# Copyright 2022 Lunar Ring. All rights reserved. # Written by Johannes Stelzer, email stelzer@lunar-ring.ai twitter @j_stelzer # # 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 torch torch.backends.cudnn.benchmark = False torch.set_grad_enabled(False) import warnings warnings.filterwarnings('ignore') import warnings from latent_blending import LatentBlending from stable_diffusion_holder import StableDiffusionHolder from movie_util import concatenate_movies from huggingface_hub import hf_hub_download # %% First let us spawn a stable diffusion holder. Uncomment your version of choice. # fp_ckpt = hf_hub_download(repo_id="stabilityai/stable-diffusion-2-1-base", filename="v2-1_512-ema-pruned.ckpt") fp_ckpt = hf_hub_download(repo_id="stabilityai/stable-diffusion-2-1", filename="v2-1_768-ema-pruned.ckpt") sdh = StableDiffusionHolder(fp_ckpt) # %% Let's setup the multi transition fps = 30 duration_single_trans = 6 depth_strength = 0.55 # Specifies how deep (in terms of diffusion iterations the first branching happens) # Specify a list of prompts below list_prompts = [] list_prompts.append("surrealistic statue made of glitter and dirt, standing in a lake, atmospheric light, strange glow") list_prompts.append("statue of a mix between a tree and human, made of marble, incredibly detailed") list_prompts.append("weird statue of a frog monkey, many colors, standing next to the ruins of an ancient city") list_prompts.append("statue of a spider that looked like a human") list_prompts.append("statue of a bird that looked like a scorpion") list_prompts.append("statue of an ancient cybernetic messenger annoucing good news, golden, futuristic") # You can optionally specify the seeds list_seeds = [954375479, 332539350, 956051013, 408831845, 250009012, 675588737] t_compute_max_allowed = 12 # per segment fp_movie = 'movie_example2.mp4' lb = LatentBlending(sdh) 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: lb.set_prompt1(list_prompts[i]) lb.set_prompt2(list_prompts[i + 1]) recycle_img1 = False else: lb.swap_forward() lb.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 lb.run_transition( depth_strength=depth_strength, t_compute_max_allowed=t_compute_max_allowed, fixed_seeds=fixed_seeds) # Save movie lb.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)