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import gradio as gr
import torch
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
from diffusers.utils import export_to_video
from video_diffusion.utils.scheduler_list import diff_scheduler_list, get_scheduler_list
stable_model_list =["damo-vilab/text-to-video-ms-1.7b","cerspense/zeroscope_v2_576w"]
class DamoText2VideoGenerator:
def __init__(self):
self.pipe = None
def load_model(self, stable_model, scheduler):
if self.pipe is None:
self.pipe = DiffusionPipeline.from_pretrained(
stable_model, torch_dtype=torch.float16, variant="fp16"
)
self.pipe = get_scheduler_list(pipe=self.pipe, scheduler=scheduler)
self.pipe.to("cuda")
self.pipe.enable_xformers_memory_efficient_attention()
return self.pipe
def generate_video(
self,
prompt: str,
negative_prompt: str,
stable_model:str,
num_frames: int,
num_inference_steps: int,
guidance_scale: int,
height: int,
width: int,
scheduler: str,
):
pipe = self.load_model(stable_model=stable_model, scheduler=scheduler)
video = pipe(
prompt,
negative_prompt=negative_prompt,
num_frames=int(num_frames),
height=height,
width=width,
num_inference_steps=num_inference_steps,
guidance_scale=guidance_scale,
).frames
video_path = export_to_video(video)
return video_path
def app():
with gr.Blocks():
with gr.Row():
with gr.Column():
dano_text2video_prompt = gr.Textbox(lines=1, placeholder="Prompt", show_label=False)
dano_text2video_negative_prompt = gr.Textbox(
lines=1, placeholder="Negative Prompt", show_label=False
)
with gr.Row():
with gr.Column():
dano_text2video_model_list = gr.Dropdown(
choices=stable_model_list,
label="Model List",
value=stable_model_list[0],
)
dano_text2video_num_inference_steps = gr.Slider(
minimum=1,
maximum=100,
value=50,
step=1,
label="Inference Steps",
)
dano_text2video_guidance_scale = gr.Slider(
minimum=1,
maximum=15,
value=7,
step=1,
label="Guidance Scale",
)
dano_text2video_num_frames = gr.Slider(
minimum=1,
maximum=50,
value=16,
step=1,
label="Number of Frames",
)
with gr.Row():
with gr.Column():
dano_text2video_height = gr.Slider(
minimum=128,
maximum=1280,
value=512,
step=32,
label="Height",
)
dano_text2video_width = gr.Slider(
minimum=128,
maximum=1280,
value=512,
step=32,
label="Width",
)
damo_text2video_scheduler = gr.Dropdown(
choices=diff_scheduler_list,
label="Scheduler",
value=diff_scheduler_list[6],
)
dano_text2video_generate = gr.Button(value="Generator")
with gr.Column():
dano_output = gr.Video(label="Output")
dano_text2video_generate.click(
fn=DamoText2VideoGenerator().generate_video,
inputs=[
dano_text2video_prompt,
dano_text2video_negative_prompt,
dano_text2video_model_list,
dano_text2video_num_frames,
dano_text2video_num_inference_steps,
dano_text2video_guidance_scale,
dano_text2video_height,
dano_text2video_width,
damo_text2video_scheduler,
],
outputs=dano_output,
)
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