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River Goddess with Canvas Dark SDXL
canvas-dark-sdxl:v1.0
evevalentine2017
evevalentine2017
·
Feb 29
351
Input
prompt
Specify things to see in the output
light theme, cyan theme, pale green theme, [pale orcher theme], by Ken Sugimori, 1 asian girl, a river goddess, stands at the water's edge, crowned with reeds and lotus blossoms, embodying the life-giving force of the Nile, magnificent background, full of details,
negative_prompt
Specify things to not see in the output
worst quality, (low quality, normal quality:1.3), child, loli, kid
num_outputs
Number of output images
3
width
Output image width
768
height
Output image height
1024
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.
3358480025
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
10
clip_skip
The number of last layers of CLIP network to skip
2
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
https://files.tungsten.run/uploads/3c0af4d1f1e84c40823885db7ec32135/00000-3358480025.webp
https://files.tungsten.run/uploads/6820c4cf2e3b48b0b310d5e57a844b43/00001-3358480026.webp
https://files.tungsten.run/uploads/305de57bc38f415aa2534fcbb0e9a6ee/00002-3358480027.webp
Finished in 67.6 seconds
Setting up the model... Preparing inputs... Processing... Loading VAE weight: models/VAE/sdxl_vae.safetensors Full prompt: light theme, cyan theme, pale green theme, [pale orcher theme], by Ken Sugimori, 1 asian girl, a river goddess, stands at the water's edge, crowned with reeds and lotus blossoms, embodying the life-giving force of the Nile, magnificent background, full of details, Full negative prompt: worst quality, (low quality, normal quality:1.3), child, loli, kid 0%| | 0/35 [00:00<?, ?it/s] 3%|▎ | 1/35 [00:00<00:32, 1.05it/s] 6%|▌ | 2/35 [00:01<00:31, 1.05it/s] 9%|▊ | 3/35 [00:02<00:30, 1.04it/s] 11%|█▏ | 4/35 [00:03<00:29, 1.04it/s] 14%|█▍ | 5/35 [00:04<00:29, 1.03it/s] 17%|█▋ | 6/35 [00:05<00:28, 1.03it/s] 20%|██ | 7/35 [00:06<00:27, 1.02it/s] 23%|██▎ | 8/35 [00:07<00:26, 1.02it/s] 26%|██▌ | 9/35 [00:08<00:25, 1.01it/s] 29%|██▊ | 10/35 [00:09<00:24, 1.01it/s] 31%|███▏ | 11/35 [00:10<00:23, 1.01it/s] 34%|███▍ | 12/35 [00:11<00:22, 1.01it/s] 37%|███▋ | 13/35 [00:12<00:21, 1.00it/s] 40%|████ | 14/35 [00:13<00:20, 1.00it/s] 43%|████▎ | 15/35 [00:14<00:19, 1.00it/s] 46%|████▌ | 16/35 [00:15<00:19, 1.00s/it] 49%|████▊ | 17/35 [00:16<00:18, 1.00s/it] 51%|█████▏ | 18/35 [00:17<00:17, 1.01s/it] 54%|█████▍ | 19/35 [00:18<00:16, 1.01s/it] 57%|█████▋ | 20/35 [00:19<00:15, 1.01s/it] 60%|██████ | 21/35 [00:20<00:14, 1.01s/it] 63%|██████▎ | 22/35 [00:21<00:13, 1.01s/it] 66%|██████▌ | 23/35 [00:22<00:12, 1.02s/it] 69%|██████▊ | 24/35 [00:23<00:11, 1.02s/it] 71%|███████▏ | 25/35 [00:24<00:10, 1.02s/it] 74%|███████▍ | 26/35 [00:25<00:09, 1.02s/it] 77%|███████▋ | 27/35 [00:26<00:08, 1.03s/it] 80%|████████ | 28/35 [00:28<00:07, 1.03s/it] 83%|████████▎ | 29/35 [00:29<00:06, 1.03s/it] 86%|████████▌ | 30/35 [00:30<00:05, 1.03s/it] 89%|████████▊ | 31/35 [00:31<00:04, 1.03s/it] 91%|█████████▏| 32/35 [00:32<00:03, 1.03s/it] 94%|█████████▍| 33/35 [00:33<00:02, 1.03s/it] 97%|█████████▋| 34/35 [00:34<00:01, 1.03s/it] 100%|██████████| 35/35 [00:35<00:00, 1.03s/it] 100%|██████████| 35/35 [00:35<00:00, 1.01s/it] Decoding latents in cuda:0... done in 1.82s Move latents to cpu... done in 0.02s 0: 640x480 1 face, 159.5ms Speed: 5.9ms preprocess, 159.5ms inference, 32.3ms postprocess per image at shape (1, 3, 640, 480) 0%| | 0/16 [00:00<?, ?it/s] 6%|▋ | 1/16 [00:00<00:07, 2.13it/s] 12%|█▎ | 2/16 [00:00<00:05, 2.56it/s] 19%|█▉ | 3/16 [00:01<00:04, 2.71it/s] 25%|██▌ | 4/16 [00:01<00:04, 2.76it/s] 31%|███▏ | 5/16 [00:01<00:03, 2.83it/s] 38%|███▊ | 6/16 [00:02<00:03, 2.89it/s] 44%|████▍ | 7/16 [00:02<00:03, 2.91it/s] 50%|█████ | 8/16 [00:02<00:02, 2.93it/s] 56%|█████▋ | 9/16 [00:03<00:02, 2.94it/s] 62%|██████▎ | 10/16 [00:03<00:02, 2.93it/s] 69%|██████▉ | 11/16 [00:03<00:01, 2.95it/s] 75%|███████▌ | 12/16 [00:04<00:01, 2.95it/s] 81%|████████▏ | 13/16 [00:04<00:01, 2.94it/s] 88%|████████▊ | 14/16 [00:04<00:00, 2.94it/s] 94%|█████████▍| 15/16 [00:05<00:00, 2.94it/s] 100%|██████████| 16/16 [00:05<00:00, 2.94it/s] 100%|██████████| 16/16 [00:05<00:00, 2.88it/s] Decoding latents in cuda:0... done in 0.6s Move latents to cpu... done in 0.0s 0: 640x480 1 face, 8.4ms Speed: 2.5ms preprocess, 8.4ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 480) 0%| | 0/16 [00:00<?, ?it/s] 6%|▋ | 1/16 [00:00<00:05, 2.94it/s] 12%|█▎ | 2/16 [00:00<00:04, 2.91it/s] 19%|█▉ | 3/16 [00:01<00:04, 2.86it/s] 25%|██▌ | 4/16 [00:01<00:04, 2.88it/s] 31%|███▏ | 5/16 [00:01<00:03, 2.91it/s] 38%|███▊ | 6/16 [00:02<00:03, 2.88it/s] 44%|████▍ | 7/16 [00:02<00:03, 2.90it/s] 50%|█████ | 8/16 [00:02<00:02, 2.90it/s] 56%|█████▋ | 9/16 [00:03<00:02, 2.87it/s] 62%|██████▎ | 10/16 [00:03<00:02, 2.88it/s] 69%|██████▉ | 11/16 [00:03<00:01, 2.91it/s] 75%|███████▌ | 12/16 [00:04<00:01, 2.89it/s] 81%|████████▏ | 13/16 [00:04<00:01, 2.91it/s] 88%|████████▊ | 14/16 [00:04<00:00, 2.93it/s] 94%|█████████▍| 15/16 [00:05<00:00, 2.88it/s] 100%|██████████| 16/16 [00:05<00:00, 2.88it/s] 100%|██████████| 16/16 [00:05<00:00, 2.89it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s 0: 640x480 1 face, 18.5ms Speed: 4.2ms preprocess, 18.5ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 480) 0%| | 0/16 [00:00<?, ?it/s] 6%|▋ | 1/16 [00:00<00:09, 1.64it/s] 12%|█▎ | 2/16 [00:01<00:08, 1.67it/s] 19%|█▉ | 3/16 [00:01<00:06, 2.06it/s] 25%|██▌ | 4/16 [00:01<00:05, 2.35it/s] 31%|███▏ | 5/16 [00:02<00:04, 2.52it/s] 38%|███▊ | 6/16 [00:02<00:03, 2.60it/s] 44%|████▍ | 7/16 [00:02<00:03, 2.71it/s] 50%|█████ | 8/16 [00:03<00:02, 2.76it/s] 56%|█████▋ | 9/16 [00:03<00:02, 2.76it/s] 62%|██████▎ | 10/16 [00:03<00:02, 2.80it/s] 69%|██████▉ | 11/16 [00:04<00:01, 2.84it/s] 75%|███████▌ | 12/16 [00:04<00:01, 2.82it/s] 81%|████████▏ | 13/16 [00:05<00:01, 2.85it/s] 88%|████████▊ | 14/16 [00:05<00:00, 2.80it/s] 94%|█████████▍| 15/16 [00:05<00:00, 2.85it/s] 100%|██████████| 16/16 [00:06<00:00, 2.87it/s] 100%|██████████| 16/16 [00:06<00:00, 2.63it/s] Decoding latents in cuda:0... done in 0.6s Move latents to cpu... done in 0.0s Uploading outputs... Finished.
prompt
Specify things to see in the output
light theme, cyan theme, pale green theme, [pale orcher theme], by Ken Sugimori, 1 asian girl, a river goddess, stands at the water's edge, crowned with reeds and lotus blossoms, embodying the life-giving force of the Nile, magnificent background, full of details,
negative_prompt
Specify things to not see in the output
worst quality, (low quality, normal quality:1.3), child, loli, kid
num_outputs
Number of output images
3
width
Output image width
768
height
Output image height
1024
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.
3358480025
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
10
clip_skip
The number of last layers of CLIP network to skip
2
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
https://files.tungsten.run/uploads/3c0af4d1f1e84c40823885db7ec32135/00000-3358480025.webp
https://files.tungsten.run/uploads/6820c4cf2e3b48b0b310d5e57a844b43/00001-3358480026.webp
https://files.tungsten.run/uploads/305de57bc38f415aa2534fcbb0e9a6ee/00002-3358480027.webp
Finished in 67.6 seconds
Setting up the model... Preparing inputs... Processing... Loading VAE weight: models/VAE/sdxl_vae.safetensors Full prompt: light theme, cyan theme, pale green theme, [pale orcher theme], by Ken Sugimori, 1 asian girl, a river goddess, stands at the water's edge, crowned with reeds and lotus blossoms, embodying the life-giving force of the Nile, magnificent background, full of details, Full negative prompt: worst quality, (low quality, normal quality:1.3), child, loli, kid 0%| | 0/35 [00:00<?, ?it/s] 3%|▎ | 1/35 [00:00<00:32, 1.05it/s] 6%|▌ | 2/35 [00:01<00:31, 1.05it/s] 9%|▊ | 3/35 [00:02<00:30, 1.04it/s] 11%|█▏ | 4/35 [00:03<00:29, 1.04it/s] 14%|█▍ | 5/35 [00:04<00:29, 1.03it/s] 17%|█▋ | 6/35 [00:05<00:28, 1.03it/s] 20%|██ | 7/35 [00:06<00:27, 1.02it/s] 23%|██▎ | 8/35 [00:07<00:26, 1.02it/s] 26%|██▌ | 9/35 [00:08<00:25, 1.01it/s] 29%|██▊ | 10/35 [00:09<00:24, 1.01it/s] 31%|███▏ | 11/35 [00:10<00:23, 1.01it/s] 34%|███▍ | 12/35 [00:11<00:22, 1.01it/s] 37%|███▋ | 13/35 [00:12<00:21, 1.00it/s] 40%|████ | 14/35 [00:13<00:20, 1.00it/s] 43%|████▎ | 15/35 [00:14<00:19, 1.00it/s] 46%|████▌ | 16/35 [00:15<00:19, 1.00s/it] 49%|████▊ | 17/35 [00:16<00:18, 1.00s/it] 51%|█████▏ | 18/35 [00:17<00:17, 1.01s/it] 54%|█████▍ | 19/35 [00:18<00:16, 1.01s/it] 57%|█████▋ | 20/35 [00:19<00:15, 1.01s/it] 60%|██████ | 21/35 [00:20<00:14, 1.01s/it] 63%|██████▎ | 22/35 [00:21<00:13, 1.01s/it] 66%|██████▌ | 23/35 [00:22<00:12, 1.02s/it] 69%|██████▊ | 24/35 [00:23<00:11, 1.02s/it] 71%|███████▏ | 25/35 [00:24<00:10, 1.02s/it] 74%|███████▍ | 26/35 [00:25<00:09, 1.02s/it] 77%|███████▋ | 27/35 [00:26<00:08, 1.03s/it] 80%|████████ | 28/35 [00:28<00:07, 1.03s/it] 83%|████████▎ | 29/35 [00:29<00:06, 1.03s/it] 86%|████████▌ | 30/35 [00:30<00:05, 1.03s/it] 89%|████████▊ | 31/35 [00:31<00:04, 1.03s/it] 91%|█████████▏| 32/35 [00:32<00:03, 1.03s/it] 94%|█████████▍| 33/35 [00:33<00:02, 1.03s/it] 97%|█████████▋| 34/35 [00:34<00:01, 1.03s/it] 100%|██████████| 35/35 [00:35<00:00, 1.03s/it] 100%|██████████| 35/35 [00:35<00:00, 1.01s/it] Decoding latents in cuda:0... done in 1.82s Move latents to cpu... done in 0.02s 0: 640x480 1 face, 159.5ms Speed: 5.9ms preprocess, 159.5ms inference, 32.3ms postprocess per image at shape (1, 3, 640, 480) 0%| | 0/16 [00:00<?, ?it/s] 6%|▋ | 1/16 [00:00<00:07, 2.13it/s] 12%|█▎ | 2/16 [00:00<00:05, 2.56it/s] 19%|█▉ | 3/16 [00:01<00:04, 2.71it/s] 25%|██▌ | 4/16 [00:01<00:04, 2.76it/s] 31%|███▏ | 5/16 [00:01<00:03, 2.83it/s] 38%|███▊ | 6/16 [00:02<00:03, 2.89it/s] 44%|████▍ | 7/16 [00:02<00:03, 2.91it/s] 50%|█████ | 8/16 [00:02<00:02, 2.93it/s] 56%|█████▋ | 9/16 [00:03<00:02, 2.94it/s] 62%|██████▎ | 10/16 [00:03<00:02, 2.93it/s] 69%|██████▉ | 11/16 [00:03<00:01, 2.95it/s] 75%|███████▌ | 12/16 [00:04<00:01, 2.95it/s] 81%|████████▏ | 13/16 [00:04<00:01, 2.94it/s] 88%|████████▊ | 14/16 [00:04<00:00, 2.94it/s] 94%|█████████▍| 15/16 [00:05<00:00, 2.94it/s] 100%|██████████| 16/16 [00:05<00:00, 2.94it/s] 100%|██████████| 16/16 [00:05<00:00, 2.88it/s] Decoding latents in cuda:0... done in 0.6s Move latents to cpu... done in 0.0s 0: 640x480 1 face, 8.4ms Speed: 2.5ms preprocess, 8.4ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 480) 0%| | 0/16 [00:00<?, ?it/s] 6%|▋ | 1/16 [00:00<00:05, 2.94it/s] 12%|█▎ | 2/16 [00:00<00:04, 2.91it/s] 19%|█▉ | 3/16 [00:01<00:04, 2.86it/s] 25%|██▌ | 4/16 [00:01<00:04, 2.88it/s] 31%|███▏ | 5/16 [00:01<00:03, 2.91it/s] 38%|███▊ | 6/16 [00:02<00:03, 2.88it/s] 44%|████▍ | 7/16 [00:02<00:03, 2.90it/s] 50%|█████ | 8/16 [00:02<00:02, 2.90it/s] 56%|█████▋ | 9/16 [00:03<00:02, 2.87it/s] 62%|██████▎ | 10/16 [00:03<00:02, 2.88it/s] 69%|██████▉ | 11/16 [00:03<00:01, 2.91it/s] 75%|███████▌ | 12/16 [00:04<00:01, 2.89it/s] 81%|████████▏ | 13/16 [00:04<00:01, 2.91it/s] 88%|████████▊ | 14/16 [00:04<00:00, 2.93it/s] 94%|█████████▍| 15/16 [00:05<00:00, 2.88it/s] 100%|██████████| 16/16 [00:05<00:00, 2.88it/s] 100%|██████████| 16/16 [00:05<00:00, 2.89it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s 0: 640x480 1 face, 18.5ms Speed: 4.2ms preprocess, 18.5ms inference, 3.1ms postprocess per image at shape (1, 3, 640, 480) 0%| | 0/16 [00:00<?, ?it/s] 6%|▋ | 1/16 [00:00<00:09, 1.64it/s] 12%|█▎ | 2/16 [00:01<00:08, 1.67it/s] 19%|█▉ | 3/16 [00:01<00:06, 2.06it/s] 25%|██▌ | 4/16 [00:01<00:05, 2.35it/s] 31%|███▏ | 5/16 [00:02<00:04, 2.52it/s] 38%|███▊ | 6/16 [00:02<00:03, 2.60it/s] 44%|████▍ | 7/16 [00:02<00:03, 2.71it/s] 50%|█████ | 8/16 [00:03<00:02, 2.76it/s] 56%|█████▋ | 9/16 [00:03<00:02, 2.76it/s] 62%|██████▎ | 10/16 [00:03<00:02, 2.80it/s] 69%|██████▉ | 11/16 [00:04<00:01, 2.84it/s] 75%|███████▌ | 12/16 [00:04<00:01, 2.82it/s] 81%|████████▏ | 13/16 [00:05<00:01, 2.85it/s] 88%|████████▊ | 14/16 [00:05<00:00, 2.80it/s] 94%|█████████▍| 15/16 [00:05<00:00, 2.85it/s] 100%|██████████| 16/16 [00:06<00:00, 2.87it/s] 100%|██████████| 16/16 [00:06<00:00, 2.63it/s] Decoding latents in cuda:0... done in 0.6s Move latents to cpu... done in 0.0s Uploading outputs... Finished.