Medieval Knights with Hephaistos SD XL
Input
prompt
Specify things to see in the output
(8K, masterpiece, award winning photo:1.3), (ultra highres, absurdres, ultradetailed, sharp focus, realistic colors:1.1), (hyperdetailed art of a paladin in holy armor with cape, armed with spear and shield, visored medieval helmet), (perfect lighting, detailed shadows), Holy symbols
negative_prompt
Specify things to not see in the output
(worst quality, low quality, 2d, painting, cartoons, sketch:1.1), tooth, open mouth, dull, blurry, watermark, low quality, black and white, dull skin, lack of details, airbrushed skin, bad hands, mutated, grotesque, ugly hands, weird 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.
1093472197
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
80
cfg_scale
Scale for classifier-free guidance
8
clip_skip
The number of last layers of CLIP network to skip
1
vae
Select VAE
sdxl_vae.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 452.4 seconds
Setting up the model...
Preparing inputs...
Processing...
Loading VAE weight: models/VAE/sdxl_vae.safetensors
Full prompt: (8K, masterpiece, award winning photo:1.3), (ultra highres, absurdres, ultradetailed, sharp focus, realistic colors:1.1), (hyperdetailed art of a paladin in holy armor with cape, armed with spear and shield, visored medieval helmet), (perfect lighting, detailed shadows), Holy symbols
Full negative prompt: (worst quality, low quality, 2d, painting, cartoons, sketch:1.1), tooth, open mouth, dull, blurry, watermark, low quality, black and white, dull skin, lack of details, airbrushed skin, bad hands, mutated, grotesque, ugly hands, weird hands
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Decoding latents in cuda:0...
done in 2.41s
Move latents to cpu...
done in 0.03s
0: 640x640 (no detections), 7.7ms
Speed: 3.2ms preprocess, 7.7ms inference, 1.0ms postprocess per image at shape (1, 3, 640, 640)
[-] ADetailer: nothing detected on image 1 with 1st settings.
0: 640x640 1 hand, 7.1ms
Speed: 3.0ms preprocess, 7.1ms inference, 22.4ms 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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0: 640x640 2 faces, 7.6ms
Speed: 3.3ms preprocess, 7.6ms inference, 1.6ms 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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0: 640x640 2 hands, 7.6ms
Speed: 3.3ms preprocess, 7.6ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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0: 640x640 (no detections), 7.2ms
Speed: 3.4ms preprocess, 7.2ms inference, 0.8ms postprocess per image at shape (1, 3, 640, 640)
[-] ADetailer: nothing detected on image 3 with 2nd settings.
Uploading outputs...
Finished.
prompt
Specify things to see in the output
(8K, masterpiece, award winning photo:1.3), (ultra highres, absurdres, ultradetailed, sharp focus, realistic colors:1.1), (hyperdetailed art of a paladin in holy armor with cape, armed with spear and shield, visored medieval helmet), (perfect lighting, detailed shadows), Holy symbols
negative_prompt
Specify things to not see in the output
(worst quality, low quality, 2d, painting, cartoons, sketch:1.1), tooth, open mouth, dull, blurry, watermark, low quality, black and white, dull skin, lack of details, airbrushed skin, bad hands, mutated, grotesque, ugly hands, weird 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.
1093472197
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
80
cfg_scale
Scale for classifier-free guidance
8
clip_skip
The number of last layers of CLIP network to skip
1
vae
Select VAE
sdxl_vae.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 452.4 seconds
Setting up the model...
Preparing inputs...
Processing...
Loading VAE weight: models/VAE/sdxl_vae.safetensors
Full prompt: (8K, masterpiece, award winning photo:1.3), (ultra highres, absurdres, ultradetailed, sharp focus, realistic colors:1.1), (hyperdetailed art of a paladin in holy armor with cape, armed with spear and shield, visored medieval helmet), (perfect lighting, detailed shadows), Holy symbols
Full negative prompt: (worst quality, low quality, 2d, painting, cartoons, sketch:1.1), tooth, open mouth, dull, blurry, watermark, low quality, black and white, dull skin, lack of details, airbrushed skin, bad hands, mutated, grotesque, ugly hands, weird hands
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100%|██████████| 80/80 [03:25<00:00, 1.84s/it]
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Decoding latents in cuda:0...
done in 2.41s
Move latents to cpu...
done in 0.03s
0: 640x640 (no detections), 7.7ms
Speed: 3.2ms preprocess, 7.7ms inference, 1.0ms postprocess per image at shape (1, 3, 640, 640)
[-] ADetailer: nothing detected on image 1 with 1st settings.
0: 640x640 1 hand, 7.1ms
Speed: 3.0ms preprocess, 7.1ms inference, 22.4ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.81s
Move latents to cpu...
done in 0.0s
0: 640x640 2 faces, 7.6ms
Speed: 3.3ms preprocess, 7.6ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.81s
Move latents to cpu...
done in 0.0s
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Decoding latents in cuda:0...
done in 0.81s
Move latents to cpu...
done in 0.0s
0: 640x640 2 hands, 7.6ms
Speed: 3.3ms preprocess, 7.6ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.81s
Move latents to cpu...
done in 0.0s
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Decoding latents in cuda:0...
done in 0.8s
Move latents to cpu...
done in 0.0s
0: 640x640 3 faces, 8.5ms
Speed: 3.3ms preprocess, 8.5ms inference, 1.9ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.8s
Move latents to cpu...
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Decoding latents in cuda:0...
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Decoding latents in cuda:0...
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Move latents to cpu...
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0: 640x640 (no detections), 7.2ms
Speed: 3.4ms preprocess, 7.2ms inference, 0.8ms postprocess per image at shape (1, 3, 640, 640)
[-] ADetailer: nothing detected on image 3 with 2nd settings.
Uploading outputs...
Finished.