70 lines
2.3 KiB
Python
70 lines
2.3 KiB
Python
# Copyright 2022 Lunar Ring. All rights reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
import os, sys
|
|
import torch
|
|
torch.backends.cudnn.benchmark = False
|
|
import numpy as np
|
|
import warnings
|
|
warnings.filterwarnings('ignore')
|
|
import warnings
|
|
import torch
|
|
from tqdm.auto import tqdm
|
|
from PIL import Image
|
|
import matplotlib.pyplot as plt
|
|
import torch
|
|
from movie_util import MovieSaver
|
|
from typing import Callable, List, Optional, Union
|
|
from latent_blending import LatentBlending, add_frames_linear_interp
|
|
from stable_diffusion_holder import StableDiffusionHolder
|
|
torch.set_grad_enabled(False)
|
|
|
|
#%% First let us spawn a stable diffusion holder
|
|
device = "cuda:0"
|
|
fp_ckpt = "../stable_diffusion_models/ckpt/768-v-ema.ckpt"
|
|
fp_config = '../stablediffusion/configs/stable-diffusion/v2-inference-v.yaml'
|
|
|
|
sdh = StableDiffusionHolder(fp_ckpt, fp_config, device)
|
|
|
|
|
|
#%% Next let's set up all parameters
|
|
quality = 'medium'
|
|
fixed_seeds = [69731932, 504430820]
|
|
|
|
lb = LatentBlending(sdh)
|
|
prompt1 = "photo of a beautiful forest covered in white flowers, ambient light, very detailed, magic"
|
|
prompt2 = "photo of an golden statue with a funny hat, surrounded by ferns and vines, grainy analog photograph, mystical ambience, incredible detail"
|
|
lb.set_prompt1(prompt1)
|
|
lb.set_prompt2(prompt2)
|
|
|
|
lb.autosetup_branching(quality=quality)
|
|
|
|
imgs_transition = lb.run_transition(fixed_seeds=fixed_seeds)
|
|
|
|
# let's get more cheap frames via linear interpolation
|
|
duration_transition = 12
|
|
fps = 60
|
|
imgs_transition_ext = add_frames_linear_interp(imgs_transition, duration_transition, fps)
|
|
|
|
# movie saving
|
|
fp_movie = f"movie_example1.mp4"
|
|
if os.path.isfile(fp_movie):
|
|
os.remove(fp_movie)
|
|
ms = MovieSaver(fp_movie, fps=fps, shape_hw=[sdh.height, sdh.width])
|
|
for img in tqdm(imgs_transition_ext):
|
|
ms.write_frame(img)
|
|
ms.finalize()
|
|
|
|
|