Cute Christmas Outfits with Realism
Input
prompt
Specify things to see in the output
(8k, RAW photo, best quality, masterpiece:1.2), ultra detailed,(photo realistic:1.4), (full body shot:1.2), staring at you, so hot, very cute, making a hot pose for the camera, so cute, ((Christmas outfit)), santa hat, so charming, she is in a bedroom, fireplace, hands on hips, <lora:add_detail:0.8>, <lora:FaceBeauty_qinglong_V3:1.5>
negative_prompt
Specify things to not see in the output
((brown eyes:2)), ((portrait:2)), ((focus on face:2)), bad-picture-chill-32v, ng_deepnegative_v1_75t, badhandv4, (worst quality:2), (low quality:2), (normal quality:2), (lowres:2), (bad anatomy:2), (bad hands:2), (watermark:2), (mole:1.5), (freckles:1.5)
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
brightness
Adjust brightness
0
contrast
Adjust contrast
0
saturation
Adjust saturation
-1.09
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
3614532514
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
30
cfg_scale
Scale for classifier-free guidance
4
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
blessed2_fp16.safetensors
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 184.8 seconds
Setting up the model...
Processing...
Loading VAE weight: models/VAE/blessed2_fp16.safetensors
Full prompt: (8k, RAW photo, best quality, masterpiece:1.2), ultra detailed,(photo realistic:1.4), (full body shot:1.2), staring at you, so hot, very cute, making a hot pose for the camera, so cute, ((Christmas outfit)), santa hat, so charming, she is in a bedroom, fireplace, hands on hips, <lora:FaceBeauty_qinglong_V3:1.5>, <lora:add_saturation:-1.09>
Full negative prompt: ((brown eyes:2)), ((portrait:2)), ((focus on face:2)), bad-picture-chill-32v, ng_deepnegative_v1_75t, badhandv4, (worst quality:2), (low quality:2), (normal quality:2), (lowres:2), (bad anatomy:2), (bad hands:2), (watermark:2), (mole:1.5), (freckles:1.5)
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0: 640x640 1 face, 8.1ms
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0: 640x640 4 hands, 8.7ms
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0: 640x640 1 face, 7.8ms
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Uploading outputs...
Finished.
prompt
Specify things to see in the output
(8k, RAW photo, best quality, masterpiece:1.2), ultra detailed,(photo realistic:1.4), (full body shot:1.2), staring at you, so hot, very cute, making a hot pose for the camera, so cute, ((Christmas outfit)), santa hat, so charming, she is in a bedroom, fireplace, hands on hips, <lora:add_detail:0.8>, <lora:FaceBeauty_qinglong_V3:1.5>
negative_prompt
Specify things to not see in the output
((brown eyes:2)), ((portrait:2)), ((focus on face:2)), bad-picture-chill-32v, ng_deepnegative_v1_75t, badhandv4, (worst quality:2), (low quality:2), (normal quality:2), (lowres:2), (bad anatomy:2), (bad hands:2), (watermark:2), (mole:1.5), (freckles:1.5)
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
brightness
Adjust brightness
0
contrast
Adjust contrast
0
saturation
Adjust saturation
-1.09
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
3614532514
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
30
cfg_scale
Scale for classifier-free guidance
4
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
blessed2_fp16.safetensors
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 184.8 seconds
Setting up the model...
Processing...
Loading VAE weight: models/VAE/blessed2_fp16.safetensors
Full prompt: (8k, RAW photo, best quality, masterpiece:1.2), ultra detailed,(photo realistic:1.4), (full body shot:1.2), staring at you, so hot, very cute, making a hot pose for the camera, so cute, ((Christmas outfit)), santa hat, so charming, she is in a bedroom, fireplace, hands on hips, <lora:FaceBeauty_qinglong_V3:1.5>, <lora:add_saturation:-1.09>
Full negative prompt: ((brown eyes:2)), ((portrait:2)), ((focus on face:2)), bad-picture-chill-32v, ng_deepnegative_v1_75t, badhandv4, (worst quality:2), (low quality:2), (normal quality:2), (lowres:2), (bad anatomy:2), (bad hands:2), (watermark:2), (mole:1.5), (freckles:1.5)
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0: 640x640 1 face, 8.1ms
Speed: 5.4ms preprocess, 8.1ms inference, 29.6ms postprocess per image at shape (1, 3, 640, 640)
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0: 640x640 2 hands, 7.9ms
Speed: 3.1ms preprocess, 7.9ms inference, 2.6ms postprocess per image at shape (1, 3, 640, 640)
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59%|█████▉ | 10/17 [00:03<00:02, 2.62it/s]
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71%|███████ | 12/17 [00:04<00:01, 2.70it/s]
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82%|████████▏ | 14/17 [00:05<00:01, 2.62it/s]
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100%|██████████| 17/17 [00:06<00:00, 3.60it/s]
100%|██████████| 17/17 [00:06<00:00, 2.76it/s]
Decoding latents in cuda:0...
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Move latents to cpu...
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59%|█████▉ | 10/17 [00:03<00:02, 2.63it/s]
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71%|███████ | 12/17 [00:04<00:01, 2.72it/s]
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82%|████████▏ | 14/17 [00:05<00:01, 2.67it/s]
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100%|██████████| 17/17 [00:06<00:00, 3.67it/s]
100%|██████████| 17/17 [00:06<00:00, 2.79it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
0: 640x640 2 faces, 7.7ms
Speed: 3.1ms preprocess, 7.7ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)
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59%|█████▉ | 10/17 [00:03<00:02, 2.69it/s]
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100%|██████████| 17/17 [00:05<00:00, 3.69it/s]
100%|██████████| 17/17 [00:05<00:00, 2.83it/s]
Decoding latents in cuda:0...
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Move latents to cpu...
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41%|████ | 7/17 [00:02<00:03, 2.51it/s]
47%|████▋ | 8/17 [00:03<00:03, 2.56it/s]
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59%|█████▉ | 10/17 [00:03<00:02, 2.66it/s]
65%|██████▍ | 11/17 [00:04<00:02, 2.76it/s]
71%|███████ | 12/17 [00:04<00:01, 2.74it/s]
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82%|████████▏ | 14/17 [00:05<00:01, 2.68it/s]
88%|████████▊ | 15/17 [00:05<00:00, 2.70it/s]
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100%|██████████| 17/17 [00:06<00:00, 3.68it/s]
100%|██████████| 17/17 [00:06<00:00, 2.82it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
0: 640x640 4 hands, 7.5ms
Speed: 3.1ms preprocess, 7.5ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640)
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47%|████▋ | 8/17 [00:03<00:03, 2.53it/s]
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59%|█████▉ | 10/17 [00:03<00:02, 2.67it/s]
65%|██████▍ | 11/17 [00:04<00:02, 2.76it/s]
71%|███████ | 12/17 [00:04<00:01, 2.73it/s]
76%|███████▋ | 13/17 [00:04<00:01, 2.62it/s]
82%|████████▏ | 14/17 [00:05<00:01, 2.62it/s]
88%|████████▊ | 15/17 [00:05<00:00, 2.64it/s]
94%|█████████▍| 16/17 [00:05<00:00, 2.99it/s]
100%|██████████| 17/17 [00:06<00:00, 3.61it/s]
100%|██████████| 17/17 [00:06<00:00, 2.78it/s]
Decoding latents in cuda:0...
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Move latents to cpu...
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59%|█████▉ | 10/17 [00:03<00:02, 2.65it/s]
65%|██████▍ | 11/17 [00:04<00:02, 2.73it/s]
71%|███████ | 12/17 [00:04<00:01, 2.68it/s]
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82%|████████▏ | 14/17 [00:05<00:01, 2.66it/s]
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94%|█████████▍| 16/17 [00:05<00:00, 3.07it/s]
100%|██████████| 17/17 [00:06<00:00, 3.69it/s]
100%|██████████| 17/17 [00:06<00:00, 2.79it/s]
Decoding latents in cuda:0...
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Move latents to cpu...
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35%|███▌ | 6/17 [00:02<00:04, 2.54it/s]
41%|████ | 7/17 [00:02<00:03, 2.51it/s]
47%|████▋ | 8/17 [00:03<00:03, 2.55it/s]
53%|█████▎ | 9/17 [00:03<00:03, 2.53it/s]
59%|█████▉ | 10/17 [00:03<00:02, 2.68it/s]
65%|██████▍ | 11/17 [00:04<00:02, 2.73it/s]
71%|███████ | 12/17 [00:04<00:01, 2.72it/s]
76%|███████▋ | 13/17 [00:04<00:01, 2.65it/s]
82%|████████▏ | 14/17 [00:05<00:01, 2.67it/s]
88%|████████▊ | 15/17 [00:05<00:00, 2.69it/s]
94%|█████████▍| 16/17 [00:05<00:00, 3.09it/s]
100%|██████████| 17/17 [00:06<00:00, 3.69it/s]
100%|██████████| 17/17 [00:06<00:00, 2.80it/s]
Decoding latents in cuda:0...
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Move latents to cpu...
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0%| | 0/17 [00:00<?, ?it/s]
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12%|█▏ | 2/17 [00:00<00:05, 2.50it/s]
18%|█▊ | 3/17 [00:01<00:05, 2.61it/s]
24%|██▎ | 4/17 [00:01<00:05, 2.57it/s]
29%|██▉ | 5/17 [00:01<00:04, 2.54it/s]
35%|███▌ | 6/17 [00:02<00:04, 2.56it/s]
41%|████ | 7/17 [00:02<00:04, 2.49it/s]
47%|████▋ | 8/17 [00:03<00:03, 2.53it/s]
53%|█████▎ | 9/17 [00:03<00:03, 2.49it/s]
59%|█████▉ | 10/17 [00:03<00:02, 2.64it/s]
65%|██████▍ | 11/17 [00:04<00:02, 2.72it/s]
71%|███████ | 12/17 [00:04<00:01, 2.66it/s]
76%|███████▋ | 13/17 [00:05<00:01, 2.58it/s]
82%|████████▏ | 14/17 [00:05<00:01, 2.61it/s]
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94%|█████████▍| 16/17 [00:06<00:00, 3.02it/s]
100%|██████████| 17/17 [00:06<00:00, 3.64it/s]
100%|██████████| 17/17 [00:06<00:00, 2.76it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
0: 640x640 2 faces, 7.7ms
Speed: 3.3ms preprocess, 7.7ms inference, 2.3ms postprocess per image at shape (1, 3, 640, 640)
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35%|███▌ | 6/17 [00:02<00:04, 2.54it/s]
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47%|████▋ | 8/17 [00:03<00:03, 2.54it/s]
53%|█████▎ | 9/17 [00:03<00:03, 2.47it/s]
59%|█████▉ | 10/17 [00:03<00:02, 2.62it/s]
65%|██████▍ | 11/17 [00:04<00:02, 2.70it/s]
71%|███████ | 12/17 [00:04<00:01, 2.67it/s]
76%|███████▋ | 13/17 [00:05<00:01, 2.62it/s]
82%|████████▏ | 14/17 [00:05<00:01, 2.65it/s]
88%|████████▊ | 15/17 [00:05<00:00, 2.66it/s]
94%|█████████▍| 16/17 [00:05<00:00, 3.05it/s]
100%|██████████| 17/17 [00:06<00:00, 3.70it/s]
100%|██████████| 17/17 [00:06<00:00, 2.78it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
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0%| | 0/17 [00:00<?, ?it/s]
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12%|█▏ | 2/17 [00:00<00:05, 2.64it/s]
18%|█▊ | 3/17 [00:01<00:05, 2.66it/s]
24%|██▎ | 4/17 [00:01<00:04, 2.64it/s]
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35%|███▌ | 6/17 [00:02<00:04, 2.57it/s]
41%|████ | 7/17 [00:02<00:03, 2.53it/s]
47%|████▋ | 8/17 [00:03<00:03, 2.53it/s]
53%|█████▎ | 9/17 [00:03<00:03, 2.51it/s]
59%|█████▉ | 10/17 [00:03<00:02, 2.66it/s]
65%|██████▍ | 11/17 [00:04<00:02, 2.71it/s]
71%|███████ | 12/17 [00:04<00:01, 2.70it/s]
76%|███████▋ | 13/17 [00:04<00:01, 2.64it/s]
82%|████████▏ | 14/17 [00:05<00:01, 2.66it/s]
88%|████████▊ | 15/17 [00:05<00:00, 2.69it/s]
94%|█████████▍| 16/17 [00:05<00:00, 3.08it/s]
100%|██████████| 17/17 [00:06<00:00, 3.67it/s]
100%|██████████| 17/17 [00:06<00:00, 2.80it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
0: 640x640 4 hands, 8.7ms
Speed: 3.3ms preprocess, 8.7ms inference, 2.4ms postprocess per image at shape (1, 3, 640, 640)
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35%|███▌ | 6/17 [00:02<00:04, 2.52it/s]
41%|████ | 7/17 [00:02<00:04, 2.49it/s]
47%|████▋ | 8/17 [00:03<00:03, 2.54it/s]
53%|█████▎ | 9/17 [00:03<00:03, 2.50it/s]
59%|█████▉ | 10/17 [00:03<00:02, 2.64it/s]
65%|██████▍ | 11/17 [00:04<00:02, 2.72it/s]
71%|███████ | 12/17 [00:04<00:01, 2.71it/s]
76%|███████▋ | 13/17 [00:05<00:01, 2.66it/s]
82%|████████▏ | 14/17 [00:05<00:01, 2.68it/s]
88%|████████▊ | 15/17 [00:05<00:00, 2.71it/s]
94%|█████████▍| 16/17 [00:05<00:00, 3.10it/s]
100%|██████████| 17/17 [00:06<00:00, 3.73it/s]
100%|██████████| 17/17 [00:06<00:00, 2.79it/s]
Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
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59%|█████▉ | 10/17 [00:03<00:02, 2.69it/s]
65%|██████▍ | 11/17 [00:04<00:02, 2.77it/s]
71%|███████ | 12/17 [00:04<00:01, 2.75it/s]
76%|███████▋ | 13/17 [00:04<00:01, 2.68it/s]
82%|████████▏ | 14/17 [00:05<00:01, 2.70it/s]
88%|████████▊ | 15/17 [00:05<00:00, 2.67it/s]
94%|█████████▍| 16/17 [00:05<00:00, 3.06it/s]
100%|██████████| 17/17 [00:06<00:00, 3.69it/s]
100%|██████████| 17/17 [00:06<00:00, 2.82it/s]
Decoding latents in cuda:0...
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Move latents to cpu...
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0%| | 0/17 [00:00<?, ?it/s]
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12%|█▏ | 2/17 [00:00<00:05, 2.61it/s]
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24%|██▎ | 4/17 [00:01<00:04, 2.61it/s]
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41%|████ | 7/17 [00:02<00:04, 2.50it/s]
47%|████▋ | 8/17 [00:03<00:03, 2.52it/s]
53%|█████▎ | 9/17 [00:03<00:03, 2.51it/s]
59%|█████▉ | 10/17 [00:03<00:02, 2.66it/s]
65%|██████▍ | 11/17 [00:04<00:02, 2.74it/s]
71%|███████ | 12/17 [00:04<00:01, 2.74it/s]
76%|███████▋ | 13/17 [00:04<00:01, 2.65it/s]
82%|████████▏ | 14/17 [00:05<00:01, 2.65it/s]
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100%|██████████| 17/17 [00:06<00:00, 3.67it/s]
100%|██████████| 17/17 [00:06<00:00, 2.79it/s]
Decoding latents in cuda:0...
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Move latents to cpu...
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Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
0: 640x640 1 face, 7.8ms
Speed: 3.1ms preprocess, 7.8ms inference, 2.3ms 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 hands, 7.9ms
Speed: 3.1ms preprocess, 7.9ms inference, 1.9ms 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...
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Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
done in 0.0s
Uploading outputs...
Finished.