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Chinese Landscape Mocks with Picx
picx:v1.0
evevalentine2017
evevalentine2017
·
Jan 5
367
Input
prompt
Specify things to see in the output
diorama, abstraction vintage chinese folk art, solo, a cute little girl, kimono, green hair, elf ears, old tree, river, wooden bridge, mountain, meditation, birds, 2d, muted colors, thick hatching, paper texture
negative_prompt
Specify things to not see in the output
(bad quality, low quality:1.3), EasyNegativeV2, negative_hand-neg, (asian face, asian eyes, old, mature, curvy, busty, big tits, tall:1.3), tattoo
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
0.45
detail
Enhance/diminish detail while keeping the overall style/character
0
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.
3396608464
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
25
cfg_scale
Scale for classifier-free guidance
7
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>
lora_2
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
Beautiful Character 4 Stable Yogi.safetensors
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)
EasyNegativeV2.safetensors
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
negative_hand-neg.pt
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/7b31a23c55484e69a370a225b07233fc/00000-3396608464.webp
https://files.tungsten.run/uploads/568a6ae86bd94e95bb0dcc95cef4631f/00001-3396608465.webp
https://files.tungsten.run/uploads/069ecb26a75a4a53b0ea8c4df6544016/00002-3396608466.webp
https://files.tungsten.run/uploads/2e05795ebc8845598f062043a6890e00/00003-3396608467.webp
Finished in 36.0 seconds
Setting up the model... Preparing inputs... Processing... Loading VAE weight: models/VAE/blessed2_fp16.safetensors Full prompt: diorama, abstraction vintage chinese folk art, solo, a cute little girl, kimono, green hair, elf ears, old tree, river, wooden bridge, mountain, meditation, birds, 2d, muted colors, thick hatching, paper texture Full negative prompt: (bad quality, low quality:1.3), EasyNegativeV2, negative_hand-neg, (asian face, asian eyes, old, mature, curvy, busty, big tits, tall:1.3), tattoo 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:15, 1.55it/s] 8%|▊ | 2/25 [00:01<00:15, 1.50it/s] 12%|█▏ | 3/25 [00:01<00:14, 1.51it/s] 16%|█▌ | 4/25 [00:02<00:14, 1.50it/s] 20%|██ | 5/25 [00:03<00:13, 1.49it/s] 24%|██▍ | 6/25 [00:03<00:12, 1.50it/s] 28%|██▊ | 7/25 [00:04<00:12, 1.50it/s] 32%|███▏ | 8/25 [00:05<00:11, 1.49it/s] 36%|███▌ | 9/25 [00:06<00:10, 1.50it/s] 40%|████ | 10/25 [00:06<00:10, 1.50it/s] 44%|████▍ | 11/25 [00:07<00:09, 1.49it/s] 48%|████▊ | 12/25 [00:08<00:08, 1.50it/s] 52%|█████▏ | 13/25 [00:08<00:08, 1.50it/s] 56%|█████▌ | 14/25 [00:09<00:07, 1.50it/s] 60%|██████ | 15/25 [00:10<00:06, 1.50it/s] 64%|██████▍ | 16/25 [00:10<00:06, 1.50it/s] 68%|██████▊ | 17/25 [00:11<00:05, 1.50it/s] 72%|███████▏ | 18/25 [00:12<00:04, 1.50it/s] 76%|███████▌ | 19/25 [00:12<00:04, 1.50it/s] 80%|████████ | 20/25 [00:13<00:03, 1.50it/s] 84%|████████▍ | 21/25 [00:14<00:02, 1.50it/s] 88%|████████▊ | 22/25 [00:14<00:01, 1.50it/s] 92%|█████████▏| 23/25 [00:15<00:01, 1.50it/s] 96%|█████████▌| 24/25 [00:15<00:00, 1.50it/s] 100%|██████████| 25/25 [00:16<00:00, 1.50it/s] 100%|██████████| 25/25 [00:16<00:00, 1.50it/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 1.9s Move latents to cpu... done in 0.02s 0: 640x640 (no detections), 7.4ms Speed: 2.8ms preprocess, 7.4ms inference, 7.9ms postprocess per image at shape (1, 3, 640, 640) [-] ADetailer: nothing detected on image 1 with 1st settings. 0: 640x640 (no detections), 7.0ms Speed: 2.8ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 640) [-] ADetailer: nothing detected on image 1 with 2nd settings. 0: 640x640 1 face, 7.5ms Speed: 2.6ms preprocess, 7.5ms inference, 10.4ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/12 [00:00<?, ?it/s] 8%|▊ | 1/12 [00:00<00:03, 3.57it/s] 17%|█▋ | 2/12 [00:00<00:02, 4.97it/s] 25%|██▌ | 3/12 [00:00<00:01, 5.65it/s] 33%|███▎ | 4/12 [00:00<00:01, 6.04it/s] 42%|████▏ | 5/12 [00:00<00:01, 6.27it/s] 50%|█████ | 6/12 [00:01<00:00, 6.34it/s] 58%|█████▊ | 7/12 [00:01<00:00, 6.36it/s] 67%|██████▋ | 8/12 [00:01<00:00, 6.37it/s] 75%|███████▌ | 9/12 [00:01<00:00, 6.43it/s] 83%|████████▎ | 10/12 [00:01<00:00, 6.50it/s] 92%|█████████▏| 11/12 [00:01<00:00, 6.56it/s] 100%|██████████| 12/12 [00:01<00:00, 6.58it/s] 100%|██████████| 12/12 [00:01<00:00, 6.18it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0: 640x640 (no detections), 6.9ms Speed: 2.6ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 640) [-] ADetailer: nothing detected on image 2 with 2nd settings. 0: 640x640 (no detections), 7.2ms Speed: 2.6ms preprocess, 7.2ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 640) [-] ADetailer: nothing detected on image 3 with 1st settings. 0: 640x640 (no detections), 6.9ms Speed: 2.8ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 640) [-] ADetailer: nothing detected on image 3 with 2nd settings. 0: 640x640 1 face, 7.4ms Speed: 2.6ms preprocess, 7.4ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/12 [00:00<?, ?it/s] 8%|▊ | 1/12 [00:00<00:01, 7.07it/s] 17%|█▋ | 2/12 [00:00<00:01, 6.90it/s] 25%|██▌ | 3/12 [00:00<00:01, 6.84it/s] 33%|███▎ | 4/12 [00:00<00:01, 6.80it/s] 42%|████▏ | 5/12 [00:00<00:01, 6.76it/s] 50%|█████ | 6/12 [00:00<00:00, 6.65it/s] 58%|█████▊ | 7/12 [00:01<00:00, 6.56it/s] 67%|██████▋ | 8/12 [00:01<00:00, 6.52it/s] 75%|███████▌ | 9/12 [00:01<00:00, 6.54it/s] 83%|████████▎ | 10/12 [00:01<00:00, 6.58it/s] 92%|█████████▏| 11/12 [00:01<00:00, 6.61it/s] 100%|██████████| 12/12 [00:01<00:00, 6.62it/s] 100%|██████████| 12/12 [00:01<00:00, 6.65it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0: 640x640 1 hand, 7.0ms Speed: 2.8ms preprocess, 7.0ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/12 [00:00<?, ?it/s] 8%|▊ | 1/12 [00:00<00:01, 7.14it/s] 17%|█▋ | 2/12 [00:00<00:01, 6.87it/s] 25%|██▌ | 3/12 [00:00<00:01, 6.82it/s] 33%|███▎ | 4/12 [00:00<00:01, 6.79it/s] 42%|████▏ | 5/12 [00:00<00:01, 6.75it/s] 50%|█████ | 6/12 [00:00<00:00, 6.66it/s] 58%|█████▊ | 7/12 [00:01<00:00, 6.58it/s] 67%|██████▋ | 8/12 [00:01<00:00, 6.53it/s] 75%|███████▌ | 9/12 [00:01<00:00, 6.50it/s] 83%|████████▎ | 10/12 [00:01<00:00, 6.55it/s] 92%|█████████▏| 11/12 [00:01<00:00, 6.58it/s] 100%|██████████| 12/12 [00:01<00:00, 6.62it/s] 100%|██████████| 12/12 [00:01<00:00, 6.64it/s] Decoding latents in cuda:0... done in 0.4s Move latents to cpu... done in 0.0s Uploading outputs... Finished.
prompt
Specify things to see in the output
diorama, abstraction vintage chinese folk art, solo, a cute little girl, kimono, green hair, elf ears, old tree, river, wooden bridge, mountain, meditation, birds, 2d, muted colors, thick hatching, paper texture
negative_prompt
Specify things to not see in the output
(bad quality, low quality:1.3), EasyNegativeV2, negative_hand-neg, (asian face, asian eyes, old, mature, curvy, busty, big tits, tall:1.3), tattoo
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
0.45
detail
Enhance/diminish detail while keeping the overall style/character
0
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.
3396608464
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
25
cfg_scale
Scale for classifier-free guidance
7
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>
lora_2
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
Beautiful Character 4 Stable Yogi.safetensors
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)
EasyNegativeV2.safetensors
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
negative_hand-neg.pt
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/7b31a23c55484e69a370a225b07233fc/00000-3396608464.webp
https://files.tungsten.run/uploads/568a6ae86bd94e95bb0dcc95cef4631f/00001-3396608465.webp
https://files.tungsten.run/uploads/069ecb26a75a4a53b0ea8c4df6544016/00002-3396608466.webp
https://files.tungsten.run/uploads/2e05795ebc8845598f062043a6890e00/00003-3396608467.webp
Finished in 36.0 seconds
Setting up the model... Preparing inputs... Processing... Loading VAE weight: models/VAE/blessed2_fp16.safetensors Full prompt: diorama, abstraction vintage chinese folk art, solo, a cute little girl, kimono, green hair, elf ears, old tree, river, wooden bridge, mountain, meditation, birds, 2d, muted colors, thick hatching, paper texture Full negative prompt: (bad quality, low quality:1.3), EasyNegativeV2, negative_hand-neg, (asian face, asian eyes, old, mature, curvy, busty, big tits, tall:1.3), tattoo 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:15, 1.55it/s] 8%|▊ | 2/25 [00:01<00:15, 1.50it/s] 12%|█▏ | 3/25 [00:01<00:14, 1.51it/s] 16%|█▌ | 4/25 [00:02<00:14, 1.50it/s] 20%|██ | 5/25 [00:03<00:13, 1.49it/s] 24%|██▍ | 6/25 [00:03<00:12, 1.50it/s] 28%|██▊ | 7/25 [00:04<00:12, 1.50it/s] 32%|███▏ | 8/25 [00:05<00:11, 1.49it/s] 36%|███▌ | 9/25 [00:06<00:10, 1.50it/s] 40%|████ | 10/25 [00:06<00:10, 1.50it/s] 44%|████▍ | 11/25 [00:07<00:09, 1.49it/s] 48%|████▊ | 12/25 [00:08<00:08, 1.50it/s] 52%|█████▏ | 13/25 [00:08<00:08, 1.50it/s] 56%|█████▌ | 14/25 [00:09<00:07, 1.50it/s] 60%|██████ | 15/25 [00:10<00:06, 1.50it/s] 64%|██████▍ | 16/25 [00:10<00:06, 1.50it/s] 68%|██████▊ | 17/25 [00:11<00:05, 1.50it/s] 72%|███████▏ | 18/25 [00:12<00:04, 1.50it/s] 76%|███████▌ | 19/25 [00:12<00:04, 1.50it/s] 80%|████████ | 20/25 [00:13<00:03, 1.50it/s] 84%|████████▍ | 21/25 [00:14<00:02, 1.50it/s] 88%|████████▊ | 22/25 [00:14<00:01, 1.50it/s] 92%|█████████▏| 23/25 [00:15<00:01, 1.50it/s] 96%|█████████▌| 24/25 [00:15<00:00, 1.50it/s] 100%|██████████| 25/25 [00:16<00:00, 1.50it/s] 100%|██████████| 25/25 [00:16<00:00, 1.50it/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 1.9s Move latents to cpu... done in 0.02s 0: 640x640 (no detections), 7.4ms Speed: 2.8ms preprocess, 7.4ms inference, 7.9ms postprocess per image at shape (1, 3, 640, 640) [-] ADetailer: nothing detected on image 1 with 1st settings. 0: 640x640 (no detections), 7.0ms Speed: 2.8ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 640) [-] ADetailer: nothing detected on image 1 with 2nd settings. 0: 640x640 1 face, 7.5ms Speed: 2.6ms preprocess, 7.5ms inference, 10.4ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/12 [00:00<?, ?it/s] 8%|▊ | 1/12 [00:00<00:03, 3.57it/s] 17%|█▋ | 2/12 [00:00<00:02, 4.97it/s] 25%|██▌ | 3/12 [00:00<00:01, 5.65it/s] 33%|███▎ | 4/12 [00:00<00:01, 6.04it/s] 42%|████▏ | 5/12 [00:00<00:01, 6.27it/s] 50%|█████ | 6/12 [00:01<00:00, 6.34it/s] 58%|█████▊ | 7/12 [00:01<00:00, 6.36it/s] 67%|██████▋ | 8/12 [00:01<00:00, 6.37it/s] 75%|███████▌ | 9/12 [00:01<00:00, 6.43it/s] 83%|████████▎ | 10/12 [00:01<00:00, 6.50it/s] 92%|█████████▏| 11/12 [00:01<00:00, 6.56it/s] 100%|██████████| 12/12 [00:01<00:00, 6.58it/s] 100%|██████████| 12/12 [00:01<00:00, 6.18it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0: 640x640 (no detections), 6.9ms Speed: 2.6ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 640) [-] ADetailer: nothing detected on image 2 with 2nd settings. 0: 640x640 (no detections), 7.2ms Speed: 2.6ms preprocess, 7.2ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 640) [-] ADetailer: nothing detected on image 3 with 1st settings. 0: 640x640 (no detections), 6.9ms Speed: 2.8ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 640, 640) [-] ADetailer: nothing detected on image 3 with 2nd settings. 0: 640x640 1 face, 7.4ms Speed: 2.6ms preprocess, 7.4ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/12 [00:00<?, ?it/s] 8%|▊ | 1/12 [00:00<00:01, 7.07it/s] 17%|█▋ | 2/12 [00:00<00:01, 6.90it/s] 25%|██▌ | 3/12 [00:00<00:01, 6.84it/s] 33%|███▎ | 4/12 [00:00<00:01, 6.80it/s] 42%|████▏ | 5/12 [00:00<00:01, 6.76it/s] 50%|█████ | 6/12 [00:00<00:00, 6.65it/s] 58%|█████▊ | 7/12 [00:01<00:00, 6.56it/s] 67%|██████▋ | 8/12 [00:01<00:00, 6.52it/s] 75%|███████▌ | 9/12 [00:01<00:00, 6.54it/s] 83%|████████▎ | 10/12 [00:01<00:00, 6.58it/s] 92%|█████████▏| 11/12 [00:01<00:00, 6.61it/s] 100%|██████████| 12/12 [00:01<00:00, 6.62it/s] 100%|██████████| 12/12 [00:01<00:00, 6.65it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0: 640x640 1 hand, 7.0ms Speed: 2.8ms preprocess, 7.0ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/12 [00:00<?, ?it/s] 8%|▊ | 1/12 [00:00<00:01, 7.14it/s] 17%|█▋ | 2/12 [00:00<00:01, 6.87it/s] 25%|██▌ | 3/12 [00:00<00:01, 6.82it/s] 33%|███▎ | 4/12 [00:00<00:01, 6.79it/s] 42%|████▏ | 5/12 [00:00<00:01, 6.75it/s] 50%|█████ | 6/12 [00:00<00:00, 6.66it/s] 58%|█████▊ | 7/12 [00:01<00:00, 6.58it/s] 67%|██████▋ | 8/12 [00:01<00:00, 6.53it/s] 75%|███████▌ | 9/12 [00:01<00:00, 6.50it/s] 83%|████████▎ | 10/12 [00:01<00:00, 6.55it/s] 92%|█████████▏| 11/12 [00:01<00:00, 6.58it/s] 100%|██████████| 12/12 [00:01<00:00, 6.62it/s] 100%|██████████| 12/12 [00:01<00:00, 6.64it/s] Decoding latents in cuda:0... done in 0.4s Move latents to cpu... done in 0.0s Uploading outputs... Finished.