr.Textbox(label="Prompt", placeholder="Darth Vader is surfing on waves", elem_id="prompt-in")
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#inference_steps = gr.Slider(label="Inference Steps", minimum=10, maximum=100, step=1, value=40, interactive=False)
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submit_btn = gr.Button("Submit")
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import gradio as gr
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import numpy as np
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from PIL import Image
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from moviepy.editor import VideoFileClip
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from share_btn import community_icon_html, loading_icon_html, share_js
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import torch
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from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
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def infer(prompt, video_in):
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# Load the input video
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clip = VideoFileClip(video_in)
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# Convert the video to the desired format
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clip.write_videofile("video.mkv")
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video = [Image.fromarray(frame).resize((1024, 576)) for frame in "video.mkv"]
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#del pipe
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#pipe_xl.to("cuda")
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video_frames = pipe_xl(prompt, video=video, strength=0.6).frames
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"""
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)
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video_in = gr.Video(type="filepath", source="upload")
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prompt_in = gr.Textbox(label="Prompt", placeholder="Darth Vader is surfing on waves", elem_id="prompt-in")
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#inference_steps = gr.Slider(label="Inference Steps", minimum=10, maximum=100, step=1, value=40, interactive=False)
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submit_btn = gr.Button("Submit")
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