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Japanese Monk with AnReal SpiceMix
anreal-spicemix:v3.0
evevalentine2017
evevalentine2017
·
Apr 11
136
Input
prompt
Specify things to see in the output
raw photo, old japanese monk, serene temple garden, (traditional robe:0.7), weathered hands in prayer, peaceful gaze, ancient wisdom, cherry blossoms in background, spiritual tranquility, soft shading
negative_prompt
Specify things to not see in the output
render, cgi, drawing, cartoon, painting, illustration, bad quality, low res, (deformed, distorted, disfigured:1.25)
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
contrast
Adjust contrast
0
saturation
Adjust saturation
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
1342285338
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
36
cfg_scale
Scale for classifier-free guidance
6.5
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
None
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
https://files.tungsten.run/uploads/2a174283d65a4ca8940220a6c7f2c09e/00000-1342285338.webp
https://files.tungsten.run/uploads/1720b93dad5b4d33ba636bef6f1af97e/00001-1342285339.webp
https://files.tungsten.run/uploads/4bc71aa797ba478ab2959d34a94f5474/00002-1342285340.webp
https://files.tungsten.run/uploads/9ab99c37d52c45e2803b3dd0f8cbd731/00003-1342285341.webp
Finished in 151.2 seconds
Setting up the model... Preparing inputs... Processing... Full prompt: raw photo, old japanese monk, serene temple garden, (traditional robe:0.7), weathered hands in prayer, peaceful gaze, ancient wisdom, cherry blossoms in background, spiritual tranquility, soft shading Full negative prompt: render, cgi, drawing, cartoon, painting, illustration, bad quality, low res, (deformed, distorted, disfigured:1.25) 0%| | 0/36 [00:00<?, ?it/s] 3%|▎ | 1/36 [00:01<00:45, 1.30s/it] 6%|▌ | 2/36 [00:03<00:54, 1.60s/it] 8%|▊ | 3/36 [00:04<00:54, 1.65s/it] 11%|█ | 4/36 [00:06<00:53, 1.68s/it] 14%|█▍ | 5/36 [00:08<00:54, 1.74s/it] 17%|█▋ | 6/36 [00:10<00:55, 1.84s/it] 19%|█▉ | 7/36 [00:12<00:53, 1.86s/it] 22%|██▏ | 8/36 [00:14<00:51, 1.85s/it] 25%|██▌ | 9/36 [00:15<00:48, 1.81s/it] 28%|██▊ | 10/36 [00:17<00:45, 1.75s/it] 31%|███ | 11/36 [00:19<00:45, 1.82s/it] 33%|███▎ | 12/36 [00:21<00:44, 1.84s/it] 36%|███▌ | 13/36 [00:23<00:42, 1.83s/it] 39%|███▉ | 14/36 [00:24<00:39, 1.78s/it] 42%|████▏ | 15/36 [00:26<00:37, 1.79s/it] 44%|████▍ | 16/36 [00:28<00:36, 1.80s/it] 47%|████▋ | 17/36 [00:30<00:33, 1.75s/it] 50%|█████ | 18/36 [00:32<00:33, 1.86s/it] 53%|█████▎ | 19/36 [00:34<00:31, 1.86s/it] 56%|█████▌ | 20/36 [00:35<00:29, 1.84s/it] 58%|█████▊ | 21/36 [00:37<00:27, 1.80s/it] 61%|██████ | 22/36 [00:39<00:24, 1.79s/it] 64%|██████▍ | 23/36 [00:41<00:22, 1.75s/it] 67%|██████▋ | 24/36 [00:42<00:20, 1.74s/it] 69%|██████▉ | 25/36 [00:44<00:18, 1.71s/it] 72%|███████▏ | 26/36 [00:46<00:16, 1.69s/it] 75%|███████▌ | 27/36 [00:47<00:15, 1.71s/it] 78%|███████▊ | 28/36 [00:49<00:13, 1.69s/it] 81%|████████ | 29/36 [00:51<00:11, 1.68s/it] 83%|████████▎ | 30/36 [00:52<00:09, 1.61s/it] 86%|████████▌ | 31/36 [00:54<00:08, 1.62s/it] 89%|████████▉ | 32/36 [00:55<00:06, 1.62s/it] 92%|█████████▏| 33/36 [00:57<00:04, 1.58s/it] 94%|█████████▍| 34/36 [00:58<00:03, 1.53s/it] 97%|█████████▋| 35/36 [00:59<00:01, 1.34s/it] 100%|██████████| 36/36 [01:00<00:00, 1.14s/it] 100%|██████████| 36/36 [01:00<00:00, 1.67s/it] Decoding latents in cuda:0... done in 1.01s Move latents to cpu... done in 0.03s 0: 640x640 1 face, 7.9ms Speed: 5.3ms preprocess, 7.9ms inference, 26.1ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:09, 1.62it/s] 12%|█▏ | 2/17 [00:01<00:07, 2.06it/s] 18%|█▊ | 3/17 [00:01<00:06, 2.28it/s] 24%|██▎ | 4/17 [00:01<00:05, 2.42it/s] 29%|██▉ | 5/17 [00:02<00:04, 2.45it/s] 35%|███▌ | 6/17 [00:02<00:04, 2.53it/s] 41%|████ | 7/17 [00:02<00:03, 2.60it/s] 47%|████▋ | 8/17 [00:03<00:03, 2.53it/s] 53%|█████▎ | 9/17 [00:03<00:03, 2.55it/s] 59%|█████▉ | 10/17 [00:04<00:02, 2.56it/s] 65%|██████▍ | 11/17 [00:04<00:02, 2.69it/s] 71%|███████ | 12/17 [00:04<00:01, 2.68it/s] 76%|███████▋ | 13/17 [00:05<00:01, 2.69it/s] 82%|████████▏ | 14/17 [00:05<00:01, 2.75it/s] 88%|████████▊ | 15/17 [00:05<00:00, 2.83it/s] 94%|█████████▍| 16/17 [00:06<00:00, 3.25it/s] 100%|██████████| 17/17 [00:06<00:00, 3.84it/s] 100%|██████████| 17/17 [00:06<00:00, 2.75it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s
prompt
Specify things to see in the output
raw photo, old japanese monk, serene temple garden, (traditional robe:0.7), weathered hands in prayer, peaceful gaze, ancient wisdom, cherry blossoms in background, spiritual tranquility, soft shading
negative_prompt
Specify things to not see in the output
render, cgi, drawing, cartoon, painting, illustration, bad quality, low res, (deformed, distorted, disfigured:1.25)
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
contrast
Adjust contrast
0
saturation
Adjust saturation
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
1342285338
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
36
cfg_scale
Scale for classifier-free guidance
6.5
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
None
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
https://files.tungsten.run/uploads/2a174283d65a4ca8940220a6c7f2c09e/00000-1342285338.webp
https://files.tungsten.run/uploads/1720b93dad5b4d33ba636bef6f1af97e/00001-1342285339.webp
https://files.tungsten.run/uploads/4bc71aa797ba478ab2959d34a94f5474/00002-1342285340.webp
https://files.tungsten.run/uploads/9ab99c37d52c45e2803b3dd0f8cbd731/00003-1342285341.webp
Finished in 151.2 seconds
Setting up the model... Preparing inputs... Processing... Full prompt: raw photo, old japanese monk, serene temple garden, (traditional robe:0.7), weathered hands in prayer, peaceful gaze, ancient wisdom, cherry blossoms in background, spiritual tranquility, soft shading Full negative prompt: render, cgi, drawing, cartoon, painting, illustration, bad quality, low res, (deformed, distorted, disfigured:1.25) 0%| | 0/36 [00:00<?, ?it/s] 3%|▎ | 1/36 [00:01<00:45, 1.30s/it] 6%|▌ | 2/36 [00:03<00:54, 1.60s/it] 8%|▊ | 3/36 [00:04<00:54, 1.65s/it] 11%|█ | 4/36 [00:06<00:53, 1.68s/it] 14%|█▍ | 5/36 [00:08<00:54, 1.74s/it] 17%|█▋ | 6/36 [00:10<00:55, 1.84s/it] 19%|█▉ | 7/36 [00:12<00:53, 1.86s/it] 22%|██▏ | 8/36 [00:14<00:51, 1.85s/it] 25%|██▌ | 9/36 [00:15<00:48, 1.81s/it] 28%|██▊ | 10/36 [00:17<00:45, 1.75s/it] 31%|███ | 11/36 [00:19<00:45, 1.82s/it] 33%|███▎ | 12/36 [00:21<00:44, 1.84s/it] 36%|███▌ | 13/36 [00:23<00:42, 1.83s/it] 39%|███▉ | 14/36 [00:24<00:39, 1.78s/it] 42%|████▏ | 15/36 [00:26<00:37, 1.79s/it] 44%|████▍ | 16/36 [00:28<00:36, 1.80s/it] 47%|████▋ | 17/36 [00:30<00:33, 1.75s/it] 50%|█████ | 18/36 [00:32<00:33, 1.86s/it] 53%|█████▎ | 19/36 [00:34<00:31, 1.86s/it] 56%|█████▌ | 20/36 [00:35<00:29, 1.84s/it] 58%|█████▊ | 21/36 [00:37<00:27, 1.80s/it] 61%|██████ | 22/36 [00:39<00:24, 1.79s/it] 64%|██████▍ | 23/36 [00:41<00:22, 1.75s/it] 67%|██████▋ | 24/36 [00:42<00:20, 1.74s/it] 69%|██████▉ | 25/36 [00:44<00:18, 1.71s/it] 72%|███████▏ | 26/36 [00:46<00:16, 1.69s/it] 75%|███████▌ | 27/36 [00:47<00:15, 1.71s/it] 78%|███████▊ | 28/36 [00:49<00:13, 1.69s/it] 81%|████████ | 29/36 [00:51<00:11, 1.68s/it] 83%|████████▎ | 30/36 [00:52<00:09, 1.61s/it] 86%|████████▌ | 31/36 [00:54<00:08, 1.62s/it] 89%|████████▉ | 32/36 [00:55<00:06, 1.62s/it] 92%|█████████▏| 33/36 [00:57<00:04, 1.58s/it] 94%|█████████▍| 34/36 [00:58<00:03, 1.53s/it] 97%|█████████▋| 35/36 [00:59<00:01, 1.34s/it] 100%|██████████| 36/36 [01:00<00:00, 1.14s/it] 100%|██████████| 36/36 [01:00<00:00, 1.67s/it] Decoding latents in cuda:0... done in 1.01s Move latents to cpu... done in 0.03s 0: 640x640 1 face, 7.9ms Speed: 5.3ms preprocess, 7.9ms inference, 26.1ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:09, 1.62it/s] 12%|█▏ | 2/17 [00:01<00:07, 2.06it/s] 18%|█▊ | 3/17 [00:01<00:06, 2.28it/s] 24%|██▎ | 4/17 [00:01<00:05, 2.42it/s] 29%|██▉ | 5/17 [00:02<00:04, 2.45it/s] 35%|███▌ | 6/17 [00:02<00:04, 2.53it/s] 41%|████ | 7/17 [00:02<00:03, 2.60it/s] 47%|████▋ | 8/17 [00:03<00:03, 2.53it/s] 53%|█████▎ | 9/17 [00:03<00:03, 2.55it/s] 59%|█████▉ | 10/17 [00:04<00:02, 2.56it/s] 65%|██████▍ | 11/17 [00:04<00:02, 2.69it/s] 71%|███████ | 12/17 [00:04<00:01, 2.68it/s] 76%|███████▋ | 13/17 [00:05<00:01, 2.69it/s] 82%|████████▏ | 14/17 [00:05<00:01, 2.75it/s] 88%|████████▊ | 15/17 [00:05<00:00, 2.83it/s] 94%|█████████▍| 16/17 [00:06<00:00, 3.25it/s] 100%|██████████| 17/17 [00:06<00:00, 3.84it/s] 100%|██████████| 17/17 [00:06<00:00, 2.75it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s