owengillett/winstondog π’πΌοΈβπβ β πΌοΈ
About
Example Output
"a colonial era portrait of [winstondog], a dog sitting at a desk. Faces of America. [winstondog], a dog, is dressed in 18th century clothing. The sitterβs costume distinguish this colonial portrait of Abigail Smith Babcock, a wealthy Bostonian. John Singleton Copley was a painter talented in both the art and business of his chosen trade. The colonial economy boomed over the course of the 18th century and produced a new class of wealthy Americans, some originally from England or the Netherlands, others born on American soil. While in America, Copley specialized in portraits of this new gentry, who were mercantile and landowning families. This new βaristocracyβ was British by nationality and emulated the appearances and ways of the British upper class back at home, acquiring goods and fashions from England. [winstondog]'s attire would have been over the top in either Boston or New Haven in 1764. Similar garments appear in several of Copleyβs other portraits and it is known that he offered sitters a choice of fancy dress in which to be pictured, based on prints of fashionable people obtained from Europe."
Output



Performance Metrics
All Input Parameters
{
"seed": 10,
"width": 512,
"height": 512,
"prompt": "a colonial era portrait of [winstondog], a dog sitting at a desk. Faces of America. [winstondog], a dog, is dressed in 18th century clothing. The sitterβs costume distinguish this colonial portrait of Abigail Smith Babcock, a wealthy Bostonian. John Singleton Copley was a painter talented in both the art and business of his chosen trade. The colonial economy boomed over the course of the 18th century and produced a new class of wealthy Americans, some originally from England or the Netherlands, others born on American soil. While in America, Copley specialized in portraits of this new gentry, who were mercantile and landowning families. This new βaristocracyβ was British by nationality and emulated the appearances and ways of the British upper class back at home, acquiring goods and fashions from England. [winstondog]'s attire would have been over the top in either Boston or New Haven in 1764. Similar garments appear in several of Copleyβs other portraits and it is known that he offered sitters a choice of fancy dress in which to be pictured, based on prints of fashionable people obtained from Europe.",
"scheduler": "DDIM",
"num_outputs": 4,
"guidance_scale": 8,
"negative_prompt": "overexposed, text, signature, cropped, out of frame, low resolution, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, poorly drawn hands, poorly drawn face, deformed, blurry, dehydrated, bad anatomy, disfigured, malformed limbs, ugly eyes, fused lips and teeth",
"prompt_strength": 1,
"num_inference_steps": 100
}
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: 10 using txt2img The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['trade. the colonial economy boomed over the course of the 1 8 th century and produced a new class of wealthy americans, some originally from england or the netherlands, others born on american soil. while in america, copley specialized in portraits of this new gentry, who were mercantile and landowning families. this new " aristocracy " was british by nationality and emulated the appearances and ways of the british upper class back at home, acquiring goods and fashions from england. [ winstondog ]\' s attire would have been over the top in either boston or new haven in 1 7 6 4. similar garments appear in several of copley\'s other portraits and it is known that he offered sitters a choice of fancy dress in which to be pictured, based on prints of fashionable people obtained from europe.', 'trade. the colonial economy boomed over the course of the 1 8 th century and produced a new class of wealthy americans, some originally from england or the netherlands, others born on american soil. while in america, copley specialized in portraits of this new gentry, who were mercantile and landowning families. this new " aristocracy " was british by nationality and emulated the appearances and ways of the british upper class back at home, acquiring goods and fashions from england. [ winstondog ]\' s attire would have been over the top in either boston or new haven in 1 7 6 4. similar garments appear in several of copley\'s other portraits and it is known that he offered sitters a choice of fancy dress in which to be pictured, based on prints of fashionable people obtained from europe.', 'trade. the colonial economy boomed over the course of the 1 8 th century and produced a new class of wealthy americans, some originally from england or the netherlands, others born on american soil. while in america, copley specialized in portraits of this new gentry, who were mercantile and landowning families. this new " aristocracy " was british by nationality and emulated the appearances and ways of the british upper class back at home, acquiring goods and fashions from england. [ winstondog ]\' s attire would have been over the top in either boston or new haven in 1 7 6 4. similar garments appear in several of copley\'s other portraits and it is known that he offered sitters a choice of fancy dress in which to be pictured, based on prints of fashionable people obtained from europe.', 'trade. the colonial economy boomed over the course of the 1 8 th century and produced a new class of wealthy americans, some originally from england or the netherlands, others born on american soil. while in america, copley specialized in portraits of this new gentry, who were mercantile and landowning families. this new " aristocracy " was british by nationality and emulated the appearances and ways of the british upper class back at home, acquiring goods and fashions from england. [ winstondog ]\' s attire would have been over the top in either boston or new haven in 1 7 6 4. similar garments appear in several of copley\'s other portraits and it is known that he offered sitters a choice of fancy dress in which to be pictured, based on prints of fashionable people obtained from europe.'] 0%| | 0/100 [00:00<?, ?it/s] 1%| | 1/100 [00:00<01:10, 1.40it/s] 2%|β | 2/100 [00:01<01:10, 1.39it/s] 3%|β | 3/100 [00:02<01:09, 1.40it/s] 4%|β | 4/100 [00:02<01:08, 1.40it/s] 5%|β | 5/100 [00:03<01:07, 1.40it/s] 6%|β | 6/100 [00:04<01:07, 1.40it/s] 7%|β | 7/100 [00:05<01:06, 1.40it/s] 8%|β | 8/100 [00:05<01:06, 1.39it/s] 9%|β | 9/100 [00:06<01:05, 1.39it/s] 10%|β | 10/100 [00:07<01:04, 1.39it/s] 11%|β | 11/100 [00:07<01:03, 1.39it/s] 12%|ββ | 12/100 [00:08<01:03, 1.39it/s] 13%|ββ | 13/100 [00:09<01:02, 1.39it/s] 14%|ββ | 14/100 [00:10<01:02, 1.38it/s] 15%|ββ | 15/100 [00:10<01:01, 1.38it/s] 16%|ββ | 16/100 [00:11<01:01, 1.38it/s] 17%|ββ | 17/100 [00:12<01:00, 1.38it/s] 18%|ββ | 18/100 [00:12<00:59, 1.37it/s] 19%|ββ | 19/100 [00:13<00:59, 1.37it/s] 20%|ββ | 20/100 [00:14<00:58, 1.37it/s] 21%|ββ | 21/100 [00:15<00:57, 1.37it/s] 22%|βββ | 22/100 [00:15<00:56, 1.37it/s] 23%|βββ | 23/100 [00:16<00:56, 1.37it/s] 24%|βββ | 24/100 [00:17<00:55, 1.37it/s] 25%|βββ | 25/100 [00:18<00:54, 1.37it/s] 26%|βββ | 26/100 [00:18<00:53, 1.37it/s] 27%|βββ | 27/100 [00:19<00:53, 1.37it/s] 28%|βββ | 28/100 [00:20<00:52, 1.37it/s] 29%|βββ | 29/100 [00:21<00:51, 1.37it/s] 30%|βββ | 30/100 [00:21<00:51, 1.36it/s] 31%|βββ | 31/100 [00:22<00:50, 1.36it/s] 32%|ββββ | 32/100 [00:23<00:50, 1.36it/s] 33%|ββββ | 33/100 [00:23<00:49, 1.36it/s] 34%|ββββ | 34/100 [00:24<00:48, 1.35it/s] 35%|ββββ | 35/100 [00:25<00:47, 1.36it/s] 36%|ββββ | 36/100 [00:26<00:47, 1.35it/s] 37%|ββββ | 37/100 [00:26<00:46, 1.35it/s] 38%|ββββ | 38/100 [00:27<00:45, 1.35it/s] 39%|ββββ | 39/100 [00:28<00:45, 1.35it/s] 40%|ββββ | 40/100 [00:29<00:44, 1.34it/s] 41%|ββββ | 41/100 [00:29<00:43, 1.34it/s] 42%|βββββ | 42/100 [00:30<00:43, 1.34it/s] 43%|βββββ | 43/100 [00:31<00:42, 1.34it/s] 44%|βββββ | 44/100 [00:32<00:41, 1.34it/s] 45%|βββββ | 45/100 [00:32<00:41, 1.34it/s] 46%|βββββ | 46/100 [00:33<00:40, 1.34it/s] 47%|βββββ | 47/100 [00:34<00:39, 1.33it/s] 48%|βββββ | 48/100 [00:35<00:39, 1.33it/s] 49%|βββββ | 49/100 [00:35<00:38, 1.33it/s] 50%|βββββ | 50/100 [00:36<00:37, 1.33it/s] 51%|βββββ | 51/100 [00:37<00:36, 1.33it/s] 52%|ββββββ | 52/100 [00:38<00:36, 1.33it/s] 53%|ββββββ | 53/100 [00:38<00:35, 1.33it/s] 54%|ββββββ | 54/100 [00:39<00:34, 1.33it/s] 55%|ββββββ | 55/100 [00:40<00:33, 1.33it/s] 56%|ββββββ | 56/100 [00:41<00:33, 1.33it/s] 57%|ββββββ | 57/100 [00:41<00:32, 1.33it/s] 58%|ββββββ | 58/100 [00:42<00:31, 1.33it/s] 59%|ββββββ | 59/100 [00:43<00:30, 1.33it/s] 60%|ββββββ | 60/100 [00:44<00:30, 1.33it/s] 61%|ββββββ | 61/100 [00:44<00:29, 1.33it/s] 62%|βββββββ | 62/100 [00:45<00:28, 1.33it/s] 63%|βββββββ | 63/100 [00:46<00:27, 1.33it/s] 64%|βββββββ | 64/100 [00:47<00:27, 1.33it/s] 65%|βββββββ | 65/100 [00:47<00:26, 1.33it/s] 66%|βββββββ | 66/100 [00:48<00:25, 1.33it/s] 67%|βββββββ | 67/100 [00:49<00:24, 1.32it/s] 68%|βββββββ | 68/100 [00:50<00:24, 1.32it/s] 69%|βββββββ | 69/100 [00:50<00:23, 1.32it/s] 70%|βββββββ | 70/100 [00:51<00:22, 1.31it/s] 71%|βββββββ | 71/100 [00:52<00:22, 1.31it/s] 72%|ββββββββ | 72/100 [00:53<00:21, 1.31it/s] 73%|ββββββββ | 73/100 [00:54<00:20, 1.31it/s] 74%|ββββββββ | 74/100 [00:54<00:19, 1.31it/s] 75%|ββββββββ | 75/100 [00:55<00:19, 1.31it/s] 76%|ββββββββ | 76/100 [00:56<00:18, 1.31it/s] 77%|ββββββββ | 77/100 [00:57<00:17, 1.31it/s] 78%|ββββββββ | 78/100 [00:57<00:16, 1.31it/s] 79%|ββββββββ | 79/100 [00:58<00:16, 1.31it/s] 80%|ββββββββ | 80/100 [00:59<00:15, 1.31it/s] 81%|ββββββββ | 81/100 [01:00<00:14, 1.31it/s] 82%|βββββββββ | 82/100 [01:00<00:13, 1.31it/s] 83%|βββββββββ | 83/100 [01:01<00:13, 1.31it/s] 84%|βββββββββ | 84/100 [01:02<00:12, 1.31it/s] 85%|βββββββββ | 85/100 [01:03<00:11, 1.31it/s] 86%|βββββββββ | 86/100 [01:03<00:10, 1.31it/s] 87%|βββββββββ | 87/100 [01:04<00:09, 1.31it/s] 88%|βββββββββ | 88/100 [01:05<00:09, 1.31it/s] 89%|βββββββββ | 89/100 [01:06<00:08, 1.31it/s] 90%|βββββββββ | 90/100 [01:07<00:07, 1.31it/s] 91%|βββββββββ | 91/100 [01:07<00:06, 1.31it/s] 92%|ββββββββββ| 92/100 [01:08<00:06, 1.30it/s] 93%|ββββββββββ| 93/100 [01:09<00:05, 1.30it/s] 94%|ββββββββββ| 94/100 [01:10<00:04, 1.30it/s] 95%|ββββββββββ| 95/100 [01:10<00:03, 1.30it/s] 96%|ββββββββββ| 96/100 [01:11<00:03, 1.30it/s] 97%|ββββββββββ| 97/100 [01:12<00:02, 1.30it/s] 98%|ββββββββββ| 98/100 [01:13<00:01, 1.30it/s] 99%|ββββββββββ| 99/100 [01:13<00:00, 1.30it/s] 100%|ββββββββββ| 100/100 [01:14<00:00, 1.30it/s] 100%|ββββββββββ| 100/100 [01:14<00:00, 1.34it/s]
Version Details
- Version ID
0733ba20b88c6406826c9b93375e008c7ab33d1367cb37edc191dca0775a7890- Version Created
- April 17, 2023