mcgregory99/goyofacebooth 🔢🖼️❓📝✓ → 🖼️
About
Example Output
Prompt:
"Capture the essence of professionalism with an 8k, meticulously detailed corporate portrait headshot photograph. This stunning image features a distinguished gycn person in a suit, radiating confidence and elegance. This hyperrealistic masterpiece is hailed as the best corporate photo winner, showcasing an unrivaled level of perfection."
Output


Performance Metrics
52.27s
Prediction Time
52.29s
Total Time
All Input Parameters
{
"seed": 1312,
"width": 512,
"height": 512,
"prompt": "Capture the essence of professionalism with an 8k, meticulously detailed corporate portrait headshot photograph. This stunning image features a distinguished gycn person in a suit, radiating confidence and elegance. This hyperrealistic masterpiece is hailed as the best corporate photo winner, showcasing an unrivaled level of perfection.",
"scheduler": "KLMS",
"num_outputs": 3,
"guidance_scale": 7.5,
"prompt_strength": 0.7,
"num_inference_steps": 80,
"disable_safety_check": false
}
Input Parameters
- seed
- Random seed. Leave blank to randomize the seed
- image
- A starting image from which to generate variations (aka 'img2img'). If this input is set, the `width` and `height` inputs are ignored and the output will have the same dimensions as the input image.
- 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.
- guidance_scale
- Scale for classifier-free guidance
- negative_prompt
- Specify things to not see in the output
- prompt_strength
- Prompt strength when using init image. 1.0 corresponds to full destruction of information in init image
- num_inference_steps
- Number of denoising steps
- disable_safety_check
- Disable safety check. Use at your own risk!
Output Schema
Output
Example Execution Logs
Using seed: 1312 using txt2img 0%| | 0/80 [00:00<?, ?it/s] 1%|▏ | 1/80 [00:00<00:47, 1.65it/s] 2%|▎ | 2/80 [00:01<00:47, 1.66it/s] 4%|▍ | 3/80 [00:01<00:45, 1.68it/s] 5%|▌ | 4/80 [00:02<00:45, 1.66it/s] 6%|▋ | 5/80 [00:02<00:44, 1.67it/s] 8%|▊ | 6/80 [00:03<00:44, 1.67it/s] 9%|▉ | 7/80 [00:04<00:43, 1.67it/s] 10%|█ | 8/80 [00:04<00:43, 1.66it/s] 11%|█▏ | 9/80 [00:05<00:42, 1.66it/s] 12%|█▎ | 10/80 [00:06<00:42, 1.66it/s] 14%|█▍ | 11/80 [00:06<00:41, 1.65it/s] 15%|█▌ | 12/80 [00:07<00:41, 1.65it/s] 16%|█▋ | 13/80 [00:07<00:40, 1.65it/s] 18%|█▊ | 14/80 [00:08<00:40, 1.65it/s] 19%|█▉ | 15/80 [00:09<00:39, 1.64it/s] 20%|██ | 16/80 [00:09<00:39, 1.63it/s] 21%|██▏ | 17/80 [00:10<00:38, 1.63it/s] 22%|██▎ | 18/80 [00:10<00:38, 1.63it/s] 24%|██▍ | 19/80 [00:11<00:37, 1.62it/s] 25%|██▌ | 20/80 [00:12<00:37, 1.62it/s] 26%|██▋ | 21/80 [00:12<00:36, 1.62it/s] 28%|██▊ | 22/80 [00:13<00:36, 1.60it/s] 29%|██▉ | 23/80 [00:14<00:35, 1.60it/s] 30%|███ | 24/80 [00:14<00:35, 1.59it/s] 31%|███▏ | 25/80 [00:15<00:34, 1.59it/s] 32%|███▎ | 26/80 [00:15<00:33, 1.59it/s] 34%|███▍ | 27/80 [00:16<00:33, 1.59it/s] 35%|███▌ | 28/80 [00:17<00:32, 1.59it/s] 36%|███▋ | 29/80 [00:17<00:32, 1.58it/s] 38%|███▊ | 30/80 [00:18<00:31, 1.58it/s] 39%|███▉ | 31/80 [00:19<00:31, 1.57it/s] 40%|████ | 32/80 [00:19<00:30, 1.56it/s] 41%|████▏ | 33/80 [00:20<00:30, 1.56it/s] 42%|████▎ | 34/80 [00:21<00:29, 1.55it/s] 44%|████▍ | 35/80 [00:21<00:28, 1.55it/s] 45%|████▌ | 36/80 [00:22<00:28, 1.55it/s] 46%|████▋ | 37/80 [00:22<00:27, 1.55it/s] 48%|████▊ | 38/80 [00:23<00:27, 1.54it/s] 49%|████▉ | 39/80 [00:24<00:26, 1.54it/s] 50%|█████ | 40/80 [00:24<00:25, 1.54it/s] 51%|█████▏ | 41/80 [00:25<00:25, 1.54it/s] 52%|█████▎ | 42/80 [00:26<00:24, 1.54it/s] 54%|█████▍ | 43/80 [00:26<00:24, 1.53it/s] 55%|█████▌ | 44/80 [00:27<00:23, 1.52it/s] 56%|█████▋ | 45/80 [00:28<00:22, 1.52it/s] 57%|█████▊ | 46/80 [00:28<00:22, 1.52it/s] 59%|█████▉ | 47/80 [00:29<00:21, 1.52it/s] 60%|██████ | 48/80 [00:30<00:21, 1.52it/s] 61%|██████▏ | 49/80 [00:30<00:20, 1.52it/s] 62%|██████▎ | 50/80 [00:31<00:19, 1.53it/s] 64%|██████▍ | 51/80 [00:32<00:18, 1.53it/s] 65%|██████▌ | 52/80 [00:32<00:18, 1.53it/s] 66%|██████▋ | 53/80 [00:33<00:17, 1.53it/s] 68%|██████▊ | 54/80 [00:34<00:16, 1.54it/s] 69%|██████▉ | 55/80 [00:34<00:16, 1.54it/s] 70%|███████ | 56/80 [00:35<00:15, 1.54it/s] 71%|███████▏ | 57/80 [00:36<00:14, 1.55it/s] 72%|███████▎ | 58/80 [00:36<00:14, 1.55it/s] 74%|███████▍ | 59/80 [00:37<00:13, 1.56it/s] 75%|███████▌ | 60/80 [00:37<00:12, 1.56it/s] 76%|███████▋ | 61/80 [00:38<00:12, 1.56it/s] 78%|███████▊ | 62/80 [00:39<00:11, 1.57it/s] 79%|███████▉ | 63/80 [00:39<00:10, 1.57it/s] 80%|████████ | 64/80 [00:40<00:10, 1.58it/s] 81%|████████▏ | 65/80 [00:41<00:09, 1.59it/s] 82%|████████▎ | 66/80 [00:41<00:08, 1.58it/s] 84%|████████▍ | 67/80 [00:42<00:08, 1.59it/s] 85%|████████▌ | 68/80 [00:42<00:07, 1.59it/s] 86%|████████▋ | 69/80 [00:43<00:06, 1.60it/s] 88%|████████▊ | 70/80 [00:44<00:06, 1.60it/s] 89%|████████▉ | 71/80 [00:44<00:05, 1.60it/s] 90%|█████████ | 72/80 [00:45<00:04, 1.61it/s] 91%|█████████▏| 73/80 [00:46<00:04, 1.61it/s] 92%|█████████▎| 74/80 [00:46<00:03, 1.62it/s] 94%|█████████▍| 75/80 [00:47<00:03, 1.62it/s] 95%|█████████▌| 76/80 [00:47<00:02, 1.62it/s] 96%|█████████▋| 77/80 [00:48<00:01, 1.63it/s] 98%|█████████▊| 78/80 [00:49<00:01, 1.61it/s] 99%|█████████▉| 79/80 [00:49<00:00, 1.62it/s] 100%|██████████| 80/80 [00:50<00:00, 1.63it/s] 100%|██████████| 80/80 [00:50<00:00, 1.59it/s]
Version Details
- Version ID
6e688d1ea46cb252b0334b3842ccad3ead53ecd2d0ffac2e21ffd2800bb30963- Version Created
- February 16, 2024