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In a Cyberpunk City with Vinava AM
vinava-am:v1.0
evevalentine2017
evevalentine2017
·
Jan 2
331
Input
prompt
Specify things to see in the output
(masterpiece, best quality), aging gracefully, bulky, 1 girl, high-tech metropolis. This tableau, inspired by Yoko Honda’s artistic flair, is a celebration of color, combining the organic with the digital, and the tranquility of nature with the pulsating life of an urban landscape, <lora:more_details:0.7>
negative_prompt
Specify things to not see in the output
By bad artist -neg, ng_deepnegative_v1_75t, verybadimagenegative_v1.3, watermark, text, bad hands, poorly drawn hands
num_outputs
Number of output images
4
width
Output image width
768
height
Output image height
768
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
true
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.55
detail
Enhance/diminish detail while keeping the overall style/character
0.1
brightness
Adjust brightness
0
contrast
Adjust contrast
0.2
saturation
Adjust saturation
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
179129430
input_image
Base image that the output should be generated from. This is useful when you want to add some detail to input_image. For example, if prompt is "sunglasses" and input_image has a man, there is the man wearing sunglasses in the output.
input_image_redrawing_strength
How differ the output is from input_image. Used only when input_image is given.
0.55
reference_image
Image with which the output should share identity (e.g. face of a person or type of a dog)
reference_image_strength
Strength of applying reference_image. Used only when reference_image is given.
1
reference_pose_image
Image with a reference pose
reference_pose_strength
Strength of applying reference_pose_image. Used only when reference_pose_image is given.
1
reference_depth_image
Image with a reference depth
reference_depth_strength
Strength of applying reference_depth_image. Used only when reference_depth_image is given.
1
sampler
Sampler type
DPM++ 2M Karras
samping_steps
Number of denoising steps
30
cfg_scale
Scale for classifier-free guidance
8.5
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
kl-f8-anime2_fp16.safetensors
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
more_details.safetensors
lora_2
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
lora_3
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
embedding_1
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
By bad artist -neg.pt
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
ng_deepnegative_v1_75t.pt
embedding_3
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
verybadimagenegative_v1.3.pt
disable_prompt_modification
Disable automatically adding suggested prompt modification. Built-in LoRAs and trigger words will remain.
false
Output
https://files.tungsten.run/uploads/015ab50b3cd2437695bd05ccae863c78/00000-179129430.webp
https://files.tungsten.run/uploads/9639822c0e5b4acd9c39576299496829/00001-179129431.webp
https://files.tungsten.run/uploads/f3fe49b5f4a24ca88a5362dbe0912bdb/00002-179129432.webp
https://files.tungsten.run/uploads/3c49a514e26347ed89a166b3504267ed/00003-179129433.webp
Finished in 45.9 seconds
Preparing inputs... Processing... Loading VAE weight: models/VAE/kl-f8-anime2_fp16.safetensors Full prompt: (masterpiece, best quality), aging gracefully, bulky, 1 girl, high-tech metropolis. This tableau, inspired by Yoko Honda’s artistic flair, is a celebration of color, combining the organic with the digital, and the tranquility of nature with the pulsating life of an urban landscape, <lora:more_details:0.7>, <lora:add_detail:0.1>, <lora:contrast_slider_v10:0.2> Full negative prompt: By bad artist -neg, ng_deepnegative_v1_75t, verybadimagenegative_v1.3, watermark, text, bad hands, poorly drawn hands 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:17, 1.61it/s] 7%|▋ | 2/30 [00:01<00:17, 1.56it/s] 10%|█ | 3/30 [00:01<00:17, 1.57it/s] 13%|█▎ | 4/30 [00:02<00:16, 1.56it/s] 17%|█▋ | 5/30 [00:03<00:16, 1.56it/s] 20%|██ | 6/30 [00:03<00:15, 1.56it/s] 23%|██▎ | 7/30 [00:04<00:14, 1.55it/s] 27%|██▋ | 8/30 [00:05<00:14, 1.55it/s] 30%|███ | 9/30 [00:05<00:13, 1.55it/s] 33%|███▎ | 10/30 [00:06<00:12, 1.55it/s] 37%|███▋ | 11/30 [00:07<00:12, 1.55it/s] 40%|████ | 12/30 [00:07<00:11, 1.55it/s] 43%|████▎ | 13/30 [00:08<00:11, 1.54it/s] 47%|████▋ | 14/30 [00:09<00:10, 1.54it/s] 50%|█████ | 15/30 [00:09<00:09, 1.54it/s] 53%|█████▎ | 16/30 [00:10<00:09, 1.54it/s] 57%|█████▋ | 17/30 [00:10<00:08, 1.54it/s] 60%|██████ | 18/30 [00:11<00:07, 1.54it/s] 63%|██████▎ | 19/30 [00:12<00:07, 1.54it/s] 67%|██████▋ | 20/30 [00:12<00:06, 1.54it/s] 70%|███████ | 21/30 [00:13<00:05, 1.53it/s] 73%|███████▎ | 22/30 [00:14<00:05, 1.53it/s] 77%|███████▋ | 23/30 [00:14<00:04, 1.53it/s] 80%|████████ | 24/30 [00:15<00:03, 1.53it/s] 83%|████████▎ | 25/30 [00:16<00:03, 1.53it/s] 87%|████████▋ | 26/30 [00:16<00:02, 1.53it/s] 90%|█████████ | 27/30 [00:17<00:01, 1.52it/s] 93%|█████████▎| 28/30 [00:18<00:01, 1.52it/s] 97%|█████████▋| 29/30 [00:18<00:00, 1.52it/s] 100%|██████████| 30/30 [00:19<00:00, 1.52it/s] 100%|██████████| 30/30 [00:19<00:00, 1.54it/s] Decoding latents in cuda:0... done in 0.95s Move latents to cpu... done in 0.01s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 7.09it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.87it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.78it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.75it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.70it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.63it/s] 41%|████ | 7/17 [00:01<00:01, 6.50it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.42it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.46it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.50it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.55it/s] 71%|███████ | 12/17 [00:01<00:00, 6.57it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.51it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.46it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.45it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.50it/s] 100%|██████████| 17/17 [00:02<00:00, 6.54it/s] 100%|██████████| 17/17 [00:02<00:00, 6.56it/s] Decoding latents in cuda:0... done in 0.23s Move latents to cpu... done in 0.0s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 7.05it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.82it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.76it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.72it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.69it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.58it/s] 41%|████ | 7/17 [00:01<00:01, 6.50it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.44it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.50it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.53it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.55it/s] 71%|███████ | 12/17 [00:01<00:00, 6.55it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.52it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.47it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.50it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.51it/s] 100%|██████████| 17/17 [00:02<00:00, 6.54it/s] 100%|██████████| 17/17 [00:02<00:00, 6.56it/s] Decoding latents in cuda:0... done in 0.23s Move latents to cpu... done in 0.0s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 6.86it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.74it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.70it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.69it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.58it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.52it/s] 41%|████ | 7/17 [00:01<00:01, 6.46it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.51it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.57it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.60it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.60it/s] 71%|███████ | 12/17 [00:01<00:00, 6.52it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.45it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.46it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.52it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.57it/s] 100%|██████████| 17/17 [00:02<00:00, 6.59it/s] 100%|██████████| 17/17 [00:02<00:00, 6.57it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 7.06it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.82it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.75it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.71it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.67it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.60it/s] 41%|████ | 7/17 [00:01<00:01, 6.48it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.42it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.42it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.49it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.55it/s] 71%|███████ | 12/17 [00:01<00:00, 6.56it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.50it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.44it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.44it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.42it/s] 100%|██████████| 17/17 [00:02<00:00, 6.48it/s] 100%|██████████| 17/17 [00:02<00:00, 6.53it/s] Decoding latents in cuda:0... done in 0.23s Move latents to cpu... done in 0.0s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 6.98it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.79it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.71it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.68it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.67it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.57it/s] 41%|████ | 7/17 [00:01<00:01, 6.43it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.38it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.43it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.49it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.53it/s] 71%|███████ | 12/17 [00:01<00:00, 6.53it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.45it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.40it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.41it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.46it/s] 100%|██████████| 17/17 [00:02<00:00, 6.51it/s] 100%|██████████| 17/17 [00:02<00:00, 6.52it/s] Decoding latents in cuda:0... done in 0.23s Move latents to cpu... done in 0.0s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 6.72it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.65it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.62it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.63it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.49it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.37it/s] 41%|████ | 7/17 [00:01<00:01, 6.38it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.42it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.47it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.51it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.47it/s] 71%|███████ | 12/17 [00:01<00:00, 6.43it/s] 76%|███████▋ | 13/17 [00:02<00:00, 6.40it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.42it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.46it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.50it/s] 100%|██████████| 17/17 [00:02<00:00, 6.46it/s] 100%|██████████| 17/17 [00:02<00:00, 6.47it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s [-] ADetailer: nothing detected on image 3 with 1st settings. [-] ADetailer: nothing detected on image 3 with 2nd settings. 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 6.97it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.74it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.66it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.65it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.63it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.51it/s] 41%|████ | 7/17 [00:01<00:01, 6.40it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.36it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.42it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.47it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.49it/s] 71%|███████ | 12/17 [00:01<00:00, 6.47it/s] 76%|███████▋ | 13/17 [00:02<00:00, 6.43it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.40it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.40it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.43it/s] 100%|██████████| 17/17 [00:02<00:00, 6.48it/s] 100%|██████████| 17/17 [00:02<00:00, 6.49it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s [-] ADetailer: nothing detected on image 4 with 2nd settings. Uploading outputs... Finished.
prompt
Specify things to see in the output
(masterpiece, best quality), aging gracefully, bulky, 1 girl, high-tech metropolis. This tableau, inspired by Yoko Honda’s artistic flair, is a celebration of color, combining the organic with the digital, and the tranquility of nature with the pulsating life of an urban landscape, <lora:more_details:0.7>
negative_prompt
Specify things to not see in the output
By bad artist -neg, ng_deepnegative_v1_75t, verybadimagenegative_v1.3, watermark, text, bad hands, poorly drawn hands
num_outputs
Number of output images
4
width
Output image width
768
height
Output image height
768
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
true
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.55
detail
Enhance/diminish detail while keeping the overall style/character
0.1
brightness
Adjust brightness
0
contrast
Adjust contrast
0.2
saturation
Adjust saturation
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
179129430
input_image
Base image that the output should be generated from. This is useful when you want to add some detail to input_image. For example, if prompt is "sunglasses" and input_image has a man, there is the man wearing sunglasses in the output.
input_image_redrawing_strength
How differ the output is from input_image. Used only when input_image is given.
0.55
reference_image
Image with which the output should share identity (e.g. face of a person or type of a dog)
reference_image_strength
Strength of applying reference_image. Used only when reference_image is given.
1
reference_pose_image
Image with a reference pose
reference_pose_strength
Strength of applying reference_pose_image. Used only when reference_pose_image is given.
1
reference_depth_image
Image with a reference depth
reference_depth_strength
Strength of applying reference_depth_image. Used only when reference_depth_image is given.
1
sampler
Sampler type
DPM++ 2M Karras
samping_steps
Number of denoising steps
30
cfg_scale
Scale for classifier-free guidance
8.5
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
kl-f8-anime2_fp16.safetensors
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
more_details.safetensors
lora_2
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
lora_3
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
embedding_1
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
By bad artist -neg.pt
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
ng_deepnegative_v1_75t.pt
embedding_3
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
verybadimagenegative_v1.3.pt
disable_prompt_modification
Disable automatically adding suggested prompt modification. Built-in LoRAs and trigger words will remain.
false
https://files.tungsten.run/uploads/015ab50b3cd2437695bd05ccae863c78/00000-179129430.webp
https://files.tungsten.run/uploads/9639822c0e5b4acd9c39576299496829/00001-179129431.webp
https://files.tungsten.run/uploads/f3fe49b5f4a24ca88a5362dbe0912bdb/00002-179129432.webp
https://files.tungsten.run/uploads/3c49a514e26347ed89a166b3504267ed/00003-179129433.webp
Finished in 45.9 seconds
Preparing inputs... Processing... Loading VAE weight: models/VAE/kl-f8-anime2_fp16.safetensors Full prompt: (masterpiece, best quality), aging gracefully, bulky, 1 girl, high-tech metropolis. This tableau, inspired by Yoko Honda’s artistic flair, is a celebration of color, combining the organic with the digital, and the tranquility of nature with the pulsating life of an urban landscape, <lora:more_details:0.7>, <lora:add_detail:0.1>, <lora:contrast_slider_v10:0.2> Full negative prompt: By bad artist -neg, ng_deepnegative_v1_75t, verybadimagenegative_v1.3, watermark, text, bad hands, poorly drawn hands 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:17, 1.61it/s] 7%|▋ | 2/30 [00:01<00:17, 1.56it/s] 10%|█ | 3/30 [00:01<00:17, 1.57it/s] 13%|█▎ | 4/30 [00:02<00:16, 1.56it/s] 17%|█▋ | 5/30 [00:03<00:16, 1.56it/s] 20%|██ | 6/30 [00:03<00:15, 1.56it/s] 23%|██▎ | 7/30 [00:04<00:14, 1.55it/s] 27%|██▋ | 8/30 [00:05<00:14, 1.55it/s] 30%|███ | 9/30 [00:05<00:13, 1.55it/s] 33%|███▎ | 10/30 [00:06<00:12, 1.55it/s] 37%|███▋ | 11/30 [00:07<00:12, 1.55it/s] 40%|████ | 12/30 [00:07<00:11, 1.55it/s] 43%|████▎ | 13/30 [00:08<00:11, 1.54it/s] 47%|████▋ | 14/30 [00:09<00:10, 1.54it/s] 50%|█████ | 15/30 [00:09<00:09, 1.54it/s] 53%|█████▎ | 16/30 [00:10<00:09, 1.54it/s] 57%|█████▋ | 17/30 [00:10<00:08, 1.54it/s] 60%|██████ | 18/30 [00:11<00:07, 1.54it/s] 63%|██████▎ | 19/30 [00:12<00:07, 1.54it/s] 67%|██████▋ | 20/30 [00:12<00:06, 1.54it/s] 70%|███████ | 21/30 [00:13<00:05, 1.53it/s] 73%|███████▎ | 22/30 [00:14<00:05, 1.53it/s] 77%|███████▋ | 23/30 [00:14<00:04, 1.53it/s] 80%|████████ | 24/30 [00:15<00:03, 1.53it/s] 83%|████████▎ | 25/30 [00:16<00:03, 1.53it/s] 87%|████████▋ | 26/30 [00:16<00:02, 1.53it/s] 90%|█████████ | 27/30 [00:17<00:01, 1.52it/s] 93%|█████████▎| 28/30 [00:18<00:01, 1.52it/s] 97%|█████████▋| 29/30 [00:18<00:00, 1.52it/s] 100%|██████████| 30/30 [00:19<00:00, 1.52it/s] 100%|██████████| 30/30 [00:19<00:00, 1.54it/s] Decoding latents in cuda:0... done in 0.95s Move latents to cpu... done in 0.01s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 7.09it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.87it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.78it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.75it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.70it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.63it/s] 41%|████ | 7/17 [00:01<00:01, 6.50it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.42it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.46it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.50it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.55it/s] 71%|███████ | 12/17 [00:01<00:00, 6.57it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.51it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.46it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.45it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.50it/s] 100%|██████████| 17/17 [00:02<00:00, 6.54it/s] 100%|██████████| 17/17 [00:02<00:00, 6.56it/s] Decoding latents in cuda:0... done in 0.23s Move latents to cpu... done in 0.0s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 7.05it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.82it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.76it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.72it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.69it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.58it/s] 41%|████ | 7/17 [00:01<00:01, 6.50it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.44it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.50it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.53it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.55it/s] 71%|███████ | 12/17 [00:01<00:00, 6.55it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.52it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.47it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.50it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.51it/s] 100%|██████████| 17/17 [00:02<00:00, 6.54it/s] 100%|██████████| 17/17 [00:02<00:00, 6.56it/s] Decoding latents in cuda:0... done in 0.23s Move latents to cpu... done in 0.0s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 6.86it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.74it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.70it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.69it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.58it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.52it/s] 41%|████ | 7/17 [00:01<00:01, 6.46it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.51it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.57it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.60it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.60it/s] 71%|███████ | 12/17 [00:01<00:00, 6.52it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.45it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.46it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.52it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.57it/s] 100%|██████████| 17/17 [00:02<00:00, 6.59it/s] 100%|██████████| 17/17 [00:02<00:00, 6.57it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 7.06it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.82it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.75it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.71it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.67it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.60it/s] 41%|████ | 7/17 [00:01<00:01, 6.48it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.42it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.42it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.49it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.55it/s] 71%|███████ | 12/17 [00:01<00:00, 6.56it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.50it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.44it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.44it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.42it/s] 100%|██████████| 17/17 [00:02<00:00, 6.48it/s] 100%|██████████| 17/17 [00:02<00:00, 6.53it/s] Decoding latents in cuda:0... done in 0.23s Move latents to cpu... done in 0.0s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 6.98it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.79it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.71it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.68it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.67it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.57it/s] 41%|████ | 7/17 [00:01<00:01, 6.43it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.38it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.43it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.49it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.53it/s] 71%|███████ | 12/17 [00:01<00:00, 6.53it/s] 76%|███████▋ | 13/17 [00:01<00:00, 6.45it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.40it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.41it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.46it/s] 100%|██████████| 17/17 [00:02<00:00, 6.51it/s] 100%|██████████| 17/17 [00:02<00:00, 6.52it/s] Decoding latents in cuda:0... done in 0.23s Move latents to cpu... done in 0.0s 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 6.72it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.65it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.62it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.63it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.49it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.37it/s] 41%|████ | 7/17 [00:01<00:01, 6.38it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.42it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.47it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.51it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.47it/s] 71%|███████ | 12/17 [00:01<00:00, 6.43it/s] 76%|███████▋ | 13/17 [00:02<00:00, 6.40it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.42it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.46it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.50it/s] 100%|██████████| 17/17 [00:02<00:00, 6.46it/s] 100%|██████████| 17/17 [00:02<00:00, 6.47it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s [-] ADetailer: nothing detected on image 3 with 1st settings. [-] ADetailer: nothing detected on image 3 with 2nd settings. 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:02, 6.97it/s] 12%|█▏ | 2/17 [00:00<00:02, 6.74it/s] 18%|█▊ | 3/17 [00:00<00:02, 6.66it/s] 24%|██▎ | 4/17 [00:00<00:01, 6.65it/s] 29%|██▉ | 5/17 [00:00<00:01, 6.63it/s] 35%|███▌ | 6/17 [00:00<00:01, 6.51it/s] 41%|████ | 7/17 [00:01<00:01, 6.40it/s] 47%|████▋ | 8/17 [00:01<00:01, 6.36it/s] 53%|█████▎ | 9/17 [00:01<00:01, 6.42it/s] 59%|█████▉ | 10/17 [00:01<00:01, 6.47it/s] 65%|██████▍ | 11/17 [00:01<00:00, 6.49it/s] 71%|███████ | 12/17 [00:01<00:00, 6.47it/s] 76%|███████▋ | 13/17 [00:02<00:00, 6.43it/s] 82%|████████▏ | 14/17 [00:02<00:00, 6.40it/s] 88%|████████▊ | 15/17 [00:02<00:00, 6.40it/s] 94%|█████████▍| 16/17 [00:02<00:00, 6.43it/s] 100%|██████████| 17/17 [00:02<00:00, 6.48it/s] 100%|██████████| 17/17 [00:02<00:00, 6.49it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s [-] ADetailer: nothing detected on image 4 with 2nd settings. Uploading outputs... Finished.