# 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 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)
# %% Next let's set up all parameters
depth_strength = 0.65  # Specifies how deep (in terms of diffusion iterations the first branching happens)
t_compute_max_allowed = 15  # Determines the quality of the transition in terms of compute time you grant it
fixed_seeds = [69731932, 504430820]

prompt1 = "photo of a beautiful cherry forest covered in white flowers, ambient light, very detailed, magic"
prompt2 = "photo of an golden statue with a funny hat, surrounded by ferns and vines, grainy analog photograph, mystical ambience, incredible detail"

fp_movie = 'movie_example1.mp4'
duration_transition = 12  # In seconds

# Spawn latent blending
lb = LatentBlending(sdh)
lb.set_prompt1(prompt1)
lb.set_prompt2(prompt2)

# 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, duration_transition)