fix

example3_upscaling.py

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+# 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 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)
+
+#%% Define vars for low-resoltion pass
+prompt1 = "photo of mount vesuvius erupting a terrifying pyroclastic ash cloud"
+prompt2 = "photo of a inside a building full of ash, fire, death, destruction, explosions"
+fixed_seeds = [5054613, 1168652]
+
+width = 512
+height = 384
+num_inference_steps_lores = 40
+nmb_max_branches_lores = 10
+depth_strength_lores = 0.5
+
+fp_ckpt_lores = "../stable_diffusion_models/ckpt/v2-1_512-ema-pruned.ckpt" 
+
+#%% Define vars for high-resoltion pass
+fp_ckpt_hires = "../stable_diffusion_models/ckpt/x4-upscaler-ema.ckpt"
+depth_strength_hires = 0.65
+num_inference_steps_hires = 100
+nmb_branches_final_hires = 6
+dp_imgs = "tmp_transition" # folder for results and intermediate steps
+
+
+#%% Run low-res pass
+sdh = StableDiffusionHolder(fp_ckpt_lores)
+
+#%%
+lb = LatentBlending(sdh)
+lb.set_prompt1(prompt1)
+lb.set_prompt2(prompt2)
+lb.set_width(width)
+lb.set_height(height)
+
+# Run latent blending
+lb.run_transition(
+    depth_strength = depth_strength_lores,
+    nmb_max_branches = nmb_max_branches_lores,
+    fixed_seeds = fixed_seeds
+    )
+
+lb.write_imgs_transition(dp_imgs)
+
+#%% Run high-res pass
+sdh = StableDiffusionHolder(fp_ckpt_hires)
+lb = LatentBlending(sdh) 
+lb.run_upscaling(dp_imgs, depth_strength_hires, num_inference_steps_hires, nmb_branches_final_hires)