pwntus/stable-diffusion-depth2img 🔢🖼️📝❓ → 🖼️
About
Create variations of an image while preserving shape and depth.

Example Output
Prompt:
"A fantasy landscape at a dark moonlit night, black sky, trending on artstation"
Output

Performance Metrics
17.79s
Prediction Time
17.83s
Total Time
All Input Parameters
{ "image": "https://replicate.delivery/pbxt/IAh0VDQpBV4STGq3JtNAFGA09FCYini5FZHMZl39OL7PwafI/sketch-mountains-input.jpeg", "prompt": "A fantasy landscape at a dark moonlit night, black sky, trending on artstation", "scheduler": "K_EULER_ANCESTRAL", "num_outputs": 1, "guidance_scale": "5.5", "negative_prompt": "light sky, day", "prompt_strength": 0.9, "num_inference_steps": 50 }
Input Parameters
- seed
- Random seed. Leave blank to randomize the seed
- image (required)
- Image that will be used as the starting point for the process.
- prompt
- The prompt to guide the image generation.
- scheduler
- Choose a scheduler.
- num_outputs
- Number of images to output. Higher number of outputs may OOM.
- guidance_scale
- Scale for classifier-free guidance. Higher guidance scale encourages to generate images that are closely linked to the text prompt, usually at the expense of lower image quality.
- negative_prompt
- The prompt NOT to guide the image generation. Ignored when not using guidance
- prompt_strength
- Prompt strength when providing the image. 1.0 corresponds to full destruction of information in init image.
- num_inference_steps
- The number of denoising steps. More denoising steps usually lead to a higher quality image at the expense of slower inference.
Output Schema
Output
Example Execution Logs
Using seed: 19973 0%| | 0/45 [00:00<?, ?it/s] 2%|▏ | 1/45 [00:00<00:15, 2.82it/s] 4%|▍ | 2/45 [00:00<00:15, 2.81it/s] 7%|▋ | 3/45 [00:01<00:15, 2.77it/s] 9%|▉ | 4/45 [00:01<00:14, 2.78it/s] 11%|█ | 5/45 [00:01<00:14, 2.78it/s] 13%|█▎ | 6/45 [00:02<00:14, 2.78it/s] 16%|█▌ | 7/45 [00:02<00:13, 2.78it/s] 18%|█▊ | 8/45 [00:02<00:13, 2.77it/s] 20%|██ | 9/45 [00:03<00:13, 2.77it/s] 22%|██▏ | 10/45 [00:03<00:12, 2.77it/s] 24%|██▍ | 11/45 [00:03<00:12, 2.77it/s] 27%|██▋ | 12/45 [00:04<00:11, 2.77it/s] 29%|██▉ | 13/45 [00:04<00:11, 2.78it/s] 31%|███ | 14/45 [00:05<00:11, 2.77it/s] 33%|███▎ | 15/45 [00:05<00:10, 2.76it/s] 36%|███▌ | 16/45 [00:05<00:10, 2.77it/s] 38%|███▊ | 17/45 [00:06<00:10, 2.76it/s] 40%|████ | 18/45 [00:06<00:09, 2.77it/s] 42%|████▏ | 19/45 [00:06<00:09, 2.77it/s] 44%|████▍ | 20/45 [00:07<00:09, 2.75it/s] 47%|████▋ | 21/45 [00:07<00:08, 2.76it/s] 49%|████▉ | 22/45 [00:07<00:08, 2.75it/s] 51%|█████ | 23/45 [00:08<00:08, 2.75it/s] 53%|█████▎ | 24/45 [00:08<00:07, 2.75it/s] 56%|█████▌ | 25/45 [00:09<00:07, 2.75it/s] 58%|█████▊ | 26/45 [00:09<00:06, 2.75it/s] 60%|██████ | 27/45 [00:09<00:06, 2.75it/s] 62%|██████▏ | 28/45 [00:10<00:06, 2.75it/s] 64%|██████▍ | 29/45 [00:10<00:05, 2.74it/s] 67%|██████▋ | 30/45 [00:10<00:05, 2.74it/s] 69%|██████▉ | 31/45 [00:11<00:05, 2.74it/s] 71%|███████ | 32/45 [00:11<00:04, 2.74it/s] 73%|███████▎ | 33/45 [00:11<00:04, 2.74it/s] 76%|███████▌ | 34/45 [00:12<00:04, 2.74it/s] 78%|███████▊ | 35/45 [00:12<00:03, 2.74it/s] 80%|████████ | 36/45 [00:13<00:03, 2.74it/s] 82%|████████▏ | 37/45 [00:13<00:02, 2.75it/s] 84%|████████▍ | 38/45 [00:13<00:02, 2.75it/s] 87%|████████▋ | 39/45 [00:14<00:02, 2.74it/s] 89%|████████▉ | 40/45 [00:14<00:01, 2.74it/s] 91%|█████████ | 41/45 [00:14<00:01, 2.74it/s] 93%|█████████▎| 42/45 [00:15<00:01, 2.74it/s] 96%|█████████▌| 43/45 [00:15<00:00, 2.74it/s] 98%|█████████▊| 44/45 [00:15<00:00, 2.74it/s] 100%|██████████| 45/45 [00:16<00:00, 2.74it/s] 100%|██████████| 45/45 [00:16<00:00, 2.75it/s]
Version Details
- Version ID
f7b8c40a2476c36633005f208aec0ca16a8e2ac2ab69e7bdf77b6aa6eb81af6b
- Version Created
- January 21, 2023