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#!/usr/bin/env python
from __future__ import annotations
import os
import gradio as gr
from gradio_demo.runner import Runner
def create_demo(runner: Runner,
pipe: InferencePipeline | None = None) -> gr.Blocks:
hf_token = os.getenv('HF_TOKEN')
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
with gr.Box():
gr.Markdown('Input Data')
input_video = gr.File(label='Input video')
input_prompt = gr.Textbox(
label='Input prompt',
max_lines=1,
placeholder='A car is moving on the road.')
gr.Markdown('''
- Upload a video and write a `Input Prompt` that describes the video.
''')
with gr.Column():
with gr.Box():
gr.Markdown('Input Parameters')
with gr.Row():
model_path = gr.Text(
label='Path to off-the-shelf model',
value='CompVis/stable-diffusion-v1-4',
max_lines=1)
resolution = gr.Dropdown(choices=['512', '768'],
value='512',
label='Resolution',
visible=False)
with gr.Accordion('Advanced settings', open=False):
sample_start_idx = gr.Number(
label='Start Frame Index',value=0)
sample_frame_rate = gr.Number(
label='Frame Rate',value=1)
n_sample_frames = gr.Number(
label='Number of Frames',value=8)
guidance_scale = gr.Number(
label='Guidance Scale', value=7.5)
seed = gr.Slider(label='Seed',
minimum=0,
maximum=100000,
step=1,
randomize=True,
value=33)
input_token = gr.Text(label='Hugging Face Write Token',
placeholder='',
visible=False if hf_token else True)
gr.Markdown('''
- Upload input video or choose an exmple blow
- Set hyperparameters & click start
- It takes a few minutes to download model first
''')
with gr.Row():
with gr.Column():
validation_prompt = gr.Text(
label='Validation Prompt',
placeholder=
'prompt to test the model, e.g: a Lego man is surfing')
remove_gpu_after_running = gr.Checkbox(
label='Remove GPU after running',
value=False,
interactive=bool(os.getenv('SPACE_ID')),
visible=False)
with gr.Row():
result = gr.Video(label='Result')
# examples
with gr.Row():
examples = [
[
'CompVis/stable-diffusion-v1-4',
"data/car-moving.mp4",
'A car is moving on the road.',
8, 0, 1,
'A jeep car is moving on the desert.',
7.5, 512, 33,
False, None,
],
[
'CompVis/stable-diffusion-v1-4',
"data/black-swan.mp4",
'A blackswan is swimming on the water.',
8, 0, 4,
'A white swan is swimming on the water.',
7.5, 512, 33,
False, None,
],
[
'CompVis/stable-diffusion-v1-4',
"data/child-riding.mp4",
'A child is riding a bike on the road.',
8, 0, 1,
'A lego child is riding a bike on the road.',
7.5, 512, 33,
False, None,
],
[
'CompVis/stable-diffusion-v1-4',
"data/car-turn.mp4",
'A jeep car is moving on the road.',
8, 0, 6,
'A jeep car is moving on the snow.',
7.5, 512, 33,
False, None,
],
[
'CompVis/stable-diffusion-v1-4',
"data/rabbit-watermelon.mp4",
'A rabbit is eating a watermelon.',
8, 0, 6,
'A puppy is eating an orange.',
7.5, 512, 33,
False, None,
],
[
'CompVis/stable-diffusion-v1-4',
"data/brown-bear.mp4",
'A brown bear is sitting on the ground.',
8, 0, 6,
'A black bear is sitting on the grass.',
7.5, 512, 33,
False, None,
],
]
gr.Examples(examples=examples,
fn=runner.run_vid2vid_zero,
inputs=[
model_path, input_video, input_prompt,
n_sample_frames, sample_start_idx, sample_frame_rate,
validation_prompt, guidance_scale, resolution, seed,
remove_gpu_after_running,
input_token,
],
outputs=result,
cache_examples=os.getenv('SYSTEM') == 'spaces'
)
# run
run_button_vid2vid_zero = gr.Button('Start vid2vid-zero')
run_button_vid2vid_zero.click(
fn=runner.run_vid2vid_zero,
inputs=[
model_path, input_video, input_prompt,
n_sample_frames, sample_start_idx, sample_frame_rate,
validation_prompt, guidance_scale, resolution, seed,
remove_gpu_after_running,
input_token,
],
outputs=result)
return demo
if __name__ == '__main__':
hf_token = os.getenv('HF_TOKEN')
runner = Runner(hf_token)
demo = create_demo(runner)
demo.queue(max_size=1).launch(share=False)
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