96 lines
2.9 KiB
Python
96 lines
2.9 KiB
Python
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# 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 os, sys
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import torch
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torch.backends.cudnn.benchmark = False
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import numpy as np
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import warnings
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warnings.filterwarnings('ignore')
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import warnings
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import torch
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from tqdm.auto import tqdm
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from PIL import Image
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# import matplotlib.pyplot as plt
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import torch
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from movie_util import MovieSaver
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from typing import Callable, List, Optional, Union
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from latent_blending import LatentBlending, add_frames_linear_interp
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from stable_diffusion_holder import StableDiffusionHolder
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torch.set_grad_enabled(False)
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#%% First let us spawn a stable diffusion holder
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fp_ckpt = "../stable_diffusion_models/riffusion/riffusion-model-v1.ckpt"
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fp_config = "configs/v1-inference.yaml"
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sdh = StableDiffusionHolder(fp_ckpt, fp_config)
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#%% Next let's set up all parameters
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depth_strength = 0.25 # Specifies how deep (in terms of diffusion iterations the first branching happens)
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t_compute_max_allowed = 10 # 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 = "ambient pad trippy"
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prompt2 = "ambient pad psychedelic"
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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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lb.branch1_influence = 0.0
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lb.branch1_max_depth_influence = 0.65
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lb.branch1_influence_decay = 0.8
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lb.parental_influence = 0.0
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lb.parental_max_depth_influence = 1.0
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lb.parental_influence_decay = 1.0
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# x = lb.compute_latents1(True)
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# Image.fromarray(x).save("//home/lugo/git/riffusion/testA.png")
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# xxx
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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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)
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dp_save = "/home/lugo/git/riffusion/latentblending"
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for i in range(len(lb.tree_final_imgs)):
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fp_save = os.path.join(dp_save, f"sound_{str(i).zfill(3)}.png")
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Image.fromarray(lb.tree_final_imgs[i]).save(fp_save)
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#%% take this file
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"""
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#!/bin/bash
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FOLDER="/home/lugo/git/riffusion/latentblending"
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for file in "$FOLDER"/*.png; do
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filename=$(basename -- "$file") # get the filename without the folder path
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filename_no_ext="${filename%.*}" # remove the file extension (i.e. png)
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# call riffusion.cli to convert the png to wav
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python -m riffusion.cli image-to-audio --image "$file" --audio "${FOLDER}/${filename_no_ext}.wav"
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done
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"""
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