danjimenezm/food-gen-v1 🔢🖼️❓📝 → 🖼️
About

Example Output
Prompt:
"A professional food photo of a chicken pizza, on a marble table, overhead. centered. 50% negative space on all sides. minimalist style. centered: 1"
Output

Performance Metrics
18.30s
Prediction Time
18.40s
Total Time
All Input Parameters
{ "image": "https://replicate.delivery/pbxt/Id7sB4syXLOODgSUcYmahgHUNispx6qePkO8PCTLbb51YUKf/test%20%284%29.png", "width": 512, "height": 512, "prompt": "A professional food photo of a chicken pizza, on a marble table, overhead. centered. 50% negative space on all sides. minimalist style. centered: 1", "scheduler": "DPMSolverMultistep", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.9, "num_inference_steps": 100 }
Input Parameters
- seed
- Random seed. Leave blank to randomize the seed
- image (required)
- Inital image to generate variations of.
- width
- Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
- height
- Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
- prompt
- Input prompt
- scheduler
- Choose a scheduler.
- num_outputs
- Number of images to output. Higher number of outputs may OOM.
- guidance_scale
- Scale for classifier-free guidance
- 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
- Number of denoising steps
Output Schema
Output
Example Execution Logs
Using seed: 38955 0%| | 0/90 [00:00<?, ?it/s] 1%| | 1/90 [00:00<00:19, 4.56it/s] 2%|▏ | 2/90 [00:00<00:17, 5.01it/s] 3%|▎ | 3/90 [00:00<00:16, 5.18it/s] 4%|▍ | 4/90 [00:00<00:16, 5.28it/s] 6%|▌ | 5/90 [00:00<00:15, 5.34it/s] 7%|▋ | 6/90 [00:01<00:15, 5.32it/s] 8%|▊ | 7/90 [00:01<00:15, 5.31it/s] 9%|▉ | 8/90 [00:01<00:15, 5.33it/s] 10%|█ | 9/90 [00:01<00:15, 5.38it/s] 11%|█ | 10/90 [00:01<00:14, 5.41it/s] 12%|█▏ | 11/90 [00:02<00:14, 5.40it/s] 13%|█▎ | 12/90 [00:02<00:14, 5.39it/s] 14%|█▍ | 13/90 [00:02<00:14, 5.37it/s] 16%|█▌ | 14/90 [00:02<00:14, 5.36it/s] 17%|█▋ | 15/90 [00:02<00:13, 5.39it/s] 18%|█▊ | 16/90 [00:03<00:13, 5.40it/s] 19%|█▉ | 17/90 [00:03<00:13, 5.39it/s] 20%|██ | 18/90 [00:03<00:13, 5.38it/s] 21%|██ | 19/90 [00:03<00:13, 5.36it/s] 22%|██▏ | 20/90 [00:03<00:13, 5.37it/s] 23%|██▎ | 21/90 [00:03<00:12, 5.40it/s] 24%|██▍ | 22/90 [00:04<00:12, 5.40it/s] 26%|██▌ | 23/90 [00:04<00:12, 5.40it/s] 27%|██▋ | 24/90 [00:04<00:12, 5.37it/s] 28%|██▊ | 25/90 [00:04<00:12, 5.36it/s] 29%|██▉ | 26/90 [00:04<00:11, 5.38it/s] 30%|███ | 27/90 [00:05<00:11, 5.39it/s] 31%|███ | 28/90 [00:05<00:11, 5.41it/s] 32%|███▏ | 29/90 [00:05<00:11, 5.40it/s] 33%|███▎ | 30/90 [00:05<00:11, 5.36it/s] 34%|███▍ | 31/90 [00:05<00:11, 5.36it/s] 36%|███▌ | 32/90 [00:05<00:10, 5.37it/s] 37%|███▋ | 33/90 [00:06<00:10, 5.38it/s] 38%|███▊ | 34/90 [00:06<00:10, 5.38it/s] 39%|███▉ | 35/90 [00:06<00:10, 5.34it/s] 40%|████ | 36/90 [00:06<00:10, 5.36it/s] 41%|████ | 37/90 [00:06<00:09, 5.38it/s] 42%|████▏ | 38/90 [00:07<00:09, 5.38it/s] 43%|████▎ | 39/90 [00:07<00:09, 5.36it/s] 44%|████▍ | 40/90 [00:07<00:09, 5.33it/s] 46%|████▌ | 41/90 [00:07<00:09, 5.34it/s] 47%|████▋ | 42/90 [00:07<00:08, 5.33it/s] 48%|████▊ | 43/90 [00:08<00:08, 5.33it/s] 49%|████▉ | 44/90 [00:08<00:08, 5.36it/s] 50%|█████ | 45/90 [00:08<00:08, 5.36it/s] 51%|█████ | 46/90 [00:08<00:08, 5.36it/s] 52%|█████▏ | 47/90 [00:08<00:08, 5.34it/s] 53%|█████▎ | 48/90 [00:08<00:07, 5.35it/s] 54%|█████▍ | 49/90 [00:09<00:07, 5.38it/s] 56%|█████▌ | 50/90 [00:09<00:07, 5.39it/s] 57%|█████▋ | 51/90 [00:09<00:07, 5.38it/s] 58%|█████▊ | 52/90 [00:09<00:07, 5.34it/s] 59%|█████▉ | 53/90 [00:09<00:06, 5.33it/s] 60%|██████ | 54/90 [00:10<00:06, 5.35it/s] 61%|██████ | 55/90 [00:10<00:06, 5.34it/s] 62%|██████▏ | 56/90 [00:10<00:06, 5.32it/s] 63%|██████▎ | 57/90 [00:10<00:06, 5.33it/s] 64%|██████▍ | 58/90 [00:10<00:06, 5.32it/s] 66%|██████▌ | 59/90 [00:11<00:05, 5.31it/s] 67%|██████▋ | 60/90 [00:11<00:05, 5.31it/s] 68%|██████▊ | 61/90 [00:11<00:05, 5.32it/s] 69%|██████▉ | 62/90 [00:11<00:05, 5.30it/s] 70%|███████ | 63/90 [00:11<00:05, 5.32it/s] 71%|███████ | 64/90 [00:11<00:04, 5.32it/s] 72%|███████▏ | 65/90 [00:12<00:04, 5.30it/s] 73%|███████▎ | 66/90 [00:12<00:04, 5.31it/s] 74%|███████▍ | 67/90 [00:12<00:04, 5.33it/s] 76%|███████▌ | 68/90 [00:12<00:04, 5.33it/s] 77%|███████▋ | 69/90 [00:12<00:03, 5.31it/s] 78%|███████▊ | 70/90 [00:13<00:03, 5.32it/s] 79%|███████▉ | 71/90 [00:13<00:03, 5.31it/s] 80%|████████ | 72/90 [00:13<00:03, 5.30it/s] 81%|████████ | 73/90 [00:13<00:03, 5.32it/s] 82%|████████▏ | 74/90 [00:13<00:03, 5.30it/s] 83%|████████▎ | 75/90 [00:14<00:02, 5.28it/s] 84%|████████▍ | 76/90 [00:14<00:02, 5.30it/s] 86%|████████▌ | 77/90 [00:14<00:02, 5.31it/s] 87%|████████▋ | 78/90 [00:14<00:02, 5.28it/s] 88%|████████▊ | 79/90 [00:14<00:02, 5.32it/s] 89%|████████▉ | 80/90 [00:14<00:01, 5.30it/s] 90%|█████████ | 81/90 [00:15<00:01, 5.27it/s] 91%|█████████ | 82/90 [00:15<00:01, 5.29it/s] 92%|█████████▏| 83/90 [00:15<00:01, 5.27it/s] 93%|█████████▎| 84/90 [00:15<00:01, 5.29it/s] 94%|█████████▍| 85/90 [00:15<00:00, 5.31it/s] 96%|█████████▌| 86/90 [00:16<00:00, 5.28it/s] 97%|█████████▋| 87/90 [00:16<00:00, 5.30it/s] 98%|█████████▊| 88/90 [00:16<00:00, 5.31it/s] 99%|█████████▉| 89/90 [00:16<00:00, 5.29it/s] 100%|██████████| 90/90 [00:16<00:00, 5.30it/s] 100%|██████████| 90/90 [00:16<00:00, 5.33it/s]
Version Details
- Version ID
235647b5791eedd2c58d9ccdf32328b8083143a2b0e68148da6ef30731453443
- Version Created
- April 10, 2023