55 lines
2.2 KiB
Python
55 lines
2.2 KiB
Python
# Copyright 2022 Lunar Ring. All rights reserved.
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# Written by Johannes Stelzer, email stelzer@lunar-ring.ai twitter @j_stelzer
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import torch
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torch.backends.cudnn.benchmark = False
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torch.set_grad_enabled(False)
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import warnings
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warnings.filterwarnings('ignore')
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import warnings
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from latent_blending import LatentBlending
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from stable_diffusion_holder import StableDiffusionHolder
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from huggingface_hub import hf_hub_download
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# %% First let us spawn a stable diffusion holder. Uncomment your version of choice.
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# fp_ckpt = hf_hub_download(repo_id="stabilityai/stable-diffusion-2-1-base", filename="v2-1_512-ema-pruned.ckpt")
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fp_ckpt = hf_hub_download(repo_id="stabilityai/stable-diffusion-2-1", filename="v2-1_768-ema-pruned.ckpt")
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sdh = StableDiffusionHolder(fp_ckpt)
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# %% Next let's set up all parameters
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depth_strength = 0.65 # Specifies how deep (in terms of diffusion iterations the first branching happens)
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t_compute_max_allowed = 15 # Determines the quality of the transition in terms of compute time you grant it
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fixed_seeds = [69731932, 504430820]
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prompt1 = "photo of a beautiful cherry forest covered in white flowers, ambient light, very detailed, magic"
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prompt2 = "photo of an golden statue with a funny hat, surrounded by ferns and vines, grainy analog photograph, mystical ambience, incredible detail"
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fp_movie = 'movie_example1.mp4'
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duration_transition = 12 # In seconds
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# Spawn latent blending
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lb = LatentBlending(sdh)
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lb.set_prompt1(prompt1)
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lb.set_prompt2(prompt2)
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# Run latent blending
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lb.run_transition(
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depth_strength=depth_strength,
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t_compute_max_allowed=t_compute_max_allowed,
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fixed_seeds=fixed_seeds)
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# Save movie
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lb.write_movie_transition(fp_movie, duration_transition)
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