Update app.py
Browse files
app.py
CHANGED
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import os, json, re, sys, subprocess, gc, tqdm, math, time, random, threading, spaces,
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import gradio as gr
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from PIL import Image, ImageOps
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from moviepy import VideoFileClip
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@@ -115,7 +116,7 @@ def convert_to_gif(video_path):
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return gif_path
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@spaces.GPU(duration=180)
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def plex(prompt,image_input,seed_value,scale_status,rife_status,progress=gr.Progress(track_tqdm=True)):
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seed = seed_value
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if seed == -1:
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seed = random.randint(0, 2**8 - 1)
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@@ -134,7 +135,7 @@ def plex(prompt,image_input,seed_value,scale_status,rife_status,progress=gr.Prog
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image = ImageOps.exif_transpose(Image.fromarray(tensor))
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prompt = prompt.strip('"')
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generator = torch.Generator(device).manual_seed(seed) if seed else None
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video_pt = pipe(prompt=prompt,image=image,num_videos_per_prompt=1,num_inference_steps=
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latents = video_pt.frames
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##free_memory()
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if scale_status:
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@@ -169,7 +170,7 @@ examples_images = [
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with gr.Blocks() as demo:
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gr.Markdown("""
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<div style="text-align: center; font-size: 32px; font-weight: bold; margin-bottom: 20px;">
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ConsisID Space🤗
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</div>
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<div style="text-align: center;">
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<a href="https://huggingface.co/BestWishYsh/ConsisID">🤗 Model Hub</a> |
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@@ -192,20 +193,17 @@ with gr.Blocks() as demo:
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with gr.Column():
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with gr.Accordion("IPT2V: Face Input", open=True):
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image_input = gr.Image(label="Input Image (should contain clear face)")
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prompt = gr.Textbox(label="Prompt (Less than 200 Words)", placeholder="Enter your prompt here", lines=
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with gr.Group():
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with gr.Column():
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with gr.Row():
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)
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with gr.Row():
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enable_scale = gr.Checkbox(label="Super-Resolution (720 × 480 -> 2880 × 1920)", value=False)
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enable_rife = gr.Checkbox(label="Frame Interpolation (8fps -> 16fps)", value=True)
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gr.Markdown(
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"✨In this demo, we use [RIFE](https://github.com/hzwer/ECCV2022-RIFE) for frame interpolation and [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN) for upscaling(Super-Resolution)."
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)
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generate_button = gr.Button("🎬 Generate Video")
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@@ -223,7 +221,7 @@ with gr.Blocks() as demo:
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)
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generate_button.click(
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fn=plex,
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inputs=[prompt, image_input, seed_param, enable_scale, enable_rife],
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outputs=[video_output, download_video_button, download_gif_button, seed_text],
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)
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import os, json, re, sys, subprocess, gc, tqdm, math, time, random, threading, spaces, torch
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import numpy as np
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import gradio as gr
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from PIL import Image, ImageOps
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from moviepy import VideoFileClip
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return gif_path
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@spaces.GPU(duration=180)
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def plex(prompt,image_input,stips,gscale,seed_value,scale_status,rife_status,progress=gr.Progress(track_tqdm=True)):
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seed = seed_value
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if seed == -1:
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seed = random.randint(0, 2**8 - 1)
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image = ImageOps.exif_transpose(Image.fromarray(tensor))
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prompt = prompt.strip('"')
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generator = torch.Generator(device).manual_seed(seed) if seed else None
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video_pt = pipe(prompt=prompt,image=image,num_videos_per_prompt=1,num_inference_steps=stips,num_frames=49,use_dynamic_cfg=False,guidance_scale=gscale,generator=generator,id_vit_hidden=id_vit_hidden,id_cond=id_cond,kps_cond=kps_cond,output_type="pt",)
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latents = video_pt.frames
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##free_memory()
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if scale_status:
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with gr.Blocks() as demo:
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gr.Markdown("""
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<div style="text-align: center; font-size: 32px; font-weight: bold; margin-bottom: 20px;">
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🤗ConsisID Space🤗
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</div>
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<div style="text-align: center;">
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<a href="https://huggingface.co/BestWishYsh/ConsisID">🤗 Model Hub</a> |
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with gr.Column():
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with gr.Accordion("IPT2V: Face Input", open=True):
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image_input = gr.Image(label="Input Image (should contain clear face)")
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prompt = gr.Textbox(label="Prompt (Less than 200 Words)", placeholder="Enter your prompt here", lines=3)
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with gr.Group():
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with gr.Column():
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with gr.Row():
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stips = gr.Slider(label="Steps", minimum=6, step=1, maximum=10, value=10)
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gscale = gr.Slider(label="Guidance scale", minimum=1, step=0.1, maximum=20, value=7.0)
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seed_param = gr.Slider(label="Inference Seed (Leave -1 for random)", minimum=0, step=32, maximum=2**8 - 1, value=-1)
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with gr.Row():
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enable_scale = gr.Checkbox(label="Super-Resolution (720 × 480 -> 2880 × 1920) [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN)", value=False)
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enable_rife = gr.Checkbox(label="Frame Interpolation (8fps -> 16fps) [RIFE](https://github.com/hzwer/ECCV2022-RIFE)", value=True)
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generate_button = gr.Button("🎬 Generate Video")
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)
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generate_button.click(
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fn=plex,
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inputs=[prompt, image_input, stips, gscale, seed_param, enable_scale, enable_rife],
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outputs=[video_output, download_video_button, download_gif_button, seed_text],
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)
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