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Cybergirls with Mix Fantasy
mix-fantasy:v3.0
evevalentine2017
evevalentine2017
·
12/12/2023
323
Input
prompt
Specify things to see in the output
Complex 3D render ultra detailed of a beautiful porcelain profile woman android face, cyborg, robotic parts, 150 mm, beautiful studio soft light, rim light, vibrant details, luxurious cyberpunk, hyperrealistic, anatomical, facial muscles, cable electric wires, microchip, elegant, octane render, H. R. Giger style, 8k, best quality, masterpiece, illustration, extremely detailed, CG, unity, (realistic, photo-realistic: 1.37), Amazing, finely detailed, masterpiece, best quality, official art, absurdres, incredibly absurdres, robot, silver helmet, full body, sitting, dynamic pose, wind, laboratory, binding, neon light, minimalism, dim lighting, <lora: more_details: 0.8>,
negative_prompt
Specify things to not see in the output
(more than 2 arms), (more than 2 legs), (more than 2 hands), (more than 2 feet), (worst quality:1.5), (low quality:1.5), (normal quality:1.5), lowres, bad anatomy, bad hands, normal quality, ((monochrome)), ((grayscale)), negative_hand-neg
num_outputs
Number of output images
4
width
Output image width
768
height
Output image height
768
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
0.55
detail
Enhance/diminish detail while keeping the overall style/character
0.1
brightness
Adjust brightness
0
contrast
Adjust contrast
0
saturation
Adjust saturation
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
2901975881
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
30
cfg_scale
Scale for classifier-free guidance
9
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
blessed2_fp16.safetensors
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
more_details.safetensors
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)
negative_hand-neg.pt
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/6e1fbf604475435fb2026863164b6dfc/00000-2901975881.webp
https://files.tungsten.run/uploads/ee055fb49d6448bba63de0bd166c3350/00001-2901975882.webp
https://files.tungsten.run/uploads/cab463f1a4b24521a0a3856c52122902/00002-2901975883.webp
https://files.tungsten.run/uploads/f6004165e0ea48a4a51eabdf9cfae4f8/00003-2901975884.webp
Finished in 100.3 seconds
v3.0: Pulling from evevalentine2017/mix-fantasy 578acb154839: Already exists ac65017cfc56: Already exists 146269b80f9c: Already exists b51bc62cc3ca: Already exists 4ba34dd48a55: Already exists 2c0d7edf2b4f: Already exists bd3aa092d934: Already exists a2a0b079260c: Already exists 48e8a1cea0b1: Already exists 607175607db9: Already exists 44762e60be28: Already exists d1e8a6995bc7: Already exists 8915fc22d7d8: Already exists e186b03af121: Already exists 4f4fb700ef54: Already exists 030de23c0760: Pull complete 688188af0ba0: Pull complete c8389b9d9270: Pull complete 9221a4a9aae3: Pull complete Setting up the model... Processing... Loading VAE weight: models/VAE/blessed2_fp16.safetensors Full prompt: Complex 3D render ultra detailed of a beautiful porcelain profile woman android face, cyborg, robotic parts, 150 mm, beautiful studio soft light, rim light, vibrant details, luxurious cyberpunk, hyperrealistic, anatomical, facial muscles, cable electric wires, microchip, elegant, octane render, H. R. Giger style, 8k, best quality, masterpiece, illustration, extremely detailed, CG, unity, (realistic, photo-realistic: 1.37), Amazing, finely detailed, masterpiece, best quality, official art, absurdres, incredibly absurdres, robot, silver helmet, full body, sitting, dynamic pose, wind, laboratory, binding, neon light, minimalism, dim lighting, <lora: more_details: 0.8>,, <lora:add_detail:0.1> Full negative prompt: (more than 2 arms), (more than 2 legs), (more than 2 hands), (more than 2 feet), (worst quality:1.5), (low quality:1.5), (normal quality:1.5), lowres, bad anatomy, bad hands, normal quality, ((monochrome)), ((grayscale)), negative_hand-neg Couldn't find network with name more_details 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:01<00:36, 1.25s/it] 7%|▋ | 2/30 [00:01<00:25, 1.12it/s] 10%|█ | 3/30 [00:02<00:20, 1.29it/s] 13%|█▎ | 4/30 [00:03<00:18, 1.38it/s] 17%|█▋ | 5/30 [00:03<00:17, 1.44it/s] 20%|██ | 6/30 [00:04<00:16, 1.47it/s] 23%|██▎ | 7/30 [00:05<00:15, 1.50it/s] 27%|██▋ | 8/30 [00:05<00:14, 1.51it/s] 30%|███ | 9/30 [00:06<00:13, 1.51it/s] 33%|███▎ | 10/30 [00:07<00:13, 1.52it/s] 37%|███▋ | 11/30 [00:07<00:12, 1.53it/s] 40%|████ | 12/30 [00:08<00:11, 1.53it/s] 43%|████▎ | 13/30 [00:09<00:11, 1.54it/s] 47%|████▋ | 14/30 [00:09<00:10, 1.54it/s] 50%|█████ | 15/30 [00:10<00:09, 1.54it/s] 53%|█████▎ | 16/30 [00:10<00:09, 1.54it/s] 57%|█████▋ | 17/30 [00:11<00:08, 1.54it/s] 60%|██████ | 18/30 [00:12<00:07, 1.54it/s] 63%|██████▎ | 19/30 [00:12<00:07, 1.54it/s] 67%|██████▋ | 20/30 [00:13<00:06, 1.54it/s] 70%|███████ | 21/30 [00:14<00:05, 1.54it/s] 73%|███████▎ | 22/30 [00:14<00:05, 1.53it/s] 77%|███████▋ | 23/30 [00:15<00:04, 1.53it/s] 80%|████████ | 24/30 [00:16<00:03, 1.53it/s] 83%|████████▎ | 25/30 [00:16<00:03, 1.53it/s] 87%|████████▋ | 26/30 [00:17<00:02, 1.53it/s] 90%|█████████ | 27/30 [00:18<00:01, 1.53it/s] 93%|█████████▎| 28/30 [00:18<00:01, 1.53it/s] 97%|█████████▋| 29/30 [00:19<00:00, 1.53it/s] 100%|██████████| 30/30 [00:20<00:00, 1.54it/s] 100%|██████████| 30/30 [00:20<00:00, 1.49it/s] Decoding latents in cuda:0... done in 0.98s Move latents to cpu... done in 0.02s 0: 640x640 1 face, 8.5ms Speed: 5.5ms preprocess, 8.5ms inference, 33.1ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:06, 2.45it/s] 12%|█▏ | 2/17 [00:00<00:04, 3.39it/s] 18%|█▊ | 3/17 [00:00<00:03, 3.91it/s] 24%|██▎ | 4/17 [00:01<00:03, 4.22it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.44it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.60it/s] 41%|████ | 7/17 [00:01<00:02, 4.63it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.71it/s] 53%|█████▎ | 9/17 [00:02<00:01, 4.76it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.79it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.83it/s] 71%|███████ | 12/17 [00:02<00:01, 4.78it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.83it/s] 82%|████████▏ | 14/17 [00:03<00:00, 4.86it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.88it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.86it/s] 100%|██████████| 17/17 [00:03<00:00, 4.87it/s] 100%|██████████| 17/17 [00:03<00:00, 4.58it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.01s 0: 640x640 2 hands, 7.1ms Speed: 2.8ms preprocess, 7.1ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.92it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.83it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.87it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.88it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.74it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.81it/s] 41%|████ | 7/17 [00:01<00:02, 4.83it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.85it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.87it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.81it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.84it/s] 71%|███████ | 12/17 [00:02<00:01, 4.86it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.83it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.75it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.77it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.77it/s] 100%|██████████| 17/17 [00:03<00:00, 4.84it/s] 100%|██████████| 17/17 [00:03<00:00, 4.82it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.89it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.93it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.94it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.94it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.76it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.81it/s] 41%|████ | 7/17 [00:01<00:02, 4.84it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.86it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.86it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.79it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.85it/s] 71%|███████ | 12/17 [00:02<00:01, 4.89it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.93it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.95it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.83it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.88it/s] 100%|██████████| 17/17 [00:03<00:00, 4.95it/s] 100%|██████████| 17/17 [00:03<00:00, 4.88it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s 0: 640x640 1 face, 7.8ms Speed: 3.1ms preprocess, 7.8ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.92it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.91it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.91it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.93it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.93it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.91it/s] 41%|████ | 7/17 [00:01<00:02, 4.87it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.78it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.83it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.82it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.82it/s] 71%|███████ | 12/17 [00:02<00:01, 4.69it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.67it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.74it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.78it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.78it/s] 100%|██████████| 17/17 [00:03<00:00, 4.84it/s] 100%|██████████| 17/17 [00:03<00:00, 4.82it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s 0: 640x640 4 hands, 7.0ms Speed: 2.8ms preprocess, 7.0ms inference, 1.9ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.99it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.95it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.93it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.93it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.91it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.94it/s] 41%|████ | 7/17 [00:01<00:02, 4.95it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.96it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.96it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.94it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.95it/s] 71%|███████ | 12/17 [00:02<00:01, 4.95it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.97it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.96it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.95it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.89it/s] 100%|██████████| 17/17 [00:03<00:00, 4.96it/s] 100%|██████████| 17/17 [00:03<00:00, 4.95it/s] Decoding latents in cuda:0... =========================================== A tensor with all NaNs was produced in VAE. Converted VAE into 32-bit float and retry. =========================================== done in 0.45s Move latents to cpu... done in 0.23s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.91it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.94it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.92it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.91it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.92it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.93it/s] 41%|████ | 7/17 [00:01<00:02, 4.93it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.92it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.88it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.78it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.81it/s] 71%|███████ | 12/17 [00:02<00:01, 4.81it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.82it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.85it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.86it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.87it/s] 100%|██████████| 17/17 [00:03<00:00, 4.92it/s] 100%|██████████| 17/17 [00:03<00:00, 4.88it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.77it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.82it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.86it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.81it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.81it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.76it/s] 41%|████ | 7/17 [00:01<00:02, 4.78it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.80it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.72it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.78it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.82it/s] 71%|███████ | 12/17 [00:02<00:01, 4.85it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.89it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.84it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.87it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.87it/s] 100%|██████████| 17/17 [00:03<00:00, 4.91it/s] 100%|██████████| 17/17 [00:03<00:00, 4.83it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.78it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.85it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.88it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.70it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.74it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.81it/s] 41%|████ | 7/17 [00:01<00:02, 4.83it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.83it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.83it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.83it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.87it/s] 71%|███████ | 12/17 [00:02<00:01, 4.89it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.87it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.82it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.82it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.77it/s] 100%|██████████| 17/17 [00:03<00:00, 4.75it/s] 100%|██████████| 17/17 [00:03<00:00, 4.81it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0: 640x640 1 face, 7.8ms Speed: 2.9ms preprocess, 7.8ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.87it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.91it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.94it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.81it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.83it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.82it/s] 41%|████ | 7/17 [00:01<00:02, 4.81it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.82it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.68it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.63it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.71it/s] 71%|███████ | 12/17 [00:02<00:01, 4.77it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.81it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.66it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.74it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.76it/s] 100%|██████████| 17/17 [00:03<00:00, 4.84it/s] 100%|██████████| 17/17 [00:03<00:00, 4.78it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s 0: 640x640 1 hand, 7.0ms Speed: 2.9ms preprocess, 7.0ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.88it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.85it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.87it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.88it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.87it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.87it/s] 41%|████ | 7/17 [00:01<00:02, 4.88it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.87it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.88it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.89it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.90it/s] 71%|███████ | 12/17 [00:02<00:01, 4.91it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.89it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.79it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.77it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.80it/s] 100%|██████████| 17/17 [00:03<00:00, 4.80it/s] 100%|██████████| 17/17 [00:03<00:00, 4.85it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0: 640x640 2 faces, 7.4ms Speed: 2.7ms preprocess, 7.4ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.74it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.83it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.85it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.77it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.77it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.80it/s] 41%|████ | 7/17 [00:01<00:02, 4.81it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.81it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.75it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.79it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.85it/s] 71%|███████ | 12/17 [00:02<00:01, 4.85it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.81it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.75it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.79it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.82it/s] 100%|██████████| 17/17 [00:03<00:00, 4.81it/s] 100%|██████████| 17/17 [00:03<00:00, 4.80it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s 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per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.58it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.76it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.82it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.87it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.89it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.81it/s] 41%|████ | 7/17 [00:01<00:02, 4.83it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.85it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.84it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.80it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.82it/s] 71%|███████ | 12/17 [00:02<00:01, 4.82it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.83it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.82it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.83it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.81it/s] 100%|██████████| 17/17 [00:03<00:00, 4.85it/s] 100%|██████████| 17/17 [00:03<00:00, 4.83it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s Couldn't find network with name more_details 0%| | 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4.80it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.81it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.81it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.57it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.60it/s] 41%|████ | 7/17 [00:01<00:02, 4.67it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.69it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.69it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.65it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.74it/s] 71%|███████ | 12/17 [00:02<00:01, 4.74it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.77it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.75it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.73it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.78it/s] 100%|██████████| 17/17 [00:03<00:00, 4.83it/s] 100%|██████████| 17/17 [00:03<00:00, 4.74it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s Finished.
prompt
Specify things to see in the output
Complex 3D render ultra detailed of a beautiful porcelain profile woman android face, cyborg, robotic parts, 150 mm, beautiful studio soft light, rim light, vibrant details, luxurious cyberpunk, hyperrealistic, anatomical, facial muscles, cable electric wires, microchip, elegant, octane render, H. R. Giger style, 8k, best quality, masterpiece, illustration, extremely detailed, CG, unity, (realistic, photo-realistic: 1.37), Amazing, finely detailed, masterpiece, best quality, official art, absurdres, incredibly absurdres, robot, silver helmet, full body, sitting, dynamic pose, wind, laboratory, binding, neon light, minimalism, dim lighting, <lora: more_details: 0.8>,
negative_prompt
Specify things to not see in the output
(more than 2 arms), (more than 2 legs), (more than 2 hands), (more than 2 feet), (worst quality:1.5), (low quality:1.5), (normal quality:1.5), lowres, bad anatomy, bad hands, normal quality, ((monochrome)), ((grayscale)), negative_hand-neg
num_outputs
Number of output images
4
width
Output image width
768
height
Output image height
768
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
0.55
detail
Enhance/diminish detail while keeping the overall style/character
0.1
brightness
Adjust brightness
0
contrast
Adjust contrast
0
saturation
Adjust saturation
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
2901975881
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
30
cfg_scale
Scale for classifier-free guidance
9
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
blessed2_fp16.safetensors
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
more_details.safetensors
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)
negative_hand-neg.pt
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/6e1fbf604475435fb2026863164b6dfc/00000-2901975881.webp
https://files.tungsten.run/uploads/ee055fb49d6448bba63de0bd166c3350/00001-2901975882.webp
https://files.tungsten.run/uploads/cab463f1a4b24521a0a3856c52122902/00002-2901975883.webp
https://files.tungsten.run/uploads/f6004165e0ea48a4a51eabdf9cfae4f8/00003-2901975884.webp
Finished in 100.3 seconds
v3.0: Pulling from evevalentine2017/mix-fantasy 578acb154839: Already exists ac65017cfc56: Already exists 146269b80f9c: Already exists b51bc62cc3ca: Already exists 4ba34dd48a55: Already exists 2c0d7edf2b4f: Already exists bd3aa092d934: Already exists a2a0b079260c: Already exists 48e8a1cea0b1: Already exists 607175607db9: Already exists 44762e60be28: Already exists d1e8a6995bc7: Already exists 8915fc22d7d8: Already exists e186b03af121: Already exists 4f4fb700ef54: Already exists 030de23c0760: Pull complete 688188af0ba0: Pull complete c8389b9d9270: Pull complete 9221a4a9aae3: Pull complete Setting up the model... Processing... Loading VAE weight: models/VAE/blessed2_fp16.safetensors Full prompt: Complex 3D render ultra detailed of a beautiful porcelain profile woman android face, cyborg, robotic parts, 150 mm, beautiful studio soft light, rim light, vibrant details, luxurious cyberpunk, hyperrealistic, anatomical, facial muscles, cable electric wires, microchip, elegant, octane render, H. R. Giger style, 8k, best quality, masterpiece, illustration, extremely detailed, CG, unity, (realistic, photo-realistic: 1.37), Amazing, finely detailed, masterpiece, best quality, official art, absurdres, incredibly absurdres, robot, silver helmet, full body, sitting, dynamic pose, wind, laboratory, binding, neon light, minimalism, dim lighting, <lora: more_details: 0.8>,, <lora:add_detail:0.1> Full negative prompt: (more than 2 arms), (more than 2 legs), (more than 2 hands), (more than 2 feet), (worst quality:1.5), (low quality:1.5), (normal quality:1.5), lowres, bad anatomy, bad hands, normal quality, ((monochrome)), ((grayscale)), negative_hand-neg Couldn't find network with name more_details 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:01<00:36, 1.25s/it] 7%|▋ | 2/30 [00:01<00:25, 1.12it/s] 10%|█ | 3/30 [00:02<00:20, 1.29it/s] 13%|█▎ | 4/30 [00:03<00:18, 1.38it/s] 17%|█▋ | 5/30 [00:03<00:17, 1.44it/s] 20%|██ | 6/30 [00:04<00:16, 1.47it/s] 23%|██▎ | 7/30 [00:05<00:15, 1.50it/s] 27%|██▋ 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100%|██████████| 30/30 [00:20<00:00, 1.49it/s] Decoding latents in cuda:0... done in 0.98s Move latents to cpu... done in 0.02s 0: 640x640 1 face, 8.5ms Speed: 5.5ms preprocess, 8.5ms inference, 33.1ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:06, 2.45it/s] 12%|█▏ | 2/17 [00:00<00:04, 3.39it/s] 18%|█▊ | 3/17 [00:00<00:03, 3.91it/s] 24%|██▎ | 4/17 [00:01<00:03, 4.22it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.44it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.60it/s] 41%|████ | 7/17 [00:01<00:02, 4.63it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.71it/s] 53%|█████▎ | 9/17 [00:02<00:01, 4.76it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.79it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.83it/s] 71%|███████ | 12/17 [00:02<00:01, 4.78it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.83it/s] 82%|████████▏ | 14/17 [00:03<00:00, 4.86it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.88it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.86it/s] 100%|██████████| 17/17 [00:03<00:00, 4.87it/s] 100%|██████████| 17/17 [00:03<00:00, 4.58it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.01s 0: 640x640 2 hands, 7.1ms Speed: 2.8ms preprocess, 7.1ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.92it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.83it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.87it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.88it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.74it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.81it/s] 41%|████ | 7/17 [00:01<00:02, 4.83it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.85it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.87it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.81it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.84it/s] 71%|███████ | 12/17 [00:02<00:01, 4.86it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.83it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.75it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.77it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.77it/s] 100%|██████████| 17/17 [00:03<00:00, 4.84it/s] 100%|██████████| 17/17 [00:03<00:00, 4.82it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.89it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.93it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.94it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.94it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.76it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.81it/s] 41%|████ | 7/17 [00:01<00:02, 4.84it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.86it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.86it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.79it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.85it/s] 71%|███████ | 12/17 [00:02<00:01, 4.89it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.93it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.95it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.83it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.88it/s] 100%|██████████| 17/17 [00:03<00:00, 4.95it/s] 100%|██████████| 17/17 [00:03<00:00, 4.88it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s 0: 640x640 1 face, 7.8ms Speed: 3.1ms preprocess, 7.8ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.92it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.91it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.91it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.93it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.93it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.91it/s] 41%|████ | 7/17 [00:01<00:02, 4.87it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.78it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.83it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.82it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.82it/s] 71%|███████ | 12/17 [00:02<00:01, 4.69it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.67it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.74it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.78it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.78it/s] 100%|██████████| 17/17 [00:03<00:00, 4.84it/s] 100%|██████████| 17/17 [00:03<00:00, 4.82it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s 0: 640x640 4 hands, 7.0ms Speed: 2.8ms preprocess, 7.0ms inference, 1.9ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.99it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.95it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.93it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.93it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.91it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.94it/s] 41%|████ | 7/17 [00:01<00:02, 4.95it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.96it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.96it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.94it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.95it/s] 71%|███████ | 12/17 [00:02<00:01, 4.95it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.97it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.96it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.95it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.89it/s] 100%|██████████| 17/17 [00:03<00:00, 4.96it/s] 100%|██████████| 17/17 [00:03<00:00, 4.95it/s] Decoding latents in cuda:0... =========================================== A tensor with all NaNs was produced in VAE. Converted VAE into 32-bit float and retry. =========================================== done in 0.45s Move latents to cpu... done in 0.23s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.91it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.94it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.92it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.91it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.92it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.93it/s] 41%|████ | 7/17 [00:01<00:02, 4.93it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.92it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.88it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.78it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.81it/s] 71%|███████ | 12/17 [00:02<00:01, 4.81it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.82it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.85it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.86it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.87it/s] 100%|██████████| 17/17 [00:03<00:00, 4.92it/s] 100%|██████████| 17/17 [00:03<00:00, 4.88it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.77it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.82it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.86it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.81it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.81it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.76it/s] 41%|████ | 7/17 [00:01<00:02, 4.78it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.80it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.72it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.78it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.82it/s] 71%|███████ | 12/17 [00:02<00:01, 4.85it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.89it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.84it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.87it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.87it/s] 100%|██████████| 17/17 [00:03<00:00, 4.91it/s] 100%|██████████| 17/17 [00:03<00:00, 4.83it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.78it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.85it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.88it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.70it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.74it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.81it/s] 41%|████ | 7/17 [00:01<00:02, 4.83it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.83it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.83it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.83it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.87it/s] 71%|███████ | 12/17 [00:02<00:01, 4.89it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.87it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.82it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.82it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.77it/s] 100%|██████████| 17/17 [00:03<00:00, 4.75it/s] 100%|██████████| 17/17 [00:03<00:00, 4.81it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0: 640x640 1 face, 7.8ms Speed: 2.9ms preprocess, 7.8ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.87it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.91it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.94it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.81it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.83it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.82it/s] 41%|████ | 7/17 [00:01<00:02, 4.81it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.82it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.68it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.63it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.71it/s] 71%|███████ | 12/17 [00:02<00:01, 4.77it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.81it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.66it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.74it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.76it/s] 100%|██████████| 17/17 [00:03<00:00, 4.84it/s] 100%|██████████| 17/17 [00:03<00:00, 4.78it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s 0: 640x640 1 hand, 7.0ms Speed: 2.9ms preprocess, 7.0ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.88it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.85it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.87it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.88it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.87it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.87it/s] 41%|████ | 7/17 [00:01<00:02, 4.88it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.87it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.88it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.89it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.90it/s] 71%|███████ | 12/17 [00:02<00:01, 4.91it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.89it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.79it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.77it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.80it/s] 100%|██████████| 17/17 [00:03<00:00, 4.80it/s] 100%|██████████| 17/17 [00:03<00:00, 4.85it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0: 640x640 2 faces, 7.4ms Speed: 2.7ms preprocess, 7.4ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.74it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.83it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.85it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.77it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.77it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.80it/s] 41%|████ | 7/17 [00:01<00:02, 4.81it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.81it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.75it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.79it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.85it/s] 71%|███████ | 12/17 [00:02<00:01, 4.85it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.81it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.75it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.79it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.82it/s] 100%|██████████| 17/17 [00:03<00:00, 4.81it/s] 100%|██████████| 17/17 [00:03<00:00, 4.80it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.81it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.90it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.77it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.79it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.78it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.82it/s] 41%|████ | 7/17 [00:01<00:02, 4.84it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.84it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.84it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.86it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.87it/s] 71%|███████ | 12/17 [00:02<00:01, 4.89it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.77it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.79it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.83it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.85it/s] 100%|██████████| 17/17 [00:03<00:00, 4.91it/s] 100%|██████████| 17/17 [00:03<00:00, 4.84it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s 0: 640x640 3 hands, 7.0ms Speed: 2.8ms preprocess, 7.0ms inference, 1.8ms postprocess per image at shape (1, 3, 640, 640) Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.58it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.76it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.82it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.87it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.89it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.81it/s] 41%|████ | 7/17 [00:01<00:02, 4.83it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.85it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.84it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.80it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.82it/s] 71%|███████ | 12/17 [00:02<00:01, 4.82it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.83it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.82it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.83it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.81it/s] 100%|██████████| 17/17 [00:03<00:00, 4.85it/s] 100%|██████████| 17/17 [00:03<00:00, 4.83it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.78it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.85it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.88it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.83it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.84it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.86it/s] 41%|████ | 7/17 [00:01<00:02, 4.88it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.87it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.89it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.82it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.82it/s] 71%|███████ | 12/17 [00:02<00:01, 4.83it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.86it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.84it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.72it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.78it/s] 100%|██████████| 17/17 [00:03<00:00, 4.86it/s] 100%|██████████| 17/17 [00:03<00:00, 4.84it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s Couldn't find network with name more_details 0%| | 0/17 [00:00<?, ?it/s] 6%|▌ | 1/17 [00:00<00:03, 4.73it/s] 12%|█▏ | 2/17 [00:00<00:03, 4.80it/s] 18%|█▊ | 3/17 [00:00<00:02, 4.81it/s] 24%|██▎ | 4/17 [00:00<00:02, 4.81it/s] 29%|██▉ | 5/17 [00:01<00:02, 4.57it/s] 35%|███▌ | 6/17 [00:01<00:02, 4.60it/s] 41%|████ | 7/17 [00:01<00:02, 4.67it/s] 47%|████▋ | 8/17 [00:01<00:01, 4.69it/s] 53%|█████▎ | 9/17 [00:01<00:01, 4.69it/s] 59%|█████▉ | 10/17 [00:02<00:01, 4.65it/s] 65%|██████▍ | 11/17 [00:02<00:01, 4.74it/s] 71%|███████ | 12/17 [00:02<00:01, 4.74it/s] 76%|███████▋ | 13/17 [00:02<00:00, 4.77it/s] 82%|████████▏ | 14/17 [00:02<00:00, 4.75it/s] 88%|████████▊ | 15/17 [00:03<00:00, 4.73it/s] 94%|█████████▍| 16/17 [00:03<00:00, 4.78it/s] 100%|██████████| 17/17 [00:03<00:00, 4.83it/s] 100%|██████████| 17/17 [00:03<00:00, 4.74it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s Finished.