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Princesses & Heroes with Acorn Is Spinning XL
acorn-is-spinning-xl:v2.0
evevalentine2017
evevalentine2017
·
Feb 13
358
Input
prompt
Specify things to see in the output
sci-fi art, award winning, ("In the golden silence of dawn, the world awakens, kissed by the soft embrace of sunlight.":1.1), woman and man, it is very Passionate, Barbarella, FOV 90 degrees, Masterpiece, Temari, extremely beautiful 18 year old
negative_prompt
Specify things to not see in the output
merged bodies, deformed legs, merged legs
num_outputs
Number of output images
3
width
Output image width
768
height
Output image height
1024
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
false
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.45
detail
Enhance/diminish detail while keeping the overall style/character
0
brightness
Adjust brightness
0
contrast
Adjust contrast
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
3991504276
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
60
cfg_scale
Scale for classifier-free guidance
7.5
clip_skip
The number of last layers of CLIP network to skip
4
vae
Select VAE
sdxl_vae.safetensors
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
!action-sdxl-V0.5.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)
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
embedding_3
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
disable_prompt_modification
Disable automatically adding suggested prompt modification. Built-in LoRAs and trigger words will remain.
false
Output
https://files.tungsten.run/uploads/2e886d1a158b498b8af72de2f6f7cd28/00000-3991504276.webp
https://files.tungsten.run/uploads/2774c55ef4f943d69bd1a85f872e96c4/00001-3991504277.webp
https://files.tungsten.run/uploads/2f87caf67e794b6a995fcf5d36a87dfe/00002-3991504278.webp
Finished in 135.2 seconds
Setting up the model... Preparing inputs... Processing... Loading VAE weight: models/VAE/sdxl_vae.safetensors Full prompt: sci-fi art, award winning, ("In the golden silence of dawn, the world awakens, kissed by the soft embrace of sunlight.":1.1), woman and man, it is very Passionate, Barbarella, FOV 90 degrees, Masterpiece, Temari, extremely beautiful 18 year old Full negative prompt: merged bodies, deformed legs, merged legs 0%| | 0/60 [00:00<?, ?it/s] 2%|▏ | 1/60 [00:00<00:56, 1.05it/s] 3%|▎ | 2/60 [00:01<00:55, 1.04it/s] 5%|▌ | 3/60 [00:02<00:55, 1.03it/s] 7%|▋ | 4/60 [00:03<00:54, 1.03it/s] 8%|▊ | 5/60 [00:04<00:53, 1.03it/s] 10%|█ | 6/60 [00:05<00:52, 1.03it/s] 12%|█▏ | 7/60 [00:06<00:51, 1.03it/s] 13%|█▎ | 8/60 [00:07<00:50, 1.03it/s] 15%|█▌ | 9/60 [00:08<00:49, 1.03it/s] 17%|█▋ | 10/60 [00:09<00:48, 1.03it/s] 18%|█▊ | 11/60 [00:10<00:47, 1.03it/s] 20%|██ | 12/60 [00:11<00:46, 1.03it/s] 22%|██▏ | 13/60 [00:12<00:45, 1.03it/s] 23%|██▎ | 14/60 [00:13<00:44, 1.03it/s] 25%|██▌ | 15/60 [00:14<00:43, 1.03it/s] 27%|██▋ | 16/60 [00:15<00:42, 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in cuda:0... done in 1.78s Move latents to cpu... done in 0.03s 0: 640x480 2 faces, 158.4ms Speed: 3.0ms preprocess, 158.4ms inference, 29.6ms postprocess per image at shape (1, 3, 640, 480) 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:12, 2.16it/s] 7%|▋ | 2/28 [00:00<00:10, 2.55it/s] 11%|█ | 3/28 [00:01<00:09, 2.72it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.82it/s] 18%|█▊ | 5/28 [00:01<00:08, 2.84it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.88it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.90it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.89it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.92it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.94it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.93it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.95it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.95it/s] 50%|█████ | 14/28 [00:04<00:04, 2.94it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.95it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.97it/s] 61%|██████ | 17/28 [00:05<00:03, 2.96it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.95it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.95it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.91it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.91it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.90it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.89it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.89it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.90it/s] 93%|█████████▎| 26/28 [00:09<00:00, 2.89it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.91it/s] 100%|██████████| 28/28 [00:09<00:00, 2.90it/s] 100%|██████████| 28/28 [00:09<00:00, 2.89it/s] Decoding latents in cuda:0... done in 0.58s Move latents to cpu... done in 0.0s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.88it/s] 7%|▋ | 2/28 [00:00<00:08, 2.91it/s] 11%|█ | 3/28 [00:01<00:08, 2.92it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.94it/s] 18%|█▊ | 5/28 [00:01<00:07, 2.93it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.93it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.94it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.94it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.93it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.94it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.95it/s] 43%|████▎ | 12/28 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[00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.89it/s] 7%|▋ | 2/28 [00:00<00:08, 2.94it/s] 11%|█ | 3/28 [00:01<00:08, 2.94it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.90it/s] 18%|█▊ | 5/28 [00:01<00:07, 2.92it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.90it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.87it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.86it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.89it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.90it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.93it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.94it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.92it/s] 50%|█████ | 14/28 [00:04<00:04, 2.94it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.95it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.91it/s] 61%|██████ | 17/28 [00:05<00:03, 2.93it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.94it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.94it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.91it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.92it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.91it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.92it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.90it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.87it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.88it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.88it/s] 100%|██████████| 28/28 [00:09<00:00, 2.89it/s] 100%|██████████| 28/28 [00:09<00:00, 2.91it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.97it/s] 7%|▋ | 2/28 [00:00<00:08, 2.92it/s] 11%|█ | 3/28 [00:01<00:08, 2.92it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.92it/s] 18%|█▊ | 5/28 [00:01<00:07, 2.90it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.92it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.93it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.93it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.95it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.93it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.91it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.92it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.94it/s] 50%|█████ | 14/28 [00:04<00:04, 2.93it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.94it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.95it/s] 61%|██████ | 17/28 [00:05<00:03, 2.87it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.89it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.91it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.92it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.94it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.94it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.92it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.95it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.96it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.97it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.97it/s] 100%|██████████| 28/28 [00:09<00:00, 2.96it/s] 100%|██████████| 28/28 [00:09<00:00, 2.93it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s 0: 640x480 2 faces, 8.0ms Speed: 2.4ms preprocess, 8.0ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 480) 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.92it/s] 7%|▋ | 2/28 [00:00<00:08, 2.91it/s] 11%|█ | 3/28 [00:01<00:08, 2.87it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.91it/s] 18%|█▊ | 5/28 [00:01<00:08, 2.65it/s] 21%|██▏ 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100%|██████████| 28/28 [00:09<00:00, 2.86it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.79it/s] 7%|▋ | 2/28 [00:00<00:09, 2.89it/s] 11%|█ | 3/28 [00:01<00:08, 2.89it/s] 14%|█▍ | 4/28 [00:01<00:09, 2.64it/s] 18%|█▊ | 5/28 [00:01<00:08, 2.64it/s] 21%|██▏ | 6/28 [00:02<00:08, 2.62it/s] 25%|██▌ | 7/28 [00:02<00:08, 2.60it/s] 29%|██▊ | 8/28 [00:03<00:07, 2.60it/s] 32%|███▏ | 9/28 [00:03<00:07, 2.64it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.73it/s] 39%|███▉ | 11/28 [00:04<00:06, 2.79it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.82it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.86it/s] 50%|█████ | 14/28 [00:05<00:04, 2.88it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.87it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.88it/s] 61%|██████ | 17/28 [00:06<00:03, 2.90it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.87it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.89it/s] 71%|███████▏ | 20/28 [00:07<00:02, 2.90it/s] 75%|███████▌ | 21/28 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Finished.
prompt
Specify things to see in the output
sci-fi art, award winning, ("In the golden silence of dawn, the world awakens, kissed by the soft embrace of sunlight.":1.1), woman and man, it is very Passionate, Barbarella, FOV 90 degrees, Masterpiece, Temari, extremely beautiful 18 year old
negative_prompt
Specify things to not see in the output
merged bodies, deformed legs, merged legs
num_outputs
Number of output images
3
width
Output image width
768
height
Output image height
1024
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
false
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.45
detail
Enhance/diminish detail while keeping the overall style/character
0
brightness
Adjust brightness
0
contrast
Adjust contrast
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
3991504276
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
60
cfg_scale
Scale for classifier-free guidance
7.5
clip_skip
The number of last layers of CLIP network to skip
4
vae
Select VAE
sdxl_vae.safetensors
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
!action-sdxl-V0.5.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)
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
embedding_3
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
disable_prompt_modification
Disable automatically adding suggested prompt modification. Built-in LoRAs and trigger words will remain.
false
https://files.tungsten.run/uploads/2e886d1a158b498b8af72de2f6f7cd28/00000-3991504276.webp
https://files.tungsten.run/uploads/2774c55ef4f943d69bd1a85f872e96c4/00001-3991504277.webp
https://files.tungsten.run/uploads/2f87caf67e794b6a995fcf5d36a87dfe/00002-3991504278.webp
Finished in 135.2 seconds
Setting up the model... Preparing inputs... Processing... Loading VAE weight: models/VAE/sdxl_vae.safetensors Full prompt: sci-fi art, award winning, ("In the golden silence of dawn, the world awakens, kissed by the soft embrace of sunlight.":1.1), woman and man, it is very Passionate, Barbarella, FOV 90 degrees, Masterpiece, Temari, extremely beautiful 18 year old Full negative prompt: merged bodies, deformed legs, merged legs 0%| | 0/60 [00:00<?, ?it/s] 2%|▏ | 1/60 [00:00<00:56, 1.05it/s] 3%|▎ | 2/60 [00:01<00:55, 1.04it/s] 5%|▌ | 3/60 [00:02<00:55, 1.03it/s] 7%|▋ | 4/60 [00:03<00:54, 1.03it/s] 8%|▊ | 5/60 [00:04<00:53, 1.03it/s] 10%|█ | 6/60 [00:05<00:52, 1.03it/s] 12%|█▏ | 7/60 [00:06<00:51, 1.03it/s] 13%|█▎ | 8/60 [00:07<00:50, 1.03it/s] 15%|█▌ | 9/60 [00:08<00:49, 1.03it/s] 17%|█▋ | 10/60 [00:09<00:48, 1.03it/s] 18%|█▊ | 11/60 [00:10<00:47, 1.03it/s] 20%|██ | 12/60 [00:11<00:46, 1.03it/s] 22%|██▏ | 13/60 [00:12<00:45, 1.03it/s] 23%|██▎ | 14/60 [00:13<00:44, 1.03it/s] 25%|██▌ | 15/60 [00:14<00:43, 1.03it/s] 27%|██▋ | 16/60 [00:15<00:42, 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in cuda:0... done in 1.78s Move latents to cpu... done in 0.03s 0: 640x480 2 faces, 158.4ms Speed: 3.0ms preprocess, 158.4ms inference, 29.6ms postprocess per image at shape (1, 3, 640, 480) 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:12, 2.16it/s] 7%|▋ | 2/28 [00:00<00:10, 2.55it/s] 11%|█ | 3/28 [00:01<00:09, 2.72it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.82it/s] 18%|█▊ | 5/28 [00:01<00:08, 2.84it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.88it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.90it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.89it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.92it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.94it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.93it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.95it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.95it/s] 50%|█████ | 14/28 [00:04<00:04, 2.94it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.95it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.97it/s] 61%|██████ | 17/28 [00:05<00:03, 2.96it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.95it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.95it/s] 71%|███████▏ | 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2.90it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.87it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.88it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.88it/s] 100%|██████████| 28/28 [00:09<00:00, 2.89it/s] 100%|██████████| 28/28 [00:09<00:00, 2.91it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.97it/s] 7%|▋ | 2/28 [00:00<00:08, 2.92it/s] 11%|█ | 3/28 [00:01<00:08, 2.92it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.92it/s] 18%|█▊ | 5/28 [00:01<00:07, 2.90it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.92it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.93it/s] 29%|██▊ | 8/28 [00:02<00:06, 2.93it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.95it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.93it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.91it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.92it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.94it/s] 50%|█████ | 14/28 [00:04<00:04, 2.93it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.94it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.95it/s] 61%|██████ | 17/28 [00:05<00:03, 2.87it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.89it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.91it/s] 71%|███████▏ | 20/28 [00:06<00:02, 2.92it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.94it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.94it/s] 82%|████████▏ | 23/28 [00:07<00:01, 2.92it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.95it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.96it/s] 93%|█████████▎| 26/28 [00:08<00:00, 2.97it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.97it/s] 100%|██████████| 28/28 [00:09<00:00, 2.96it/s] 100%|██████████| 28/28 [00:09<00:00, 2.93it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s 0: 640x480 2 faces, 8.0ms Speed: 2.4ms preprocess, 8.0ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 480) 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.92it/s] 7%|▋ | 2/28 [00:00<00:08, 2.91it/s] 11%|█ | 3/28 [00:01<00:08, 2.87it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.91it/s] 18%|█▊ | 5/28 [00:01<00:08, 2.65it/s] 21%|██▏ | 6/28 [00:02<00:08, 2.75it/s] 25%|██▌ | 7/28 [00:02<00:07, 2.81it/s] 29%|██▊ | 8/28 [00:02<00:07, 2.82it/s] 32%|███▏ | 9/28 [00:03<00:06, 2.87it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.89it/s] 39%|███▉ | 11/28 [00:03<00:05, 2.89it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.91it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.88it/s] 50%|█████ | 14/28 [00:04<00:04, 2.87it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.89it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.91it/s] 61%|██████ | 17/28 [00:05<00:03, 2.90it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.93it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.93it/s] 71%|███████▏ | 20/28 [00:07<00:02, 2.73it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.80it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.85it/s] 82%|████████▏ | 23/28 [00:08<00:01, 2.83it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.87it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.89it/s] 93%|█████████▎| 26/28 [00:09<00:00, 2.89it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.83it/s] 100%|██████████| 28/28 [00:09<00:00, 2.87it/s] 100%|██████████| 28/28 [00:09<00:00, 2.86it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.79it/s] 7%|▋ | 2/28 [00:00<00:09, 2.89it/s] 11%|█ | 3/28 [00:01<00:08, 2.89it/s] 14%|█▍ | 4/28 [00:01<00:09, 2.64it/s] 18%|█▊ | 5/28 [00:01<00:08, 2.64it/s] 21%|██▏ | 6/28 [00:02<00:08, 2.62it/s] 25%|██▌ | 7/28 [00:02<00:08, 2.60it/s] 29%|██▊ | 8/28 [00:03<00:07, 2.60it/s] 32%|███▏ | 9/28 [00:03<00:07, 2.64it/s] 36%|███▌ | 10/28 [00:03<00:06, 2.73it/s] 39%|███▉ | 11/28 [00:04<00:06, 2.79it/s] 43%|████▎ | 12/28 [00:04<00:05, 2.82it/s] 46%|████▋ | 13/28 [00:04<00:05, 2.86it/s] 50%|█████ | 14/28 [00:05<00:04, 2.88it/s] 54%|█████▎ | 15/28 [00:05<00:04, 2.87it/s] 57%|█████▋ | 16/28 [00:05<00:04, 2.88it/s] 61%|██████ | 17/28 [00:06<00:03, 2.90it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.87it/s] 68%|██████▊ | 19/28 [00:06<00:03, 2.89it/s] 71%|███████▏ | 20/28 [00:07<00:02, 2.90it/s] 75%|███████▌ | 21/28 [00:07<00:02, 2.90it/s] 79%|███████▊ | 22/28 [00:07<00:02, 2.91it/s] 82%|████████▏ | 23/28 [00:08<00:01, 2.93it/s] 86%|████████▌ | 24/28 [00:08<00:01, 2.90it/s] 89%|████████▉ | 25/28 [00:08<00:01, 2.91it/s] 93%|█████████▎| 26/28 [00:09<00:00, 2.92it/s] 96%|█████████▋| 27/28 [00:09<00:00, 2.92it/s] 100%|██████████| 28/28 [00:09<00:00, 2.92it/s] 100%|██████████| 28/28 [00:09<00:00, 2.83it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s Uploading outputs... Finished.