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latentblending
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fixed example1

This commit is contained in:
Johannes Stelzer 2023-02-17 10:50:38 +01:00
parent 07a5c4ffd7
commit 20a80a5d1f
1 changed files with 7 additions and 6 deletions
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13
example1_standard.py
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@ -33,13 +33,12 @@ torch.set_grad_enabled(False)
#%% First let us spawn a stable diffusion holder
fp_ckpt = "../stable_diffusion_models/ckpt/v2-1_768-ema-pruned.ckpt"
sdh = StableDiffusionHolder(fp_ckpt)
#%% Next let's set up all parameters
quality = 'medium'
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"
@ -50,13 +49,15 @@ fps = 30
# Spawn latent blending
lb = LatentBlending(sdh)
lb.load_branching_profile(quality=quality, depth_strength=depth_strength)
lb.set_prompt1(prompt1)
lb.set_prompt2(prompt2)
#FIXME AssertionError: Either specify t_compute_max_allowed or nmb_max_branches
# Run latent blending
imgs_transition = lb.run_transition(fixed_seeds=fixed_seeds)
imgs_transition = lb.run_transition(
depth_strength = depth_strength,
t_compute_max_allowed = t_compute_max_allowed,
fixed_seeds = fixed_seeds
)
# Let's get more cheap frames via linear interpolation (duration_transition*fps frames)
imgs_transition_ext = add_frames_linear_interp(imgs_transition, duration_transition, fps)