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import argparse
import imageio
import numpy as np
import gradio as gr
from PIL import Image
from demo.motiondirector import MotionDirector
runner = MotionDirector()
def motiondirector(model_select, text_pormpt, neg_text_pormpt, random_seed=1, steps=25, guidance_scale=7.5, baseline_select=False):
return runner(model_select, text_pormpt, neg_text_pormpt, int(random_seed) if random_seed != "" else 1, int(steps), float(guidance_scale), baseline_select)
with gr.Blocks() as demo:
gr.HTML(
"""
<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
<a href="https://github.com/showlab/MotionDirector" style="margin-right: 20px; text-decoration: none; display: flex; align-items: center;">
</a>
<div>
<h1 >MotionDirector: Motion Customization of Text-to-Video Diffusion Models</h1>
<h5 style="margin: 0;">More MotionDirectors are on the way. Stay tuned 🔥!</h5>
<h5 style="margin: 0;"> If you like our project, please give us a star ✨ on Github for the latest update.</h5>
</br>
<div style="display: flex; justify-content: center; align-items: center; text-align: center;>
<a href="https://arxiv.org/abs/2310.08465"></a>
<a href="https://arxiv.org/abs/2310.08465"><img src="https://img.shields.io/badge/arXiv-2310.08465-b31b1b.svg"></a>
<a href="https://showlab.github.io/MotionDirector"><img src="https://img.shields.io/badge/Project_Page-MotionDirector-green"></a>
<a href="https://github.com/showlab/MotionDirector"><img src="https://img.shields.io/badge/Github-Code-blue"></a>
</div>
</div>
</div>
""")
with gr.Row():
generated_video_baseline = gr.Video(format="mp4", label="Video Generated by base model (ZeroScope with same seed)")
generated_video = gr.Video(format="mp4", label="Video Generated by MotionDirector")
with gr.Column():
baseline_select = gr.Checkbox(label="Compare with baseline (ZeroScope with same seed)", info="Run baseline? Note: Inference time will be doubled.")
random_seed = gr.Textbox(label="Random seed", value=1, info="default: 1")
sampling_steps = gr.Textbox(label="Sampling steps", value=30, info="default: 30")
guidance_scale = gr.Textbox(label="Guidance scale", value=12, info="default: 12")
with gr.Row():
model_select = gr.Dropdown(
["1-1: [Cinematic Shots] -- Zoom Out",
"1-2: [Cinematic Shots] -- Zoom In",
"1-3: [Cinematic Shots] -- Zoom Out",
"1-3: [Cinematic Shots] -- Dolly Zoom (Hitchcockian Zoom) 1",
"1-4: [Cinematic Shots] -- Dolly Zoom (Hitchcockian Zoom) 2",
"1-5: [Cinematic Shots] -- Follow",
"1-6: [Cinematic Shots] -- Reverse Follow",
"1-7: [Cinematic Shots] -- Chest Transition",
"1-8: [Cinematic Shots] -- Mini Jib Reveal",
"1-9: [Cinematic Shots] -- Orbit",
"1-10: [Cinematic Shots] -- Pull Back",
"2-1: [Object Trajectory] -- Right to Left",
"2-2: [Object Trajectory] -- Left to Right",
"3-1: [Sports Concepts] -- Riding Bicycle",
"3-2: [Sports Concepts] -- Riding Horse",
"3-3: [Sports Concepts] -- Lifting Weights",
"3-4: [Sports Concepts] -- Playing Golf",
"3-5: [Sports Concepts] -- Skateboarding",
],
label="Select MotionDirector *",
info="Which MotionDirector would you like to use!"
)
text_pormpt = gr.Textbox(label="Text Prompt *", value='', placeholder="Input your text prompt here!")
neg_text_pormpt = gr.Textbox(label="Negative Text Prompt", value='', placeholder="default: None")
submit = gr.Button("Generate")
# when the `submit` button is clicked
submit.click(
motiondirector,
[model_select, text_pormpt, neg_text_pormpt, random_seed, sampling_steps, guidance_scale, baseline_select],
[generated_video, generated_video_baseline]
)
gr.Markdown("Note: * denotes required field. Tips: More detailed text prompt is helpful for generating better results.")
# Examples
gr.Markdown("## Examples")
gr.Examples(
fn=motiondirector,
examples=[
["1-1: [Cinematic Shots] -- Zoom Out", "A spaceman standing on the moon captured with a zoom out.",
5894219],
["1-2: [Cinematic Shots] -- Zoom In", "A polar bear standing at the top of a snowy mountain captured with a zoom in.", 7938587],
["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],
["1-4: [Cinematic Shots] -- Dolly Zoom (Hitchcockian Zoom) 2", "A lion sitting on top of a cliff captured with a dolly zoom.", 1675932],
["1-5: [Cinematic Shots] -- Follow", "A fireman is walking through fire captured with a follow cinematic shot.", 2927089],
["1-6: [Cinematic Shots] -- Reverse Follow", "A fireman is walking through fire captured with a reverse follow cinematic shot.", 271723],
["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],
["1-8: [Cinematic Shots] -- Mini Jib Reveal",
"A British Redcoat soldier is walking through the mountains captured with a mini jib reveal cinematic shot.",
566917],
["1-9: [Cinematic Shots] -- Orbit", "A spaceman on the moon captured with an orbit cinematic shot.", 5899496],
["1-10: [Cinematic Shots] -- Pull Back", "A spaceman on the moon looking at a lunar rover captured with a pull back cinematic shot.",
5585865],
["2-1: [Object Trajectory] -- Right to Left", "A tank is running on the moon.", 2047046],
["2-2: [Object Trajectory] -- Left to Right", "A tiger is running in the forest.", 3463673],
["3-1: [Sports Concepts] -- Riding Bicycle", "An astronaut is riding a bicycle past the pyramids Mars 4K high quailty highly detailed.", 4422954],
["3-2: [Sports Concepts] -- Riding Horse", "A man riding an elephant through the jungle.", 6230765],
["3-3: [Sports Concepts] -- Lifting Weights", "A panda is lifting weights in a garden.", 1699276],
["3-4: [Sports Concepts] -- Playing Golf", "A monkey is playing golf on a field full of flowers.", 4156856],
["3-5: [Sports Concepts] -- Skateboarding", "An astronaut is skateboarding on Mars.", 6615212],
],
inputs=[model_select, text_pormpt, random_seed],
outputs=generated_video,
)
demo.queue(max_size=15)
demo.launch(share=True)
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