Long White Hair with Animesh
Input
prompt
Specify things to see in the output
((cowboy shot)), 1anime girl, solo, long white hair and red skirt posing, graphic artist magali villeneuve, black iron tiara, mark brooks detailed, a painting of white silver, art print, jinyoung shin art, gothic lighting, beautiful wood elf, (natural skin texture, hyperrealism, soft light, sharp, perfect face),
negative_prompt
Specify things to not see in the output
easynegative, ng_deepnegative_v1_75t, (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad hands, normal quality, ((monochrome)), ((grayscale)), ((watermark))
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
0.45
detail
Enhance/diminish detail while keeping the overall style/character
0
brightness
Adjust brightness
0.3
contrast
Adjust contrast
-0.6
saturation
Adjust saturation
0.6
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
119188724
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 SDE Karras
samping_steps
Number of denoising steps
50
cfg_scale
Scale for classifier-free guidance
7
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
ClearVAE_V2.3_fp16.pt
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
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
Finished in 217.2 seconds
Setting up the model...
Preparing inputs...
Processing...
Loading VAE weight: models/VAE/ClearVAE_V2.3_fp16.pt
Full prompt: ((cowboy shot)), 1anime girl, solo, long white hair and red skirt posing, graphic artist magali villeneuve, black iron tiara, mark brooks detailed, a painting of white silver, art print, jinyoung shin art, gothic lighting, beautiful wood elf, (natural skin texture, hyperrealism, soft light, sharp, perfect face),, <lora:add_brightness:0.3>, <lora:contrast_slider_v10:-0.6>, <lora:add_saturation:0.6>
Full negative prompt: easynegative, ng_deepnegative_v1_75t, (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad hands, normal quality, ((monochrome)), ((grayscale)), ((watermark))
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0: 640x640 1 face, 8.2ms
Speed: 3.4ms preprocess, 8.2ms inference, 25.2ms postprocess per image at shape (1, 3, 640, 640)
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0: 640x640 2 hands, 10.2ms
Speed: 3.2ms preprocess, 10.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)
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0: 640x640 1 face, 7.5ms
Speed: 2.7ms preprocess, 7.5ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 640)
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0: 640x640 2 faces, 7.5ms
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0: 640x640 2 hands, 7.2ms
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Decoding latents in cuda:0...
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Uploading outputs...
Finished.
prompt
Specify things to see in the output
((cowboy shot)), 1anime girl, solo, long white hair and red skirt posing, graphic artist magali villeneuve, black iron tiara, mark brooks detailed, a painting of white silver, art print, jinyoung shin art, gothic lighting, beautiful wood elf, (natural skin texture, hyperrealism, soft light, sharp, perfect face),
negative_prompt
Specify things to not see in the output
easynegative, ng_deepnegative_v1_75t, (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad hands, normal quality, ((monochrome)), ((grayscale)), ((watermark))
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
0.45
detail
Enhance/diminish detail while keeping the overall style/character
0
brightness
Adjust brightness
0.3
contrast
Adjust contrast
-0.6
saturation
Adjust saturation
0.6
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
119188724
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 SDE Karras
samping_steps
Number of denoising steps
50
cfg_scale
Scale for classifier-free guidance
7
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
ClearVAE_V2.3_fp16.pt
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
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
Finished in 217.2 seconds
Setting up the model...
Preparing inputs...
Processing...
Loading VAE weight: models/VAE/ClearVAE_V2.3_fp16.pt
Full prompt: ((cowboy shot)), 1anime girl, solo, long white hair and red skirt posing, graphic artist magali villeneuve, black iron tiara, mark brooks detailed, a painting of white silver, art print, jinyoung shin art, gothic lighting, beautiful wood elf, (natural skin texture, hyperrealism, soft light, sharp, perfect face),, <lora:add_brightness:0.3>, <lora:contrast_slider_v10:-0.6>, <lora:add_saturation:0.6>
Full negative prompt: easynegative, ng_deepnegative_v1_75t, (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad hands, normal quality, ((monochrome)), ((grayscale)), ((watermark))
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78%|███████▊ | 39/50 [01:07<00:16, 1.54s/it]
80%|████████ | 40/50 [01:09<00:15, 1.52s/it]
82%|████████▏ | 41/50 [01:11<00:14, 1.59s/it]
84%|████████▍ | 42/50 [01:12<00:12, 1.55s/it]
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88%|████████▊ | 44/50 [01:15<00:09, 1.58s/it]
90%|█████████ | 45/50 [01:17<00:07, 1.56s/it]
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94%|█████████▍| 47/50 [01:19<00:04, 1.44s/it]
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100%|██████████| 50/50 [01:22<00:00, 1.08s/it]
100%|██████████| 50/50 [01:22<00:00, 1.66s/it]
Decoding latents in cuda:0...
done in 0.99s
Move latents to cpu...
done in 0.02s
0: 640x640 1 face, 8.2ms
Speed: 3.4ms preprocess, 8.2ms inference, 25.2ms postprocess per image at shape (1, 3, 640, 640)
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39%|███▉ | 9/23 [00:03<00:05, 2.62it/s]
43%|████▎ | 10/23 [00:03<00:04, 2.78it/s]
48%|████▊ | 11/23 [00:04<00:04, 2.84it/s]
52%|█████▏ | 12/23 [00:04<00:04, 2.75it/s]
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61%|██████ | 14/23 [00:05<00:03, 2.66it/s]
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100%|██████████| 23/23 [00:08<00:00, 4.04it/s]
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Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
0: 640x640 2 hands, 10.2ms
Speed: 3.2ms preprocess, 10.2ms inference, 2.8ms postprocess per image at shape (1, 3, 640, 640)
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39%|███▉ | 9/23 [00:03<00:05, 2.75it/s]
43%|████▎ | 10/23 [00:03<00:04, 2.87it/s]
48%|████▊ | 11/23 [00:04<00:04, 2.91it/s]
52%|█████▏ | 12/23 [00:04<00:03, 2.78it/s]
57%|█████▋ | 13/23 [00:04<00:03, 2.78it/s]
61%|██████ | 14/23 [00:05<00:03, 2.62it/s]
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100%|██████████| 23/23 [00:08<00:00, 4.04it/s]
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Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
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22%|██▏ | 5/23 [00:01<00:06, 2.61it/s]
26%|██▌ | 6/23 [00:02<00:06, 2.58it/s]
30%|███ | 7/23 [00:02<00:06, 2.65it/s]
35%|███▍ | 8/23 [00:03<00:05, 2.64it/s]
39%|███▉ | 9/23 [00:03<00:05, 2.78it/s]
43%|████▎ | 10/23 [00:03<00:04, 2.87it/s]
48%|████▊ | 11/23 [00:04<00:04, 2.92it/s]
52%|█████▏ | 12/23 [00:04<00:04, 2.66it/s]
57%|█████▋ | 13/23 [00:04<00:03, 2.72it/s]
61%|██████ | 14/23 [00:05<00:03, 2.63it/s]
65%|██████▌ | 15/23 [00:05<00:02, 2.72it/s]
70%|██████▉ | 16/23 [00:05<00:02, 2.77it/s]
74%|███████▍ | 17/23 [00:06<00:02, 2.69it/s]
78%|███████▊ | 18/23 [00:06<00:01, 2.73it/s]
83%|████████▎ | 19/23 [00:07<00:01, 2.83it/s]
87%|████████▋ | 20/23 [00:07<00:01, 2.96it/s]
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100%|██████████| 23/23 [00:08<00:00, 4.04it/s]
100%|██████████| 23/23 [00:08<00:00, 2.86it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
0: 640x640 1 face, 7.5ms
Speed: 2.7ms preprocess, 7.5ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 640)
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17%|█▋ | 4/23 [00:01<00:07, 2.48it/s]
22%|██▏ | 5/23 [00:02<00:07, 2.56it/s]
26%|██▌ | 6/23 [00:02<00:06, 2.53it/s]
30%|███ | 7/23 [00:02<00:06, 2.60it/s]
35%|███▍ | 8/23 [00:03<00:05, 2.61it/s]
39%|███▉ | 9/23 [00:03<00:05, 2.76it/s]
43%|████▎ | 10/23 [00:03<00:04, 2.86it/s]
48%|████▊ | 11/23 [00:04<00:04, 2.91it/s]
52%|█████▏ | 12/23 [00:04<00:03, 2.76it/s]
57%|█████▋ | 13/23 [00:04<00:03, 2.79it/s]
61%|██████ | 14/23 [00:05<00:03, 2.65it/s]
65%|██████▌ | 15/23 [00:05<00:02, 2.73it/s]
70%|██████▉ | 16/23 [00:05<00:02, 2.76it/s]
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83%|████████▎ | 19/23 [00:07<00:01, 2.81it/s]
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100%|██████████| 23/23 [00:08<00:00, 4.02it/s]
100%|██████████| 23/23 [00:08<00:00, 2.85it/s]
Decoding latents in cuda:0...
done in 0.24s
Move latents to cpu...
done in 0.0s
0: 640x640 3 hands, 7.2ms
Speed: 2.8ms preprocess, 7.2ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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22%|██▏ | 5/23 [00:01<00:06, 2.59it/s]
26%|██▌ | 6/23 [00:02<00:06, 2.57it/s]
30%|███ | 7/23 [00:02<00:06, 2.64it/s]
35%|███▍ | 8/23 [00:03<00:05, 2.64it/s]
39%|███▉ | 9/23 [00:03<00:05, 2.80it/s]
43%|████▎ | 10/23 [00:03<00:04, 2.91it/s]
48%|████▊ | 11/23 [00:04<00:04, 2.95it/s]
52%|█████▏ | 12/23 [00:04<00:03, 2.82it/s]
57%|█████▋ | 13/23 [00:04<00:03, 2.83it/s]
61%|██████ | 14/23 [00:05<00:03, 2.68it/s]
65%|██████▌ | 15/23 [00:05<00:02, 2.75it/s]
70%|██████▉ | 16/23 [00:05<00:02, 2.79it/s]
74%|███████▍ | 17/23 [00:06<00:02, 2.69it/s]
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83%|████████▎ | 19/23 [00:06<00:01, 2.84it/s]
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100%|██████████| 23/23 [00:07<00:00, 4.08it/s]
100%|██████████| 23/23 [00:07<00:00, 2.90it/s]
Decoding latents in cuda:0...
done in 0.24s
Move latents to cpu...
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22%|██▏ | 5/23 [00:01<00:06, 2.61it/s]
26%|██▌ | 6/23 [00:02<00:06, 2.58it/s]
30%|███ | 7/23 [00:02<00:06, 2.64it/s]
35%|███▍ | 8/23 [00:03<00:05, 2.65it/s]
39%|███▉ | 9/23 [00:03<00:05, 2.78it/s]
43%|████▎ | 10/23 [00:03<00:04, 2.88it/s]
48%|████▊ | 11/23 [00:04<00:04, 2.92it/s]
52%|█████▏ | 12/23 [00:04<00:03, 2.79it/s]
57%|█████▋ | 13/23 [00:04<00:03, 2.74it/s]
61%|██████ | 14/23 [00:05<00:03, 2.64it/s]
65%|██████▌ | 15/23 [00:05<00:02, 2.70it/s]
70%|██████▉ | 16/23 [00:05<00:02, 2.75it/s]
74%|███████▍ | 17/23 [00:06<00:02, 2.67it/s]
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83%|████████▎ | 19/23 [00:07<00:01, 2.79it/s]
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100%|██████████| 23/23 [00:08<00:00, 4.01it/s]
100%|██████████| 23/23 [00:08<00:00, 2.86it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
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17%|█▋ | 4/23 [00:01<00:07, 2.49it/s]
22%|██▏ | 5/23 [00:02<00:06, 2.60it/s]
26%|██▌ | 6/23 [00:02<00:06, 2.51it/s]
30%|███ | 7/23 [00:02<00:06, 2.60it/s]
35%|███▍ | 8/23 [00:03<00:05, 2.59it/s]
39%|███▉ | 9/23 [00:03<00:05, 2.73it/s]
43%|████▎ | 10/23 [00:03<00:04, 2.85it/s]
48%|████▊ | 11/23 [00:04<00:04, 2.87it/s]
52%|█████▏ | 12/23 [00:04<00:04, 2.64it/s]
57%|█████▋ | 13/23 [00:04<00:03, 2.64it/s]
61%|██████ | 14/23 [00:05<00:03, 2.53it/s]
65%|██████▌ | 15/23 [00:05<00:03, 2.65it/s]
70%|██████▉ | 16/23 [00:06<00:02, 2.73it/s]
74%|███████▍ | 17/23 [00:06<00:02, 2.54it/s]
78%|███████▊ | 18/23 [00:06<00:01, 2.63it/s]
83%|████████▎ | 19/23 [00:07<00:01, 2.74it/s]
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96%|█████████▌| 22/23 [00:08<00:00, 3.41it/s]
100%|██████████| 23/23 [00:08<00:00, 4.01it/s]
100%|██████████| 23/23 [00:08<00:00, 2.81it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
0: 640x640 2 faces, 7.5ms
Speed: 2.6ms preprocess, 7.5ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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26%|██▌ | 6/23 [00:02<00:06, 2.45it/s]
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39%|███▉ | 9/23 [00:03<00:05, 2.75it/s]
43%|████▎ | 10/23 [00:03<00:04, 2.87it/s]
48%|████▊ | 11/23 [00:04<00:04, 2.93it/s]
52%|█████▏ | 12/23 [00:04<00:03, 2.78it/s]
57%|█████▋ | 13/23 [00:04<00:03, 2.77it/s]
61%|██████ | 14/23 [00:05<00:03, 2.60it/s]
65%|██████▌ | 15/23 [00:05<00:02, 2.71it/s]
70%|██████▉ | 16/23 [00:05<00:02, 2.77it/s]
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100%|██████████| 23/23 [00:08<00:00, 4.02it/s]
100%|██████████| 23/23 [00:08<00:00, 2.86it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
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39%|███▉ | 9/23 [00:03<00:05, 2.72it/s]
43%|████▎ | 10/23 [00:03<00:04, 2.84it/s]
48%|████▊ | 11/23 [00:04<00:04, 2.90it/s]
52%|█████▏ | 12/23 [00:04<00:03, 2.79it/s]
57%|█████▋ | 13/23 [00:04<00:03, 2.81it/s]
61%|██████ | 14/23 [00:05<00:03, 2.69it/s]
65%|██████▌ | 15/23 [00:05<00:02, 2.76it/s]
70%|██████▉ | 16/23 [00:06<00:02, 2.79it/s]
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83%|████████▎ | 19/23 [00:07<00:01, 2.75it/s]
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100%|██████████| 23/23 [00:08<00:00, 4.01it/s]
100%|██████████| 23/23 [00:08<00:00, 2.82it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
0: 640x640 1 hand, 7.2ms
Speed: 2.8ms preprocess, 7.2ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
0: 640x640 2 faces, 7.6ms
Speed: 2.8ms preprocess, 7.6ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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Decoding latents in cuda:0...
done in 0.24s
Move latents to cpu...
done in 0.0s
0: 640x640 2 hands, 7.2ms
Speed: 3.5ms preprocess, 7.2ms inference, 1.7ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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Move latents to cpu...
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Decoding latents in cuda:0...
done in 0.24s
Move latents to cpu...
done in 0.0s
Uploading outputs...
Finished.