Cyberpunk Streets with Cyber Realistic XL
Input
prompt
Specify things to see in the output
100mm raw camera, f/2.8, professional photo, (by night, starts, moon), photo of Cyberpunk, big city, small street with food stalls, cinematic, film grain, professional photo, film photography, 4k ultra detailed), ultra realistic, best quality, subsurface scattering, volumetric lighting, clear focus, masterpiece, 64k, UHD, HDR, digital photography, backlighting
negative_prompt
Specify things to not see in the output
(less than 2 pirate ships), sunset, desaturated, (worst quality, low quality, normal quality, lowres, low details, grayscale, bw), text, signature, username, watermark
num_outputs
Number of output images
3
width
Output image width
1024
height
Output image height
768
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
false
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.
289963012
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 Karras
samping_steps
Number of denoising steps
35
cfg_scale
Scale for classifier-free guidance
7
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
Finished in 249.5 seconds
Setting up the model...
Preparing inputs...
Processing...
Full prompt: 100mm raw camera, f/2.8, professional photo, (by night, starts, moon), photo of Cyberpunk, big city, small street with food stalls, cinematic, film grain, professional photo, film photography, 4k ultra detailed), ultra realistic, best quality, subsurface scattering, volumetric lighting, clear focus, masterpiece, 64k, UHD, HDR, digital photography, backlighting
Full negative prompt: (less than 2 pirate ships), sunset, desaturated, (worst quality, low quality, normal quality, lowres, low details, grayscale, bw), text, signature, username, watermark
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0: 480x640 3 faces, 165.3ms
Speed: 2.9ms preprocess, 165.3ms inference, 39.8ms postprocess per image at shape (1, 3, 480, 640)
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0: 480x640 7 faces, 8.2ms
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0: 480x640 9 faces, 8.0ms
Speed: 2.4ms preprocess, 8.0ms inference, 1.3ms postprocess per image at shape (1, 3, 480, 640)
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Uploading outputs...
Finished.
prompt
Specify things to see in the output
100mm raw camera, f/2.8, professional photo, (by night, starts, moon), photo of Cyberpunk, big city, small street with food stalls, cinematic, film grain, professional photo, film photography, 4k ultra detailed), ultra realistic, best quality, subsurface scattering, volumetric lighting, clear focus, masterpiece, 64k, UHD, HDR, digital photography, backlighting
negative_prompt
Specify things to not see in the output
(less than 2 pirate ships), sunset, desaturated, (worst quality, low quality, normal quality, lowres, low details, grayscale, bw), text, signature, username, watermark
num_outputs
Number of output images
3
width
Output image width
1024
height
Output image height
768
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
false
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.
289963012
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 Karras
samping_steps
Number of denoising steps
35
cfg_scale
Scale for classifier-free guidance
7
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
Finished in 249.5 seconds
Setting up the model...
Preparing inputs...
Processing...
Full prompt: 100mm raw camera, f/2.8, professional photo, (by night, starts, moon), photo of Cyberpunk, big city, small street with food stalls, cinematic, film grain, professional photo, film photography, 4k ultra detailed), ultra realistic, best quality, subsurface scattering, volumetric lighting, clear focus, masterpiece, 64k, UHD, HDR, digital photography, backlighting
Full negative prompt: (less than 2 pirate ships), sunset, desaturated, (worst quality, low quality, normal quality, lowres, low details, grayscale, bw), text, signature, username, watermark
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0: 480x640 3 faces, 165.3ms
Speed: 2.9ms preprocess, 165.3ms inference, 39.8ms postprocess per image at shape (1, 3, 480, 640)
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Decoding latents in cuda:0...
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Decoding latents in cuda:0...
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0: 480x640 7 faces, 8.2ms
Speed: 2.5ms preprocess, 8.2ms inference, 1.7ms postprocess per image at shape (1, 3, 480, 640)
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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: 480x640 9 faces, 8.0ms
Speed: 2.4ms preprocess, 8.0ms inference, 1.3ms postprocess per image at shape (1, 3, 480, 640)
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Decoding latents in cuda:0...
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Decoding latents in cuda:0...
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Decoding latents in cuda:0...
done in 0.56s
Move latents to cpu...
done in 0.0s
Uploading outputs...
Finished.