cjwbw/van-gogh-diffusion 🔢❓📝 → 🖼️

▶️ 5.5K runs 📅 Nov 2022 ⚙️ Cog 0.4.4 ⚖️ License
text-to-image van-gogh-style

About

Van Gough on Stable Diffusion via Dreambooth

Example Output

Prompt:

"lvngvncnt, beautiful woman at sunset"

Output

Example output

Performance Metrics

13.80s Prediction Time
13.84s Total Time
All Input Parameters 
{
  "width": 512,
  "height": 512,
  "prompt": "lvngvncnt, beautiful woman at sunset",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 50
}
Input Parameters
seed Type: integer
Random seed. Leave blank to randomize the seed
width Default: 512
Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
height Default: 512
Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
prompt Type: stringDefault: lvngvncnt, beautiful woman at sunset
Input prompt
num_outputs Default: 1
Number of images to output
guidance_scale Type: numberDefault: 7.5Range: 1 - 20
Scale for classifier-free guidance
num_inference_steps Type: integerDefault: 50Range: 1 - 500
Number of denoising steps
Output Schema

Output

Type: array • Items Type: string • Items Format: uri

Example Execution Logs 
Using seed: 53092
Global seed set to 53092

  0%|          | 0/51 [00:00<?, ?it/s]
  2%|▏         | 1/51 [00:00<00:16,  3.02it/s]
  4%|▍         | 2/51 [00:00<00:14,  3.48it/s]
  6%|▌         | 3/51 [00:00<00:13,  3.65it/s]
  8%|▊         | 4/51 [00:01<00:12,  3.75it/s]
 10%|▉         | 5/51 [00:01<00:12,  3.77it/s]
 12%|█▏        | 6/51 [00:01<00:11,  3.80it/s]
 14%|█▎        | 7/51 [00:01<00:11,  3.82it/s]
 16%|█▌        | 8/51 [00:02<00:11,  3.84it/s]
 18%|█▊        | 9/51 [00:02<00:10,  3.84it/s]
 20%|█▉        | 10/51 [00:02<00:10,  3.85it/s]
 22%|██▏       | 11/51 [00:02<00:10,  3.85it/s]
 24%|██▎       | 12/51 [00:03<00:10,  3.85it/s]
 25%|██▌       | 13/51 [00:03<00:09,  3.85it/s]
 27%|██▋       | 14/51 [00:03<00:09,  3.85it/s]
 29%|██▉       | 15/51 [00:03<00:09,  3.85it/s]
 31%|███▏      | 16/51 [00:04<00:09,  3.86it/s]
 33%|███▎      | 17/51 [00:04<00:08,  3.85it/s]
 35%|███▌      | 18/51 [00:04<00:08,  3.85it/s]
 37%|███▋      | 19/51 [00:04<00:08,  3.85it/s]
 39%|███▉      | 20/51 [00:05<00:08,  3.85it/s]
 41%|████      | 21/51 [00:05<00:07,  3.86it/s]
 43%|████▎     | 22/51 [00:05<00:07,  3.85it/s]
 45%|████▌     | 23/51 [00:06<00:07,  3.85it/s]
 47%|████▋     | 24/51 [00:06<00:07,  3.85it/s]
 49%|████▉     | 25/51 [00:06<00:06,  3.85it/s]
 51%|█████     | 26/51 [00:06<00:06,  3.86it/s]
 53%|█████▎    | 27/51 [00:07<00:06,  3.85it/s]
 55%|█████▍    | 28/51 [00:07<00:05,  3.85it/s]
 57%|█████▋    | 29/51 [00:07<00:05,  3.84it/s]
 59%|█████▉    | 30/51 [00:07<00:05,  3.84it/s]
 61%|██████    | 31/51 [00:08<00:05,  3.85it/s]
 63%|██████▎   | 32/51 [00:08<00:04,  3.85it/s]
 65%|██████▍   | 33/51 [00:08<00:04,  3.85it/s]
 67%|██████▋   | 34/51 [00:08<00:04,  3.84it/s]
 69%|██████▊   | 35/51 [00:09<00:04,  3.84it/s]
 71%|███████   | 36/51 [00:09<00:03,  3.84it/s]
 73%|███████▎  | 37/51 [00:09<00:03,  3.84it/s]
 75%|███████▍  | 38/51 [00:09<00:03,  3.84it/s]
 76%|███████▋  | 39/51 [00:10<00:03,  3.84it/s]
 78%|███████▊  | 40/51 [00:10<00:02,  3.85it/s]
 80%|████████  | 41/51 [00:10<00:02,  3.83it/s]
 82%|████████▏ | 42/51 [00:10<00:02,  3.83it/s]
 84%|████████▍ | 43/51 [00:11<00:02,  3.82it/s]
 86%|████████▋ | 44/51 [00:11<00:01,  3.83it/s]
 88%|████████▊ | 45/51 [00:11<00:01,  3.83it/s]
 90%|█████████ | 46/51 [00:12<00:01,  3.83it/s]
 92%|█████████▏| 47/51 [00:12<00:01,  3.83it/s]
 94%|█████████▍| 48/51 [00:12<00:00,  3.84it/s]
 96%|█████████▌| 49/51 [00:12<00:00,  3.83it/s]
 98%|█████████▊| 50/51 [00:13<00:00,  3.83it/s]
100%|██████████| 51/51 [00:13<00:00,  3.82it/s]
100%|██████████| 51/51 [00:13<00:00,  3.83it/s]
Version Details
Version ID
2d43b996608bd7d4aba4cacbe9b751399892a9d6cbc27a39f8f49347a3a16f9c
Version Created
November 8, 2022
Run on Replicate →