99 lines
3.6 KiB
Python
99 lines
3.6 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 time
|
|
import subprocess
|
|
import warnings
|
|
import torch
|
|
from tqdm.auto import tqdm
|
|
from diffusers import StableDiffusionInpaintPipeline
|
|
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"
|
|
num_inference_steps = 20 # Number of diffusion interations
|
|
fp_ckpt= "../stable_diffusion_models/ckpt/512-inpainting-ema.ckpt"
|
|
fp_config = '../stablediffusion/configs//stable-diffusion/v2-inpainting-inference.yaml'
|
|
|
|
sdh = StableDiffusionHolder(fp_ckpt, fp_config, device, num_inference_steps=num_inference_steps)
|
|
|
|
|
|
#%% Let's make a source image and mask.
|
|
height = 512
|
|
width = 512
|
|
num_inference_steps = 30
|
|
guidance_scale = 5
|
|
fixed_seeds = [629575320, 670154945]
|
|
|
|
lb = LatentBlending(sdh, num_inference_steps, guidance_scale)
|
|
prompt1 = "photo of a futuristic alien temple in a desert, mystic, glowing, organic, intricate, sci-fi movie, mesmerizing, scary"
|
|
lb.set_prompt1(prompt1)
|
|
lb.init_inpainting(init_empty=True)
|
|
lb.set_seed(fixed_seeds[0])
|
|
image_source = lb.run_diffusion(lb.text_embedding1, return_image=True)
|
|
mask_image = 255*np.ones([512,512], dtype=np.uint8)
|
|
mask_image[160:250, 200:320] = 0
|
|
mask_image = Image.fromarray(mask_image)
|
|
|
|
|
|
#%% Next let's set up all parameters
|
|
# FIXME below fix numbers
|
|
# We want 20 diffusion steps, begin with 2 branches, have 3 branches at step 12 (=0.6*20)
|
|
# 10 branches at step 16 (=0.8*20) and 24 branches at step 18 (=0.9*20)
|
|
# Furthermore we want seed 993621550 for keyframeA and seed 54878562 for keyframeB ()
|
|
|
|
num_inference_steps = 20 # Number of diffusion interations
|
|
list_nmb_branches = [2, 3, 10, 24] # Branching structure: how many branches
|
|
list_injection_strength = [0.0, 0.6, 0.8, 0.9] # Branching structure: how deep is the blending
|
|
width = 512
|
|
height = 512
|
|
guidance_scale = 5
|
|
fixed_seeds = [993621550, 280335986]
|
|
|
|
prompt1 = "photo of a futuristic alien temple in a desert, mystic, glowing, organic, intricate, sci-fi movie, mesmerizing, scary"
|
|
prompt2 = "aerial photo of a futuristic alien temple in a coastal area, waves clashing"
|
|
lb.set_prompt1(prompt1)
|
|
lb.set_prompt2(prompt2)
|
|
lb.init_inpainting(image_source, mask_image)
|
|
|
|
imgs_transition = lb.run_transition(list_nmb_branches, list_injection_strength, 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 = "/home/lugo/tmp/latentblending/bobo_incoming.mp4"
|
|
if os.path.isfile(fp_movie):
|
|
os.remove(fp_movie)
|
|
ms = MovieSaver(fp_movie, fps=fps, shape_hw=[lb.height, lb.width])
|
|
for img in tqdm(imgs_transition_ext):
|
|
ms.write_frame(img)
|
|
ms.finalize()
|
|
|