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Cool Tattoos with Mat Dreams Turbo XL
mat-dreams-turbo-xl:v1.0
evevalentine2017
evevalentine2017
·
Jan 23
359
Input
prompt
Specify things to see in the output
painting, intricate details, medium shot of a Sensual Magnificent petite Art Nouveau (Female:1.3), furious, Vivacious pose, she has a Decora Navy Blue Cellphone, Invigorating Tattoos, city street and flora, soft focus, Fine art, Angry, Warm lighting, 800mm lens, two colors, artstation, trending on artstation, pixabay, ornate
negative_prompt
Specify things to not see in the output
bad quality, bad anatomy, low quality, worst quality, blury, grainey, old, badly drawn hands
num_outputs
Number of output images
3
width
Output image width
1024
height
Output image height
1024
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
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
1989517264
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
Euler a
samping_steps
Number of denoising steps
8
cfg_scale
Scale for classifier-free guidance
2.5
clip_skip
The number of last layers of CLIP network to skip
1
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/13d308184c7d41cfb631f4f92453ce90/00000-1989517264.webp
https://files.tungsten.run/uploads/adbccbc7da0245f9b17d2cc480a7bf70/00001-1989517265.webp
https://files.tungsten.run/uploads/98573c43a28240a69c6c6275d6b5b095/00002-1989517266.webp
Finished in 35.6 seconds
Preparing inputs... Processing... Full prompt: painting, intricate details, medium shot of a Sensual Magnificent petite Art Nouveau (Female:1.3), furious, Vivacious pose, she has a Decora Navy Blue Cellphone, Invigorating Tattoos, city street and flora, soft focus, Fine art, Angry, Warm lighting, 800mm lens, two colors, artstation, trending on artstation, pixabay, ornate Full negative prompt: bad quality, bad anatomy, low quality, worst quality, blury, grainey, old, badly drawn hands 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:01<00:09, 1.37s/it] 25%|██▌ | 2/8 [00:02<00:08, 1.37s/it] 38%|███▊ | 3/8 [00:04<00:06, 1.38s/it] 50%|█████ | 4/8 [00:05<00:05, 1.38s/it] 62%|██████▎ | 5/8 [00:06<00:04, 1.38s/it] 75%|███████▌ | 6/8 [00:08<00:02, 1.38s/it] 88%|████████▊ | 7/8 [00:09<00:01, 1.39s/it] 100%|██████████| 8/8 [00:11<00:00, 1.38s/it] 100%|██████████| 8/8 [00:11<00:00, 1.38s/it] Decoding latents in cuda:0... done in 2.34s Move latents to cpu... done in 0.01s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.51it/s] 50%|█████ | 2/4 [00:00<00:00, 2.50it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.40it/s] 100%|██████████| 4/4 [00:01<00:00, 2.44it/s] 100%|██████████| 4/4 [00:01<00:00, 2.45it/s] Decoding latents in cuda:0... done in 0.79s Move latents to cpu... done in 0.0s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.52it/s] 50%|█████ | 2/4 [00:00<00:00, 2.52it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.43it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] 100%|██████████| 4/4 [00:01<00:00, 2.47it/s] Decoding latents in cuda:0... done in 0.77s Move latents to cpu... done in 0.0s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.53it/s] 50%|█████ | 2/4 [00:00<00:00, 2.52it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.42it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] 100%|██████████| 4/4 [00:01<00:00, 2.47it/s] Decoding latents in cuda:0... done in 0.78s Move latents to cpu... done in 0.0s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.51it/s] 50%|█████ | 2/4 [00:00<00:00, 2.50it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.41it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] Decoding latents in cuda:0... done in 0.78s Move latents to cpu... done in 0.0s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.53it/s] 50%|█████ | 2/4 [00:00<00:00, 2.52it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.41it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] Decoding latents in cuda:0... done in 0.78s Move latents to cpu... done in 0.0s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.53it/s] 50%|█████ | 2/4 [00:00<00:00, 2.51it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.41it/s] 100%|██████████| 4/4 [00:01<00:00, 2.45it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] Decoding latents in cuda:0... done in 0.78s Move latents to cpu... done in 0.0s Uploading outputs... Finished.
prompt
Specify things to see in the output
painting, intricate details, medium shot of a Sensual Magnificent petite Art Nouveau (Female:1.3), furious, Vivacious pose, she has a Decora Navy Blue Cellphone, Invigorating Tattoos, city street and flora, soft focus, Fine art, Angry, Warm lighting, 800mm lens, two colors, artstation, trending on artstation, pixabay, ornate
negative_prompt
Specify things to not see in the output
bad quality, bad anatomy, low quality, worst quality, blury, grainey, old, badly drawn hands
num_outputs
Number of output images
3
width
Output image width
1024
height
Output image height
1024
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
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
1989517264
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
Euler a
samping_steps
Number of denoising steps
8
cfg_scale
Scale for classifier-free guidance
2.5
clip_skip
The number of last layers of CLIP network to skip
1
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/13d308184c7d41cfb631f4f92453ce90/00000-1989517264.webp
https://files.tungsten.run/uploads/adbccbc7da0245f9b17d2cc480a7bf70/00001-1989517265.webp
https://files.tungsten.run/uploads/98573c43a28240a69c6c6275d6b5b095/00002-1989517266.webp
Finished in 35.6 seconds
Preparing inputs... Processing... Full prompt: painting, intricate details, medium shot of a Sensual Magnificent petite Art Nouveau (Female:1.3), furious, Vivacious pose, she has a Decora Navy Blue Cellphone, Invigorating Tattoos, city street and flora, soft focus, Fine art, Angry, Warm lighting, 800mm lens, two colors, artstation, trending on artstation, pixabay, ornate Full negative prompt: bad quality, bad anatomy, low quality, worst quality, blury, grainey, old, badly drawn hands 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:01<00:09, 1.37s/it] 25%|██▌ | 2/8 [00:02<00:08, 1.37s/it] 38%|███▊ | 3/8 [00:04<00:06, 1.38s/it] 50%|█████ | 4/8 [00:05<00:05, 1.38s/it] 62%|██████▎ | 5/8 [00:06<00:04, 1.38s/it] 75%|███████▌ | 6/8 [00:08<00:02, 1.38s/it] 88%|████████▊ | 7/8 [00:09<00:01, 1.39s/it] 100%|██████████| 8/8 [00:11<00:00, 1.38s/it] 100%|██████████| 8/8 [00:11<00:00, 1.38s/it] Decoding latents in cuda:0... done in 2.34s Move latents to cpu... done in 0.01s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.51it/s] 50%|█████ | 2/4 [00:00<00:00, 2.50it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.40it/s] 100%|██████████| 4/4 [00:01<00:00, 2.44it/s] 100%|██████████| 4/4 [00:01<00:00, 2.45it/s] Decoding latents in cuda:0... done in 0.79s Move latents to cpu... done in 0.0s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.52it/s] 50%|█████ | 2/4 [00:00<00:00, 2.52it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.43it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] 100%|██████████| 4/4 [00:01<00:00, 2.47it/s] Decoding latents in cuda:0... done in 0.77s Move latents to cpu... done in 0.0s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.53it/s] 50%|█████ | 2/4 [00:00<00:00, 2.52it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.42it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] 100%|██████████| 4/4 [00:01<00:00, 2.47it/s] Decoding latents in cuda:0... done in 0.78s Move latents to cpu... done in 0.0s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.51it/s] 50%|█████ | 2/4 [00:00<00:00, 2.50it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.41it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] Decoding latents in cuda:0... done in 0.78s Move latents to cpu... done in 0.0s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.53it/s] 50%|█████ | 2/4 [00:00<00:00, 2.52it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.41it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] Decoding latents in cuda:0... done in 0.78s Move latents to cpu... done in 0.0s 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:01, 2.53it/s] 50%|█████ | 2/4 [00:00<00:00, 2.51it/s] 75%|███████▌ | 3/4 [00:01<00:00, 2.41it/s] 100%|██████████| 4/4 [00:01<00:00, 2.45it/s] 100%|██████████| 4/4 [00:01<00:00, 2.46it/s] Decoding latents in cuda:0... done in 0.78s Move latents to cpu... done in 0.0s Uploading outputs... Finished.