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lllyasviel
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40a0a2b
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Parent(s):
4cd7c68
revert to 1.0.36
Browse files- fooocus_version.py +1 -1
- modules/async_worker.py +2 -2
- modules/core.py +2 -3
- modules/sdxl_styles.py +2 -2
- readme.md +2 -2
- update_log.md +0 -8
fooocus_version.py
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version = '1.0.
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version = '1.0.36'
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modules/async_worker.py
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@@ -45,10 +45,10 @@ def worker():
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if performance_selction == 'Speed':
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steps = 30
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switch =
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else:
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steps = 60
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switch =
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width, height = aspect_ratios[aspect_ratios_selction]
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if performance_selction == 'Speed':
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steps = 30
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switch = 20
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else:
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steps = 60
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switch = 40
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width, height = aspect_ratios[aspect_ratios_selction]
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modules/core.py
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@@ -92,7 +92,7 @@ def get_previewer(device, latent_format):
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@torch.no_grad()
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def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sampler_name='
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scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
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force_full_denoise=False, callback_function=None):
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# SCHEDULERS = ["normal", "karras", "exponential", "simple", "ddim_uniform"]
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@@ -134,7 +134,6 @@ def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sa
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noise_mask = prepare_mask(noise_mask, noise.shape, device)
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comfy.model_management.load_model_gpu(model)
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real_model = model.model
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noise = noise.to(device)
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@torch.no_grad()
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def ksampler_with_refiner(model, positive, negative, refiner, refiner_positive, refiner_negative, latent,
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seed=None, steps=30, refiner_switch_step=20, cfg=7.0, sampler_name='
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scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
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force_full_denoise=False, callback_function=None):
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# SCHEDULERS = ["normal", "karras", "exponential", "simple", "ddim_uniform"]
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@torch.no_grad()
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def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sampler_name='dpmpp_2m_sde_gpu',
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scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
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force_full_denoise=False, callback_function=None):
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# SCHEDULERS = ["normal", "karras", "exponential", "simple", "ddim_uniform"]
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noise_mask = prepare_mask(noise_mask, noise.shape, device)
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comfy.model_management.load_model_gpu(model)
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real_model = model.model
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noise = noise.to(device)
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@torch.no_grad()
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def ksampler_with_refiner(model, positive, negative, refiner, refiner_positive, refiner_negative, latent,
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seed=None, steps=30, refiner_switch_step=20, cfg=7.0, sampler_name='dpmpp_2m_sde_gpu',
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scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
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force_full_denoise=False, callback_function=None):
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# SCHEDULERS = ["normal", "karras", "exponential", "simple", "ddim_uniform"]
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modules/sdxl_styles.py
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},
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{
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"name": "cinematic-default",
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"prompt": "cinematic still {prompt} . emotional, harmonious, vignette, highly detailed, high budget, moody, epic, gorgeous, film grain, grainy",
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"negative_prompt": "
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},
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{
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"name": "sai-3d-model",
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},
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{
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"name": "cinematic-default",
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"prompt": "cinematic still {prompt} . emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
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"negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured"
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},
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{
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"name": "sai-3d-model",
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readme.md
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# Fooocus
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<img src="https://github.com/lllyasviel/Fooocus/assets/19834515/
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Fooocus is an image generating software.
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6. The parameters of samplers are carefully tuned.
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7. Because XL uses positional encoding for generation resolution, images generated by several fixed resolutions look a bit better than that from arbitrary resolutions (because the positional encoding is not very good at handling int numbers that are unseen during training). This suggests that the resolutions in UI may be hard coded for best results.
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8. Separated prompts for two different text encoders seem unnecessary. Separated prompts for base model and refiner may work but the effects are random, and we refrain from implement this.
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9. DPM family
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## Advanced Features
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# Fooocus
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<img src="https://github.com/lllyasviel/Fooocus/assets/19834515/bcb0336b-5c79-4de2-b0cb-f7f68c753a88" width=100%>
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Fooocus is an image generating software.
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6. The parameters of samplers are carefully tuned.
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7. Because XL uses positional encoding for generation resolution, images generated by several fixed resolutions look a bit better than that from arbitrary resolutions (because the positional encoding is not very good at handling int numbers that are unseen during training). This suggests that the resolutions in UI may be hard coded for best results.
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8. Separated prompts for two different text encoders seem unnecessary. Separated prompts for base model and refiner may work but the effects are random, and we refrain from implement this.
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9. DPM family seems well-suited for XL, since XL sometimes generates overly smooth texture but DPM family sometimes generate overly dense detail in texture. Their joint effect looks neutral and appealing to human perception.
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## Advanced Features
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update_log.md
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### 1.0.38
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* Update dependency, update to sampler.
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### 1.0.37
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* Cinematic-default v2.
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### 1.0.36
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* Change gaussian kernel to anisotropic kernel.
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### 1.0.36
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* Change gaussian kernel to anisotropic kernel.
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