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Girls by a Pool with Realism Engine SDXL
realism-engine-sdxl:v3.0
evevalentine2017
evevalentine2017
·
Feb 1
350
Input
prompt
Specify things to see in the output
professional painting by Alayna Lemmer of a girl wearing slingship bikini, walking by a pool. Smooth focus on the girl, dynamic pose, dynamic background, dynamic composition, dynamic lighting, realistic proportions, intricate details, 16k resolution, hdr, raytracing.
negative_prompt
Specify things to not see in the output
(worst quality:1.4), (low quality:1.4), (normal quality:1.4), (makeup, ugly, underwear, swimsuit, clothes), ear, hand, finger, nail, tail, claw, paw, tentacle, fin, narrow hips, skinny, depth of field, bokeh, perfect, (looking at viewer:1.7), thin,
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.
2059310518
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
70
cfg_scale
Scale for classifier-free guidance
3
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
https://files.tungsten.run/uploads/ae0f3b2284e04af69a893d3459102878/00000-2059310518.webp
https://files.tungsten.run/uploads/7ac0b46c79694520bff61edbb217b25a/00001-2059310519.webp
https://files.tungsten.run/uploads/e775f8e62fb64f558468f7d66ec1f150/00002-2059310520.webp
Finished in 200.8 seconds
Preparing inputs... Processing... Full prompt: professional painting by Alayna Lemmer of a girl wearing slingship bikini, walking by a pool. Smooth focus on the girl, dynamic pose, dynamic background, dynamic composition, dynamic lighting, realistic proportions, intricate details, 16k resolution, hdr, raytracing. Full negative prompt: (worst quality:1.4), (low quality:1.4), (normal quality:1.4), (makeup, ugly, underwear, swimsuit, clothes), ear, hand, finger, nail, tail, claw, paw, tentacle, fin, narrow hips, skinny, depth of field, bokeh, perfect, (looking at viewer:1.7), thin, 0%| | 0/70 [00:00<?, ?it/s] 1%|▏ | 1/70 [00:01<01:47, 1.56s/it] 3%|▎ | 2/70 [00:03<02:02, 1.81s/it] 4%|▍ | 3/70 [00:05<02:11, 1.96s/it] 6%|▌ | 4/70 [00:07<02:12, 2.00s/it] 7%|▋ | 5/70 [00:09<02:12, 2.04s/it] 9%|▊ | 6/70 [00:12<02:12, 2.08s/it] 10%|█ | 7/70 [00:14<02:12, 2.10s/it] 11%|█▏ | 8/70 [00:16<02:09, 2.09s/it] 13%|█▎ | 9/70 [00:18<02:07, 2.09s/it] 14%|█▍ | 10/70 [00:20<02:03, 2.05s/it] 16%|█▌ | 11/70 [00:22<02:02, 2.07s/it] 17%|█▋ | 12/70 [00:24<02:01, 2.09s/it] 19%|█▊ | 13/70 [00:26<01:58, 2.08s/it] 20%|██ | 14/70 [00:28<01:57, 2.09s/it] 21%|██▏ | 15/70 [00:30<01:53, 2.06s/it] 23%|██▎ | 16/70 [00:32<01:52, 2.09s/it] 24%|██▍ | 17/70 [00:34<01:46, 2.01s/it] 26%|██▌ | 18/70 [00:36<01:41, 1.94s/it] 27%|██▋ | 19/70 [00:38<01:40, 1.96s/it] 29%|██▊ | 20/70 [00:40<01:39, 2.00s/it] 30%|███ | 21/70 [00:42<01:39, 2.03s/it] 31%|███▏ | 22/70 [00:44<01:37, 2.04s/it] 33%|███▎ | 23/70 [00:46<01:37, 2.07s/it] 34%|███▍ | 24/70 [00:48<01:33, 2.04s/it] 36%|███▌ | 25/70 [00:50<01:32, 2.05s/it] 37%|███▋ | 26/70 [00:52<01:27, 1.99s/it] 39%|███▊ | 27/70 [00:54<01:24, 1.98s/it] 40%|████ | 28/70 [00:56<01:22, 1.97s/it] 41%|████▏ | 29/70 [00:58<01:21, 1.99s/it] 43%|████▎ | 30/70 [01:00<01:20, 2.01s/it] 44%|████▍ | 31/70 [01:02<01:19, 2.03s/it] 46%|████▌ | 32/70 [01:04<01:17, 2.04s/it] 47%|████▋ | 33/70 [01:06<01:14, 2.02s/it] 49%|████▊ | 34/70 [01:08<01:13, 2.03s/it] 50%|█████ | 35/70 [01:10<01:09, 1.98s/it] 51%|█████▏ | 36/70 [01:12<01:07, 1.99s/it] 53%|█████▎ | 37/70 [01:14<01:04, 1.95s/it] 54%|█████▍ | 38/70 [01:16<01:01, 1.92s/it] 56%|█████▌ | 39/70 [01:18<01:00, 1.96s/it] 57%|█████▋ | 40/70 [01:20<00:58, 1.94s/it] 59%|█████▊ | 41/70 [01:22<00:55, 1.93s/it] 60%|██████ | 42/70 [01:24<00:54, 1.95s/it] 61%|██████▏ | 43/70 [01:26<00:51, 1.92s/it] 63%|██████▎ | 44/70 [01:28<00:49, 1.92s/it] 64%|██████▍ | 45/70 [01:30<00:48, 1.94s/it] 66%|██████▌ | 46/70 [01:32<00:47, 1.98s/it] 67%|██████▋ | 47/70 [01:34<00:44, 1.95s/it] 69%|██████▊ | 48/70 [01:35<00:42, 1.94s/it] 70%|███████ | 49/70 [01:37<00:39, 1.86s/it] 71%|███████▏ | 50/70 [01:39<00:37, 1.88s/it] 73%|███████▎ | 51/70 [01:41<00:36, 1.90s/it] 74%|███████▍ | 52/70 [01:43<00:34, 1.93s/it] 76%|███████▌ | 53/70 [01:45<00:32, 1.91s/it] 77%|███████▋ | 54/70 [01:47<00:30, 1.92s/it] 79%|███████▊ | 55/70 [01:49<00:28, 1.90s/it] 80%|████████ | 56/70 [01:51<00:26, 1.88s/it] 81%|████████▏ | 57/70 [01:52<00:24, 1.87s/it] 83%|████████▎ | 58/70 [01:54<00:21, 1.83s/it] 84%|████████▍ | 59/70 [01:56<00:19, 1.78s/it] 86%|████████▌ | 60/70 [01:57<00:17, 1.76s/it] 87%|████████▋ | 61/70 [01:59<00:16, 1.81s/it] 89%|████████▊ | 62/70 [02:01<00:13, 1.75s/it] 90%|█████████ | 63/70 [02:03<00:12, 1.77s/it] 91%|█████████▏| 64/70 [02:05<00:10, 1.75s/it] 93%|█████████▎| 65/70 [02:06<00:08, 1.79s/it] 94%|█████████▍| 66/70 [02:08<00:06, 1.70s/it] 96%|█████████▌| 67/70 [02:10<00:05, 1.72s/it] 97%|█████████▋| 68/70 [02:11<00:03, 1.69s/it] 99%|█████████▊| 69/70 [02:12<00:01, 1.51s/it] 100%|██████████| 70/70 [02:13<00:00, 1.35s/it] 100%|██████████| 70/70 [02:13<00:00, 1.91s/it] Decoding latents in cuda:0... done in 1.75s Move latents to cpu... done in 0.01s 0%| | 0/32 [00:00<?, ?it/s] 3%|▎ | 1/32 [00:00<00:22, 1.38it/s] 6%|▋ | 2/32 [00:01<00:20, 1.49it/s] 9%|▉ | 3/32 [00:01<00:18, 1.53it/s] 12%|█▎ | 4/32 [00:02<00:18, 1.52it/s] 16%|█▌ | 5/32 [00:03<00:17, 1.53it/s] 19%|█▉ | 6/32 [00:03<00:17, 1.51it/s] 22%|██▏ | 7/32 [00:04<00:16, 1.49it/s] 25%|██▌ | 8/32 [00:05<00:16, 1.48it/s] 28%|██▊ | 9/32 [00:06<00:15, 1.49it/s] 31%|███▏ | 10/32 [00:06<00:14, 1.49it/s] 34%|███▍ | 11/32 [00:07<00:13, 1.57it/s] 38%|███▊ | 12/32 [00:07<00:12, 1.55it/s] 41%|████ | 13/32 [00:08<00:12, 1.54it/s] 44%|████▍ | 14/32 [00:09<00:11, 1.52it/s] 47%|████▋ | 15/32 [00:09<00:11, 1.54it/s] 50%|█████ | 16/32 [00:10<00:10, 1.53it/s] 53%|█████▎ | 17/32 [00:11<00:09, 1.56it/s] 56%|█████▋ | 18/32 [00:11<00:08, 1.57it/s] 59%|█████▉ | 19/32 [00:12<00:08, 1.58it/s] 62%|██████▎ | 20/32 [00:12<00:07, 1.62it/s] 66%|██████▌ | 21/32 [00:13<00:06, 1.66it/s] 69%|██████▉ | 22/32 [00:14<00:05, 1.68it/s] 72%|███████▏ | 23/32 [00:14<00:05, 1.63it/s] 75%|███████▌ | 24/32 [00:15<00:04, 1.70it/s] 78%|███████▊ | 25/32 [00:15<00:04, 1.68it/s] 81%|████████▏ | 26/32 [00:16<00:03, 1.70it/s] 84%|████████▍ | 27/32 [00:17<00:03, 1.66it/s] 88%|████████▊ | 28/32 [00:17<00:02, 1.73it/s] 91%|█████████ | 29/32 [00:18<00:01, 1.71it/s] 94%|█████████▍| 30/32 [00:18<00:01, 1.73it/s] 97%|█████████▋| 31/32 [00:19<00:00, 1.94it/s] 100%|██████████| 32/32 [00:19<00:00, 2.17it/s] 100%|██████████| 32/32 [00:19<00:00, 1.64it/s] Decoding latents in cuda:0... done in 0.58s Move latents to cpu... done in 0.0s 0%| | 0/32 [00:00<?, ?it/s] 3%|▎ | 1/32 [00:00<00:21, 1.43it/s] 6%|▋ | 2/32 [00:01<00:20, 1.50it/s] 9%|▉ | 3/32 [00:01<00:19, 1.52it/s] 12%|█▎ | 4/32 [00:02<00:18, 1.51it/s] 16%|█▌ | 5/32 [00:03<00:17, 1.55it/s] 19%|█▉ | 6/32 [00:03<00:16, 1.57it/s] 22%|██▏ | 7/32 [00:04<00:16, 1.55it/s] 25%|██▌ | 8/32 [00:05<00:15, 1.51it/s] 28%|██▊ | 9/32 [00:05<00:15, 1.52it/s] 31%|███▏ | 10/32 [00:06<00:14, 1.53it/s] 34%|███▍ | 11/32 [00:07<00:13, 1.57it/s] 38%|███▊ | 12/32 [00:07<00:12, 1.54it/s] 41%|████ | 13/32 [00:08<00:12, 1.51it/s] 44%|████▍ | 14/32 [00:09<00:12, 1.48it/s] 47%|████▋ | 15/32 [00:09<00:11, 1.49it/s] 50%|█████ | 16/32 [00:10<00:10, 1.48it/s] 53%|█████▎ | 17/32 [00:11<00:09, 1.52it/s] 56%|█████▋ | 18/32 [00:11<00:09, 1.55it/s] 59%|█████▉ | 19/32 [00:12<00:08, 1.54it/s] 62%|██████▎ | 20/32 [00:13<00:07, 1.56it/s] 66%|██████▌ | 21/32 [00:13<00:06, 1.60it/s] 69%|██████▉ | 22/32 [00:14<00:06, 1.61it/s] 72%|███████▏ | 23/32 [00:14<00:05, 1.59it/s] 75%|███████▌ | 24/32 [00:15<00:04, 1.66it/s] 78%|███████▊ | 25/32 [00:16<00:04, 1.65it/s] 81%|████████▏ | 26/32 [00:16<00:03, 1.68it/s] 84%|████████▍ | 27/32 [00:17<00:03, 1.64it/s] 88%|████████▊ | 28/32 [00:17<00:02, 1.73it/s] 91%|█████████ | 29/32 [00:18<00:01, 1.72it/s] 94%|█████████▍| 30/32 [00:19<00:01, 1.69it/s] 97%|█████████▋| 31/32 [00:19<00:00, 1.89it/s] 100%|██████████| 32/32 [00:19<00:00, 2.13it/s] 100%|██████████| 32/32 [00:19<00:00, 1.62it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s 0%| | 0/32 [00:00<?, ?it/s] 3%|▎ | 1/32 [00:00<00:21, 1.47it/s] 6%|▋ | 2/32 [00:01<00:19, 1.52it/s] 9%|▉ | 3/32 [00:01<00:18, 1.54it/s] 12%|█▎ | 4/32 [00:02<00:18, 1.52it/s] 16%|█▌ | 5/32 [00:03<00:17, 1.52it/s] 19%|█▉ | 6/32 [00:03<00:16, 1.54it/s] 22%|██▏ | 7/32 [00:04<00:16, 1.53it/s] 25%|██▌ | 8/32 [00:05<00:15, 1.51it/s] 28%|██▊ | 9/32 [00:05<00:15, 1.52it/s] 31%|███▏ | 10/32 [00:06<00:14, 1.53it/s] 34%|███▍ | 11/32 [00:07<00:13, 1.59it/s] 38%|███▊ | 12/32 [00:07<00:13, 1.49it/s] 41%|████ | 13/32 [00:08<00:13, 1.44it/s] 44%|████▍ | 14/32 [00:09<00:12, 1.46it/s] 47%|████▋ | 15/32 [00:09<00:11, 1.50it/s] 50%|█████ | 16/32 [00:10<00:10, 1.51it/s] 53%|█████▎ | 17/32 [00:11<00:09, 1.54it/s] 56%|█████▋ | 18/32 [00:11<00:09, 1.53it/s] 59%|█████▉ | 19/32 [00:12<00:08, 1.53it/s] 62%|██████▎ | 20/32 [00:13<00:07, 1.55it/s] 66%|██████▌ | 21/32 [00:13<00:06, 1.60it/s] 69%|██████▉ | 22/32 [00:14<00:06, 1.61it/s] 72%|███████▏ | 23/32 [00:15<00:05, 1.58it/s] 75%|███████▌ | 24/32 [00:15<00:04, 1.63it/s] 78%|███████▊ | 25/32 [00:16<00:04, 1.58it/s] 81%|████████▏ | 26/32 [00:16<00:03, 1.61it/s] 84%|████████▍ | 27/32 [00:17<00:03, 1.56it/s] 88%|████████▊ | 28/32 [00:18<00:02, 1.65it/s] 91%|█████████ | 29/32 [00:18<00:01, 1.65it/s] 94%|█████████▍| 30/32 [00:19<00:01, 1.66it/s] 97%|█████████▋| 31/32 [00:19<00:00, 1.84it/s] 100%|██████████| 32/32 [00:20<00:00, 2.03it/s] 100%|██████████| 32/32 [00:20<00:00, 1.60it/s] Decoding latents in cuda:0... done in 0.58s Move latents to cpu... done in 0.0s Uploading outputs... Finished.
prompt
Specify things to see in the output
professional painting by Alayna Lemmer of a girl wearing slingship bikini, walking by a pool. Smooth focus on the girl, dynamic pose, dynamic background, dynamic composition, dynamic lighting, realistic proportions, intricate details, 16k resolution, hdr, raytracing.
negative_prompt
Specify things to not see in the output
(worst quality:1.4), (low quality:1.4), (normal quality:1.4), (makeup, ugly, underwear, swimsuit, clothes), ear, hand, finger, nail, tail, claw, paw, tentacle, fin, narrow hips, skinny, depth of field, bokeh, perfect, (looking at viewer:1.7), thin,
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.
2059310518
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
70
cfg_scale
Scale for classifier-free guidance
3
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
https://files.tungsten.run/uploads/ae0f3b2284e04af69a893d3459102878/00000-2059310518.webp
https://files.tungsten.run/uploads/7ac0b46c79694520bff61edbb217b25a/00001-2059310519.webp
https://files.tungsten.run/uploads/e775f8e62fb64f558468f7d66ec1f150/00002-2059310520.webp
Finished in 200.8 seconds
Preparing inputs... Processing... Full prompt: professional painting by Alayna Lemmer of a girl wearing slingship bikini, walking by a pool. Smooth focus on the girl, dynamic pose, dynamic background, dynamic composition, dynamic lighting, realistic proportions, intricate details, 16k resolution, hdr, raytracing. Full negative prompt: (worst quality:1.4), (low quality:1.4), (normal quality:1.4), (makeup, ugly, underwear, swimsuit, clothes), ear, hand, finger, nail, tail, claw, paw, tentacle, fin, narrow hips, skinny, depth of field, bokeh, perfect, (looking at viewer:1.7), thin, 0%| | 0/70 [00:00<?, ?it/s] 1%|▏ | 1/70 [00:01<01:47, 1.56s/it] 3%|▎ | 2/70 [00:03<02:02, 1.81s/it] 4%|▍ | 3/70 [00:05<02:11, 1.96s/it] 6%|▌ | 4/70 [00:07<02:12, 2.00s/it] 7%|▋ | 5/70 [00:09<02:12, 2.04s/it] 9%|▊ | 6/70 [00:12<02:12, 2.08s/it] 10%|█ | 7/70 [00:14<02:12, 2.10s/it] 11%|█▏ | 8/70 [00:16<02:09, 2.09s/it] 13%|█▎ | 9/70 [00:18<02:07, 2.09s/it] 14%|█▍ | 10/70 [00:20<02:03, 2.05s/it] 16%|█▌ | 11/70 [00:22<02:02, 2.07s/it] 17%|█▋ | 12/70 [00:24<02:01, 2.09s/it] 19%|█▊ | 13/70 [00:26<01:58, 2.08s/it] 20%|██ | 14/70 [00:28<01:57, 2.09s/it] 21%|██▏ | 15/70 [00:30<01:53, 2.06s/it] 23%|██▎ | 16/70 [00:32<01:52, 2.09s/it] 24%|██▍ | 17/70 [00:34<01:46, 2.01s/it] 26%|██▌ | 18/70 [00:36<01:41, 1.94s/it] 27%|██▋ | 19/70 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43/70 [01:26<00:51, 1.92s/it] 63%|██████▎ | 44/70 [01:28<00:49, 1.92s/it] 64%|██████▍ | 45/70 [01:30<00:48, 1.94s/it] 66%|██████▌ | 46/70 [01:32<00:47, 1.98s/it] 67%|██████▋ | 47/70 [01:34<00:44, 1.95s/it] 69%|██████▊ | 48/70 [01:35<00:42, 1.94s/it] 70%|███████ | 49/70 [01:37<00:39, 1.86s/it] 71%|███████▏ | 50/70 [01:39<00:37, 1.88s/it] 73%|███████▎ | 51/70 [01:41<00:36, 1.90s/it] 74%|███████▍ | 52/70 [01:43<00:34, 1.93s/it] 76%|███████▌ | 53/70 [01:45<00:32, 1.91s/it] 77%|███████▋ | 54/70 [01:47<00:30, 1.92s/it] 79%|███████▊ | 55/70 [01:49<00:28, 1.90s/it] 80%|████████ | 56/70 [01:51<00:26, 1.88s/it] 81%|████████▏ | 57/70 [01:52<00:24, 1.87s/it] 83%|████████▎ | 58/70 [01:54<00:21, 1.83s/it] 84%|████████▍ | 59/70 [01:56<00:19, 1.78s/it] 86%|████████▌ | 60/70 [01:57<00:17, 1.76s/it] 87%|████████▋ | 61/70 [01:59<00:16, 1.81s/it] 89%|████████▊ | 62/70 [02:01<00:13, 1.75s/it] 90%|█████████ | 63/70 [02:03<00:12, 1.77s/it] 91%|█████████▏| 64/70 [02:05<00:10, 1.75s/it] 93%|█████████▎| 65/70 [02:06<00:08, 1.79s/it] 94%|█████████▍| 66/70 [02:08<00:06, 1.70s/it] 96%|█████████▌| 67/70 [02:10<00:05, 1.72s/it] 97%|█████████▋| 68/70 [02:11<00:03, 1.69s/it] 99%|█████████▊| 69/70 [02:12<00:01, 1.51s/it] 100%|██████████| 70/70 [02:13<00:00, 1.35s/it] 100%|██████████| 70/70 [02:13<00:00, 1.91s/it] Decoding latents in cuda:0... done in 1.75s Move latents to cpu... done in 0.01s 0%| | 0/32 [00:00<?, ?it/s] 3%|▎ | 1/32 [00:00<00:22, 1.38it/s] 6%|▋ | 2/32 [00:01<00:20, 1.49it/s] 9%|▉ | 3/32 [00:01<00:18, 1.53it/s] 12%|█▎ | 4/32 [00:02<00:18, 1.52it/s] 16%|█▌ | 5/32 [00:03<00:17, 1.53it/s] 19%|█▉ | 6/32 [00:03<00:17, 1.51it/s] 22%|██▏ | 7/32 [00:04<00:16, 1.49it/s] 25%|██▌ | 8/32 [00:05<00:16, 1.48it/s] 28%|██▊ | 9/32 [00:06<00:15, 1.49it/s] 31%|███▏ | 10/32 [00:06<00:14, 1.49it/s] 34%|███▍ | 11/32 [00:07<00:13, 1.57it/s] 38%|███▊ | 12/32 [00:07<00:12, 1.55it/s] 41%|████ | 13/32 [00:08<00:12, 1.54it/s] 44%|████▍ | 14/32 [00:09<00:11, 1.52it/s] 47%|████▋ | 15/32 [00:09<00:11, 1.54it/s] 50%|█████ | 16/32 [00:10<00:10, 1.53it/s] 53%|█████▎ | 17/32 [00:11<00:09, 1.56it/s] 56%|█████▋ | 18/32 [00:11<00:08, 1.57it/s] 59%|█████▉ | 19/32 [00:12<00:08, 1.58it/s] 62%|██████▎ | 20/32 [00:12<00:07, 1.62it/s] 66%|██████▌ | 21/32 [00:13<00:06, 1.66it/s] 69%|██████▉ | 22/32 [00:14<00:05, 1.68it/s] 72%|███████▏ | 23/32 [00:14<00:05, 1.63it/s] 75%|███████▌ | 24/32 [00:15<00:04, 1.70it/s] 78%|███████▊ | 25/32 [00:15<00:04, 1.68it/s] 81%|████████▏ | 26/32 [00:16<00:03, 1.70it/s] 84%|████████▍ | 27/32 [00:17<00:03, 1.66it/s] 88%|████████▊ | 28/32 [00:17<00:02, 1.73it/s] 91%|█████████ | 29/32 [00:18<00:01, 1.71it/s] 94%|█████████▍| 30/32 [00:18<00:01, 1.73it/s] 97%|█████████▋| 31/32 [00:19<00:00, 1.94it/s] 100%|██████████| 32/32 [00:19<00:00, 2.17it/s] 100%|██████████| 32/32 [00:19<00:00, 1.64it/s] Decoding latents in cuda:0... done in 0.58s Move latents to cpu... done in 0.0s 0%| | 0/32 [00:00<?, ?it/s] 3%|▎ | 1/32 [00:00<00:21, 1.43it/s] 6%|▋ | 2/32 [00:01<00:20, 1.50it/s] 9%|▉ | 3/32 [00:01<00:19, 1.52it/s] 12%|█▎ | 4/32 [00:02<00:18, 1.51it/s] 16%|█▌ | 5/32 [00:03<00:17, 1.55it/s] 19%|█▉ | 6/32 [00:03<00:16, 1.57it/s] 22%|██▏ | 7/32 [00:04<00:16, 1.55it/s] 25%|██▌ | 8/32 [00:05<00:15, 1.51it/s] 28%|██▊ | 9/32 [00:05<00:15, 1.52it/s] 31%|███▏ | 10/32 [00:06<00:14, 1.53it/s] 34%|███▍ | 11/32 [00:07<00:13, 1.57it/s] 38%|███▊ | 12/32 [00:07<00:12, 1.54it/s] 41%|████ | 13/32 [00:08<00:12, 1.51it/s] 44%|████▍ | 14/32 [00:09<00:12, 1.48it/s] 47%|████▋ | 15/32 [00:09<00:11, 1.49it/s] 50%|█████ | 16/32 [00:10<00:10, 1.48it/s] 53%|█████▎ | 17/32 [00:11<00:09, 1.52it/s] 56%|█████▋ | 18/32 [00:11<00:09, 1.55it/s] 59%|█████▉ | 19/32 [00:12<00:08, 1.54it/s] 62%|██████▎ | 20/32 [00:13<00:07, 1.56it/s] 66%|██████▌ | 21/32 [00:13<00:06, 1.60it/s] 69%|██████▉ | 22/32 [00:14<00:06, 1.61it/s] 72%|███████▏ | 23/32 [00:14<00:05, 1.59it/s] 75%|███████▌ | 24/32 [00:15<00:04, 1.66it/s] 78%|███████▊ | 25/32 [00:16<00:04, 1.65it/s] 81%|████████▏ | 26/32 [00:16<00:03, 1.68it/s] 84%|████████▍ | 27/32 [00:17<00:03, 1.64it/s] 88%|████████▊ | 28/32 [00:17<00:02, 1.73it/s] 91%|█████████ | 29/32 [00:18<00:01, 1.72it/s] 94%|█████████▍| 30/32 [00:19<00:01, 1.69it/s] 97%|█████████▋| 31/32 [00:19<00:00, 1.89it/s] 100%|██████████| 32/32 [00:19<00:00, 2.13it/s] 100%|██████████| 32/32 [00:19<00:00, 1.62it/s] Decoding latents in cuda:0... done in 0.59s Move latents to cpu... done in 0.0s 0%| | 0/32 [00:00<?, ?it/s] 3%|▎ | 1/32 [00:00<00:21, 1.47it/s] 6%|▋ | 2/32 [00:01<00:19, 1.52it/s] 9%|▉ | 3/32 [00:01<00:18, 1.54it/s] 12%|█▎ | 4/32 [00:02<00:18, 1.52it/s] 16%|█▌ | 5/32 [00:03<00:17, 1.52it/s] 19%|█▉ | 6/32 [00:03<00:16, 1.54it/s] 22%|██▏ | 7/32 [00:04<00:16, 1.53it/s] 25%|██▌ | 8/32 [00:05<00:15, 1.51it/s] 28%|██▊ | 9/32 [00:05<00:15, 1.52it/s] 31%|███▏ | 10/32 [00:06<00:14, 1.53it/s] 34%|███▍ | 11/32 [00:07<00:13, 1.59it/s] 38%|███▊ | 12/32 [00:07<00:13, 1.49it/s] 41%|████ | 13/32 [00:08<00:13, 1.44it/s] 44%|████▍ | 14/32 [00:09<00:12, 1.46it/s] 47%|████▋ | 15/32 [00:09<00:11, 1.50it/s] 50%|█████ | 16/32 [00:10<00:10, 1.51it/s] 53%|█████▎ | 17/32 [00:11<00:09, 1.54it/s] 56%|█████▋ | 18/32 [00:11<00:09, 1.53it/s] 59%|█████▉ | 19/32 [00:12<00:08, 1.53it/s] 62%|██████▎ | 20/32 [00:13<00:07, 1.55it/s] 66%|██████▌ | 21/32 [00:13<00:06, 1.60it/s] 69%|██████▉ | 22/32 [00:14<00:06, 1.61it/s] 72%|███████▏ | 23/32 [00:15<00:05, 1.58it/s] 75%|███████▌ | 24/32 [00:15<00:04, 1.63it/s] 78%|███████▊ | 25/32 [00:16<00:04, 1.58it/s] 81%|████████▏ | 26/32 [00:16<00:03, 1.61it/s] 84%|████████▍ | 27/32 [00:17<00:03, 1.56it/s] 88%|████████▊ | 28/32 [00:18<00:02, 1.65it/s] 91%|█████████ | 29/32 [00:18<00:01, 1.65it/s] 94%|█████████▍| 30/32 [00:19<00:01, 1.66it/s] 97%|█████████▋| 31/32 [00:19<00:00, 1.84it/s] 100%|██████████| 32/32 [00:20<00:00, 2.03it/s] 100%|██████████| 32/32 [00:20<00:00, 1.60it/s] Decoding latents in cuda:0... done in 0.58s Move latents to cpu... done in 0.0s Uploading outputs... Finished.