Spaces:
No application file
No application file
File size: 2,125 Bytes
940cc9a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
import torch
import warnings
from diffusers import AutoPipelineForText2Image
from lunar_tools import concatenate_movies
from latentblending.blending_engine import BlendingEngine
import numpy as np
torch.set_grad_enabled(False)
torch.backends.cudnn.benchmark = False
warnings.filterwarnings('ignore')
# %% First let us spawn a stable diffusion holder. Uncomment your version of choice.
pretrained_model_name_or_path = "stabilityai/stable-diffusion-xl-base-1.0"
# pretrained_model_name_or_path = "stabilityai/sdxl-turbo"
pipe = AutoPipelineForText2Image.from_pretrained(pretrained_model_name_or_path, torch_dtype=torch.float16, variant="fp16")
pipe.to('cuda')
be = BlendingEngine(pipe, do_compile=True)
be.set_negative_prompt("blurry, pale, low-res, lofi")
# %% Let's setup the multi transition
fps = 30
duration_single_trans = 10
be.set_dimensions((1024, 1024))
nmb_prompts = 20
# Specify a list of prompts below
#%%
list_prompts = []
list_prompts.append("high resolution ultra 8K image with lake and forest")
list_prompts.append("strange and alien desolate lanscapes 8K")
list_prompts.append("ultra high res psychedelic skyscraper city landscape 8K unreal engine")
#%%
fp_movie = f'surreal_nmb{len(list_prompts)}.mp4'
# Specify the seeds
list_seeds = np.random.randint(0, np.iinfo(np.int32).max, len(list_prompts))
list_movie_parts = []
for i in range(len(list_prompts) - 1):
# For a multi transition we can save some computation time and recycle the latents
if i == 0:
be.set_prompt1(list_prompts[i])
be.set_prompt2(list_prompts[i + 1])
recycle_img1 = False
else:
be.swap_forward()
be.set_prompt2(list_prompts[i + 1])
recycle_img1 = True
fp_movie_part = f"tmp_part_{str(i).zfill(3)}.mp4"
fixed_seeds = list_seeds[i:i + 2]
# Run latent blending
be.run_transition(
recycle_img1=recycle_img1,
fixed_seeds=fixed_seeds)
# Save movie
be.write_movie_transition(fp_movie_part, duration_single_trans)
list_movie_parts.append(fp_movie_part)
# Finally, concatente the result
concatenate_movies(fp_movie, list_movie_parts)
|