Spaces:
Paused
Paused
Update app.py
Browse files
app.py
CHANGED
@@ -1,4 +1,6 @@
|
|
1 |
import gradio as gr
|
|
|
|
|
2 |
from share_btn import community_icon_html, loading_icon_html, share_js
|
3 |
import torch
|
4 |
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
|
@@ -8,12 +10,25 @@ pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_576w", torch_dt
|
|
8 |
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
|
9 |
pipe.enable_model_cpu_offload()
|
10 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
11 |
def infer(prompt):
|
12 |
#prompt = "Darth Vader is surfing on waves"
|
13 |
video_frames = pipe(prompt, num_inference_steps=40, height=320, width=576, num_frames=24).frames
|
14 |
video_path = export_to_video(video_frames)
|
15 |
print(video_path)
|
16 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
17 |
|
18 |
css = """
|
19 |
#col-container {max-width: 510px; margin-left: auto; margin-right: auto;}
|
|
|
1 |
import gradio as gr
|
2 |
+
import numpy as np
|
3 |
+
from PIL import Image
|
4 |
from share_btn import community_icon_html, loading_icon_html, share_js
|
5 |
import torch
|
6 |
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
|
|
|
10 |
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
|
11 |
pipe.enable_model_cpu_offload()
|
12 |
|
13 |
+
pipe_xl = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_XL", torch_dtype=torch.float16, revision="refs/pr/17")
|
14 |
+
pipe_xl.vae.enable_slicing()
|
15 |
+
pipe_xl.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
|
16 |
+
pipe_xl.enable_model_cpu_offload()
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
def infer(prompt):
|
21 |
#prompt = "Darth Vader is surfing on waves"
|
22 |
video_frames = pipe(prompt, num_inference_steps=40, height=320, width=576, num_frames=24).frames
|
23 |
video_path = export_to_video(video_frames)
|
24 |
print(video_path)
|
25 |
+
|
26 |
+
video = [Image.fromarray(frame).resize((1024, 576)) for frame in video_frames]
|
27 |
+
|
28 |
+
video_frames = pipe_xl(prompt, video=video, strength=0.6).frames
|
29 |
+
video_path = export_to_video(video_frames, output_video_path="xl_result.mp4")
|
30 |
+
|
31 |
+
return "xl_result.mp4", gr.Group.update(visible=True)
|
32 |
|
33 |
css = """
|
34 |
#col-container {max-width: 510px; margin-left: auto; margin-right: auto;}
|