Chinese Demons with Acorn Is Spinning XL
Input
prompt
Specify things to see in the output
a wooden country house decorated with Christmas decorations and a decorated Christmas tree next to it, white and red color, digital art style, hight quality, detailed, colorful aura, brightly
negative_prompt
Specify things to not see in the output
(normal quality:2), (b&w:1.2), (black and white:1.2),(disfigured:1.2),(deformed:1.2), (extra limbs:1.2), (b&w:1.2), (blurry:1.2), (duplicate:1.2), (morbid:1.2), (mutilated:1.2), (poorly drawn hands:1.2), (poorly drawn face:1.2), (mutation:1.2), (deformed:1.2), (bad anatomy:1.2), (watermark:1.5), text
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.
377963548
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
80
cfg_scale
Scale for classifier-free guidance
7
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/0d1213152d45419f8144e576f560a899/00000-377963548.webp
https://files.tungsten.run/uploads/610d33ead6534bb3a25d7329f1fb7e93/00001-377963549.webp
https://files.tungsten.run/uploads/51c59487a675463982291e2f7d17ec14/00002-377963550.webp
Finished in 86.4 seconds
Setting up the model... Preparing inputs... Processing... Loading VAE weight: models/VAE/sdxl_vae.safetensors Full prompt: a wooden country house decorated with Christmas decorations and a decorated Christmas tree next to it, white and red color, digital art style, hight quality, detailed, colorful aura, brightly Full negative prompt: (normal quality:2), (b&w:1.2), (black and white:1.2),(disfigured:1.2),(deformed:1.2), (extra limbs:1.2), (b&w:1.2), (blurry:1.2), (duplicate:1.2), (morbid:1.2), (mutilated:1.2), (poorly drawn hands:1.2), (poorly drawn face:1.2), (mutation:1.2), (deformed:1.2), (bad anatomy:1.2), (watermark:1.5), text 0%| | 0/80 [00:00<?, ?it/s] 1%|▏ | 1/80 [00:00<01:12, 1.09it/s] 2%|▎ | 2/80 [00:01<01:11, 1.09it/s] 4%|▍ | 3/80 [00:02<01:10, 1.09it/s] 5%|▌ | 4/80 [00:03<01:09, 1.09it/s] 6%|▋ | 5/80 [00:04<01:08, 1.09it/s] 8%|▊ | 6/80 [00:05<01:08, 1.09it/s] 9%|▉ | 7/80 [00:06<01:07, 1.08it/s] 10%|█ | 8/80 [00:07<01:06, 1.08it/s] 11%|█▏ | 9/80 [00:08<01:05, 1.08it/s] 12%|█▎ | 10/80 [00:09<01:05, 1.08it/s] 14%|█▍ | 11/80 [00:10<01:04, 1.08it/s] 15%|█▌ | 12/80 [00:11<01:03, 1.07it/s] 16%|█▋ | 13/80 [00:12<01:02, 1.07it/s] 18%|█▊ | 14/80 [00:12<01:01, 1.07it/s] 19%|█▉ | 15/80 [00:13<01:00, 1.07it/s] 20%|██ | 16/80 [00:14<00:59, 1.07it/s] 21%|██▏ | 17/80 [00:15<00:58, 1.07it/s] 22%|██▎ | 18/80 [00:16<00:57, 1.07it/s] 24%|██▍ | 19/80 [00:17<00:56, 1.07it/s] 25%|██▌ | 20/80 [00:18<00:56, 1.07it/s] 26%|██▋ | 21/80 [00:19<00:55, 1.07it/s] 28%|██▊ | 22/80 [00:20<00:54, 1.07it/s] 29%|██▉ | 23/80 [00:21<00:53, 1.07it/s] 30%|███ | 24/80 [00:22<00:52, 1.07it/s] 31%|███▏ | 25/80 [00:23<00:51, 1.06it/s] 32%|███▎ | 26/80 [00:24<00:50, 1.06it/s] 34%|███▍ | 27/80 [00:25<00:49, 1.06it/s] 35%|███▌ | 28/80 [00:26<00:48, 1.06it/s] 36%|███▋ | 29/80 [00:27<00:48, 1.06it/s] 38%|███▊ | 30/80 [00:27<00:47, 1.06it/s] 39%|███▉ | 31/80 [00:28<00:46, 1.06it/s] 40%|████ | 32/80 [00:29<00:45, 1.06it/s] 41%|████▏ | 33/80 [00:30<00:44, 1.06it/s] 42%|████▎ | 34/80 [00:31<00:43, 1.05it/s] 44%|████▍ | 35/80 [00:32<00:42, 1.05it/s] 45%|████▌ | 36/80 [00:33<00:41, 1.05it/s] 46%|████▋ | 37/80 [00:34<00:40, 1.05it/s] 48%|████▊ | 38/80 [00:35<00:40, 1.05it/s] 49%|████▉ | 39/80 [00:36<00:39, 1.05it/s] 50%|█████ | 40/80 [00:37<00:38, 1.05it/s] 51%|█████▏ | 41/80 [00:38<00:37, 1.05it/s] 52%|█████▎ | 42/80 [00:39<00:36, 1.05it/s] 54%|█████▍ | 43/80 [00:40<00:35, 1.05it/s] 55%|█████▌ | 44/80 [00:41<00:34, 1.05it/s] 56%|█████▋ | 45/80 [00:42<00:33, 1.04it/s] 57%|█████▊ | 46/80 [00:43<00:32, 1.04it/s] 59%|█████▉ | 47/80 [00:44<00:31, 1.04it/s] 60%|██████ | 48/80 [00:45<00:30, 1.05it/s] 61%|██████▏ | 49/80 [00:46<00:29, 1.05it/s] 62%|██████▎ | 50/80 [00:47<00:28, 1.05it/s] 64%|██████▍ | 51/80 [00:48<00:27, 1.04it/s] 65%|██████▌ | 52/80 [00:48<00:26, 1.04it/s] 66%|██████▋ | 53/80 [00:49<00:25, 1.04it/s] 68%|██████▊ | 54/80 [00:50<00:24, 1.04it/s] 69%|██████▉ | 55/80 [00:51<00:23, 1.04it/s] 70%|███████ | 56/80 [00:52<00:23, 1.04it/s] 71%|███████▏ | 57/80 [00:53<00:22, 1.04it/s] 72%|███████▎ | 58/80 [00:54<00:21, 1.04it/s] 74%|███████▍ | 59/80 [00:55<00:20, 1.04it/s] 75%|███████▌ | 60/80 [00:56<00:19, 1.04it/s] 76%|███████▋ | 61/80 [00:57<00:18, 1.04it/s] 78%|███████▊ | 62/80 [00:58<00:17, 1.04it/s] 79%|███████▉ | 63/80 [00:59<00:16, 1.04it/s] 80%|████████ | 64/80 [01:00<00:15, 1.04it/s] 81%|████████▏ | 65/80 [01:01<00:14, 1.04it/s] 82%|████████▎ | 66/80 [01:02<00:13, 1.04it/s] 84%|████████▍ | 67/80 [01:03<00:12, 1.04it/s] 85%|████████▌ | 68/80 [01:04<00:11, 1.04it/s] 86%|████████▋ | 69/80 [01:05<00:10, 1.04it/s] 88%|████████▊ | 70/80 [01:06<00:09, 1.04it/s] 89%|████████▉ | 71/80 [01:07<00:08, 1.04it/s] 90%|█████████ | 72/80 [01:08<00:07, 1.04it/s] 91%|█████████▏| 73/80 [01:09<00:06, 1.04it/s] 92%|█████████▎| 74/80 [01:10<00:05, 1.04it/s] 94%|█████████▍| 75/80 [01:11<00:04, 1.04it/s] 95%|█████████▌| 76/80 [01:12<00:03, 1.04it/s] 96%|█████████▋| 77/80 [01:13<00:02, 1.04it/s] 98%|█████████▊| 78/80 [01:14<00:01, 1.04it/s] 99%|█████████▉| 79/80 [01:14<00:00, 1.03it/s] 100%|██████████| 80/80 [01:15<00:00, 1.03it/s] 100%|██████████| 80/80 [01:15<00:00, 1.05it/s] Decoding latents in cuda:0... done in 1.75s Move latents to cpu... done in 0.02s 0: 640x480 (no detections), 159.0ms Speed: 4.9ms preprocess, 159.0ms inference, 10.5ms postprocess per image at shape (1, 3, 640, 480) [-] ADetailer: nothing detected on image 1 with 1st settings. 0: 640x480 (no detections), 8.0ms Speed: 2.4ms preprocess, 8.0ms inference, 0.8ms postprocess per image at shape (1, 3, 640, 480) [-] ADetailer: nothing detected on image 2 with 1st settings. 0: 640x480 (no detections), 7.8ms Speed: 2.3ms preprocess, 7.8ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 480) [-] ADetailer: nothing detected on image 3 with 1st settings. Uploading outputs... Finished.
prompt
Specify things to see in the output
a wooden country house decorated with Christmas decorations and a decorated Christmas tree next to it, white and red color, digital art style, hight quality, detailed, colorful aura, brightly
negative_prompt
Specify things to not see in the output
(normal quality:2), (b&w:1.2), (black and white:1.2),(disfigured:1.2),(deformed:1.2), (extra limbs:1.2), (b&w:1.2), (blurry:1.2), (duplicate:1.2), (morbid:1.2), (mutilated:1.2), (poorly drawn hands:1.2), (poorly drawn face:1.2), (mutation:1.2), (deformed:1.2), (bad anatomy:1.2), (watermark:1.5), text
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.
377963548
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
80
cfg_scale
Scale for classifier-free guidance
7
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/0d1213152d45419f8144e576f560a899/00000-377963548.webp
https://files.tungsten.run/uploads/610d33ead6534bb3a25d7329f1fb7e93/00001-377963549.webp
https://files.tungsten.run/uploads/51c59487a675463982291e2f7d17ec14/00002-377963550.webp
Finished in 86.4 seconds
Setting up the model... Preparing inputs... Processing... Loading VAE weight: models/VAE/sdxl_vae.safetensors Full prompt: a wooden country house decorated with Christmas decorations and a decorated Christmas tree next to it, white and red color, digital art style, hight quality, detailed, colorful aura, brightly Full negative prompt: (normal quality:2), (b&w:1.2), (black and white:1.2),(disfigured:1.2),(deformed:1.2), (extra limbs:1.2), (b&w:1.2), (blurry:1.2), (duplicate:1.2), (morbid:1.2), (mutilated:1.2), (poorly drawn hands:1.2), (poorly drawn face:1.2), (mutation:1.2), (deformed:1.2), (bad anatomy:1.2), (watermark:1.5), text 0%| | 0/80 [00:00<?, ?it/s] 1%|▏ | 1/80 [00:00<01:12, 1.09it/s] 2%|▎ | 2/80 [00:01<01:11, 1.09it/s] 4%|▍ | 3/80 [00:02<01:10, 1.09it/s] 5%|▌ | 4/80 [00:03<01:09, 1.09it/s] 6%|▋ | 5/80 [00:04<01:08, 1.09it/s] 8%|▊ | 6/80 [00:05<01:08, 1.09it/s] 9%|▉ | 7/80 [00:06<01:07, 1.08it/s] 10%|█ | 8/80 [00:07<01:06, 1.08it/s] 11%|█▏ | 9/80 [00:08<01:05, 1.08it/s] 12%|█▎ | 10/80 [00:09<01:05, 1.08it/s] 14%|█▍ | 11/80 [00:10<01:04, 1.08it/s] 15%|█▌ | 12/80 [00:11<01:03, 1.07it/s] 16%|█▋ | 13/80 [00:12<01:02, 1.07it/s] 18%|█▊ | 14/80 [00:12<01:01, 1.07it/s] 19%|█▉ | 15/80 [00:13<01:00, 1.07it/s] 20%|██ | 16/80 [00:14<00:59, 1.07it/s] 21%|██▏ | 17/80 [00:15<00:58, 1.07it/s] 22%|██▎ | 18/80 [00:16<00:57, 1.07it/s] 24%|██▍ | 19/80 [00:17<00:56, 1.07it/s] 25%|██▌ | 20/80 [00:18<00:56, 1.07it/s] 26%|██▋ | 21/80 [00:19<00:55, 1.07it/s] 28%|██▊ | 22/80 [00:20<00:54, 1.07it/s] 29%|██▉ | 23/80 [00:21<00:53, 1.07it/s] 30%|███ | 24/80 [00:22<00:52, 1.07it/s] 31%|███▏ | 25/80 [00:23<00:51, 1.06it/s] 32%|███▎ | 26/80 [00:24<00:50, 1.06it/s] 34%|███▍ | 27/80 [00:25<00:49, 1.06it/s] 35%|███▌ | 28/80 [00:26<00:48, 1.06it/s] 36%|███▋ | 29/80 [00:27<00:48, 1.06it/s] 38%|███▊ | 30/80 [00:27<00:47, 1.06it/s] 39%|███▉ | 31/80 [00:28<00:46, 1.06it/s] 40%|████ | 32/80 [00:29<00:45, 1.06it/s] 41%|████▏ | 33/80 [00:30<00:44, 1.06it/s] 42%|████▎ | 34/80 [00:31<00:43, 1.05it/s] 44%|████▍ | 35/80 [00:32<00:42, 1.05it/s] 45%|████▌ | 36/80 [00:33<00:41, 1.05it/s] 46%|████▋ | 37/80 [00:34<00:40, 1.05it/s] 48%|████▊ | 38/80 [00:35<00:40, 1.05it/s] 49%|████▉ | 39/80 [00:36<00:39, 1.05it/s] 50%|█████ | 40/80 [00:37<00:38, 1.05it/s] 51%|█████▏ | 41/80 [00:38<00:37, 1.05it/s] 52%|█████▎ | 42/80 [00:39<00:36, 1.05it/s] 54%|█████▍ | 43/80 [00:40<00:35, 1.05it/s] 55%|█████▌ | 44/80 [00:41<00:34, 1.05it/s] 56%|█████▋ | 45/80 [00:42<00:33, 1.04it/s] 57%|█████▊ | 46/80 [00:43<00:32, 1.04it/s] 59%|█████▉ | 47/80 [00:44<00:31, 1.04it/s] 60%|██████ | 48/80 [00:45<00:30, 1.05it/s] 61%|██████▏ | 49/80 [00:46<00:29, 1.05it/s] 62%|██████▎ | 50/80 [00:47<00:28, 1.05it/s] 64%|██████▍ | 51/80 [00:48<00:27, 1.04it/s] 65%|██████▌ | 52/80 [00:48<00:26, 1.04it/s] 66%|██████▋ | 53/80 [00:49<00:25, 1.04it/s] 68%|██████▊ | 54/80 [00:50<00:24, 1.04it/s] 69%|██████▉ | 55/80 [00:51<00:23, 1.04it/s] 70%|███████ | 56/80 [00:52<00:23, 1.04it/s] 71%|███████▏ | 57/80 [00:53<00:22, 1.04it/s] 72%|███████▎ | 58/80 [00:54<00:21, 1.04it/s] 74%|███████▍ | 59/80 [00:55<00:20, 1.04it/s] 75%|███████▌ | 60/80 [00:56<00:19, 1.04it/s] 76%|███████▋ | 61/80 [00:57<00:18, 1.04it/s] 78%|███████▊ | 62/80 [00:58<00:17, 1.04it/s] 79%|███████▉ | 63/80 [00:59<00:16, 1.04it/s] 80%|████████ | 64/80 [01:00<00:15, 1.04it/s] 81%|████████▏ | 65/80 [01:01<00:14, 1.04it/s] 82%|████████▎ | 66/80 [01:02<00:13, 1.04it/s] 84%|████████▍ | 67/80 [01:03<00:12, 1.04it/s] 85%|████████▌ | 68/80 [01:04<00:11, 1.04it/s] 86%|████████▋ | 69/80 [01:05<00:10, 1.04it/s] 88%|████████▊ | 70/80 [01:06<00:09, 1.04it/s] 89%|████████▉ | 71/80 [01:07<00:08, 1.04it/s] 90%|█████████ | 72/80 [01:08<00:07, 1.04it/s] 91%|█████████▏| 73/80 [01:09<00:06, 1.04it/s] 92%|█████████▎| 74/80 [01:10<00:05, 1.04it/s] 94%|█████████▍| 75/80 [01:11<00:04, 1.04it/s] 95%|█████████▌| 76/80 [01:12<00:03, 1.04it/s] 96%|█████████▋| 77/80 [01:13<00:02, 1.04it/s] 98%|█████████▊| 78/80 [01:14<00:01, 1.04it/s] 99%|█████████▉| 79/80 [01:14<00:00, 1.03it/s] 100%|██████████| 80/80 [01:15<00:00, 1.03it/s] 100%|██████████| 80/80 [01:15<00:00, 1.05it/s] Decoding latents in cuda:0... done in 1.75s Move latents to cpu... done in 0.02s 0: 640x480 (no detections), 159.0ms Speed: 4.9ms preprocess, 159.0ms inference, 10.5ms postprocess per image at shape (1, 3, 640, 480) [-] ADetailer: nothing detected on image 1 with 1st settings. 0: 640x480 (no detections), 8.0ms Speed: 2.4ms preprocess, 8.0ms inference, 0.8ms postprocess per image at shape (1, 3, 640, 480) [-] ADetailer: nothing detected on image 2 with 1st settings. 0: 640x480 (no detections), 7.8ms Speed: 2.3ms preprocess, 7.8ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 480) [-] ADetailer: nothing detected on image 3 with 1st settings. Uploading outputs... Finished.