misbahsy / woolitize-diffusion
Diffusion model to generate Woolitize images
- Public
- 174 runs
-
T4
- License
Prediction
misbahsy/woolitize-diffusion:5411e9efb858ef003e1c2787181c29d9592c7eba9a436597bf303ecb0b2667f8ID7dbvpfilmfebdimt64nhmnat7mStatusSucceededSourceWebHardware–Total durationCreatedInput
- width
- 512
- height
- 512
- prompt
- woolitize an upper body shot photo of Keanu Reeves as Neo from the matrix, higly detailed face, 85 mm, HD, 8k
- scheduler
- K-LMS
- num_outputs
- 1
- guidance_scale
- 7.5
- negative_prompt
- ugly, disfigured
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 512, "height": 512, "prompt": "woolitize an upper body shot photo of Keanu Reeves as Neo from the matrix, higly detailed face, 85 mm, HD, 8k", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run misbahsy/woolitize-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "misbahsy/woolitize-diffusion:5411e9efb858ef003e1c2787181c29d9592c7eba9a436597bf303ecb0b2667f8", { input: { width: 512, height: 512, prompt: "woolitize an upper body shot photo of Keanu Reeves as Neo from the matrix, higly detailed face, 85 mm, HD, 8k", scheduler: "K-LMS", num_outputs: 1, guidance_scale: 7.5, negative_prompt: "ugly, disfigured", prompt_strength: 0.8, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun misbahsy/woolitize-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "misbahsy/woolitize-diffusion:5411e9efb858ef003e1c2787181c29d9592c7eba9a436597bf303ecb0b2667f8", input={ "width": 512, "height": 512, "prompt": "woolitize an upper body shot photo of Keanu Reeves as Neo from the matrix, higly detailed face, 85 mm, HD, 8k", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run misbahsy/woolitize-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "misbahsy/woolitize-diffusion:5411e9efb858ef003e1c2787181c29d9592c7eba9a436597bf303ecb0b2667f8", "input": { "width": 512, "height": 512, "prompt": "woolitize an upper body shot photo of Keanu Reeves as Neo from the matrix, higly detailed face, 85 mm, HD, 8k", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-01-11T20:24:44.421285Z", "created_at": "2023-01-11T20:24:29.357859Z", "data_removed": false, "error": null, "id": "7dbvpfilmfebdimt64nhmnat7m", "input": { "width": 512, "height": 512, "prompt": "woolitize an upper body shot photo of Keanu Reeves as Neo from the matrix, higly detailed face, 85 mm, HD, 8k", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 57167\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:18, 2.65it/s]\n 4%|▍ | 2/50 [00:00<00:15, 3.13it/s]\n 6%|▌ | 3/50 [00:00<00:14, 3.32it/s]\n 8%|▊ | 4/50 [00:01<00:13, 3.40it/s]\n 10%|█ | 5/50 [00:01<00:13, 3.45it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.49it/s]\n 14%|█▍ | 7/50 [00:02<00:12, 3.50it/s]\n 16%|█▌ | 8/50 [00:02<00:12, 3.49it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.51it/s]\n 20%|██ | 10/50 [00:02<00:11, 3.52it/s]\n 22%|██▏ | 11/50 [00:03<00:11, 3.52it/s]\n 24%|██▍ | 12/50 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"2023-01-11T20:24:29.404225Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7dbvpfilmfebdimt64nhmnat7m", "cancel": "https://api.replicate.com/v1/predictions/7dbvpfilmfebdimt64nhmnat7m/cancel" }, "version": "5411e9efb858ef003e1c2787181c29d9592c7eba9a436597bf303ecb0b2667f8" }Generated inUsing seed: 57167 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:18, 2.65it/s] 4%|▍ | 2/50 [00:00<00:15, 3.13it/s] 6%|▌ | 3/50 [00:00<00:14, 3.32it/s] 8%|▊ | 4/50 [00:01<00:13, 3.40it/s] 10%|█ | 5/50 [00:01<00:13, 3.45it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.49it/s] 14%|█▍ | 7/50 [00:02<00:12, 3.50it/s] 16%|█▌ | 8/50 [00:02<00:12, 3.49it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.51it/s] 20%|██ | 10/50 [00:02<00:11, 3.52it/s] 22%|██▏ | 11/50 [00:03<00:11, 3.52it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.51it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.52it/s] 28%|██▊ | 14/50 [00:04<00:10, 3.52it/s] 30%|███ | 15/50 [00:04<00:09, 3.52it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.52it/s] 34%|███▍ | 17/50 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misbahsy/woolitize-diffusion:5411e9efb858ef003e1c2787181c29d9592c7eba9a436597bf303ecb0b2667f8Input
- width
- 512
- height
- 512
- prompt
- woolitize photo of elon musk
- scheduler
- K-LMS
- num_outputs
- 1
- guidance_scale
- 7.5
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 512, "height": 512, "prompt": "woolitize photo of elon musk", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run misbahsy/woolitize-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "misbahsy/woolitize-diffusion:5411e9efb858ef003e1c2787181c29d9592c7eba9a436597bf303ecb0b2667f8", { input: { width: 512, height: 512, prompt: "woolitize photo of elon musk", scheduler: "K-LMS", num_outputs: 1, guidance_scale: 7.5, prompt_strength: 0.8, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun misbahsy/woolitize-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "misbahsy/woolitize-diffusion:5411e9efb858ef003e1c2787181c29d9592c7eba9a436597bf303ecb0b2667f8", input={ "width": 512, "height": 512, "prompt": "woolitize photo of elon musk", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run misbahsy/woolitize-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "misbahsy/woolitize-diffusion:5411e9efb858ef003e1c2787181c29d9592c7eba9a436597bf303ecb0b2667f8", "input": { "width": 512, "height": 512, "prompt": "woolitize photo of elon musk", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-01-11T20:13:21.537130Z", "created_at": "2023-01-11T20:13:06.173890Z", "data_removed": false, "error": null, "id": "ih5m7ntu6nbv3hmcbdpsm62zum", "input": { "width": 512, "height": 512, "prompt": "woolitize photo of elon musk", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 22267\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:17, 2.78it/s]\n 4%|▍ | 2/50 [00:00<00:14, 3.22it/s]\n 6%|▌ | 3/50 [00:00<00:13, 3.39it/s]\n 8%|▊ | 4/50 [00:01<00:13, 3.45it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.49it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.52it/s]\n 14%|█▍ | 7/50 [00:02<00:12, 3.55it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.55it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.55it/s]\n 20%|██ | 10/50 [00:02<00:11, 3.56it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.58it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.56it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.56it/s]\n 28%|██▊ | 14/50 [00:03<00:10, 3.56it/s]\n 30%|███ | 15/50 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3.53it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.53it/s]\n 78%|███████▊ | 39/50 [00:11<00:03, 3.53it/s]\n 80%|████████ | 40/50 [00:11<00:02, 3.52it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.53it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.54it/s]\n 86%|████████▌ | 43/50 [00:12<00:01, 3.54it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.53it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.54it/s]\n 92%|█████████▏| 46/50 [00:13<00:01, 3.54it/s]\n 94%|█████████▍| 47/50 [00:13<00:00, 3.54it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.54it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.53it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.54it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.53it/s]", "metrics": { "predict_time": 15.312194, "total_time": 15.36324 }, "output": [ "https://replicate.delivery/pbxt/A1q4R3BNSw6TO9q5zyH0ekCjc77pMgzawv7IGlPR2TLwUmJIA/out-0.png" ], "started_at": "2023-01-11T20:13:06.224936Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ih5m7ntu6nbv3hmcbdpsm62zum", "cancel": "https://api.replicate.com/v1/predictions/ih5m7ntu6nbv3hmcbdpsm62zum/cancel" }, "version": "5411e9efb858ef003e1c2787181c29d9592c7eba9a436597bf303ecb0b2667f8" }Generated inUsing seed: 22267 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:17, 2.78it/s] 4%|▍ | 2/50 [00:00<00:14, 3.22it/s] 6%|▌ | 3/50 [00:00<00:13, 3.39it/s] 8%|▊ | 4/50 [00:01<00:13, 3.45it/s] 10%|█ | 5/50 [00:01<00:12, 3.49it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.52it/s] 14%|█▍ | 7/50 [00:02<00:12, 3.55it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.55it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.55it/s] 20%|██ | 10/50 [00:02<00:11, 3.56it/s] 22%|██▏ | 11/50 [00:03<00:10, 3.58it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.56it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.56it/s] 28%|██▊ | 14/50 [00:03<00:10, 3.56it/s] 30%|███ | 15/50 [00:04<00:09, 3.55it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.55it/s] 34%|███▍ | 17/50 [00:04<00:09, 3.56it/s] 36%|███▌ | 18/50 [00:05<00:08, 3.56it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.57it/s] 40%|████ | 20/50 [00:05<00:08, 3.56it/s] 42%|████▏ | 21/50 [00:05<00:08, 3.56it/s] 44%|████▍ | 22/50 [00:06<00:07, 3.56it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.55it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.55it/s] 50%|█████ | 25/50 [00:07<00:07, 3.55it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.56it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.55it/s] 56%|█████▌ | 28/50 [00:07<00:06, 3.55it/s] 58%|█████▊ | 29/50 [00:08<00:05, 3.55it/s] 60%|██████ | 30/50 [00:08<00:05, 3.55it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.54it/s] 64%|██████▍ | 32/50 [00:09<00:05, 3.54it/s] 66%|██████▌ | 33/50 [00:09<00:04, 3.54it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.53it/s] 70%|███████ | 35/50 [00:09<00:04, 3.53it/s] 72%|███████▏ | 36/50 [00:10<00:03, 3.53it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.53it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.53it/s] 78%|███████▊ | 39/50 [00:11<00:03, 3.53it/s] 80%|████████ | 40/50 [00:11<00:02, 3.52it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.53it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.54it/s] 86%|████████▌ | 43/50 [00:12<00:01, 3.54it/s] 88%|████████▊ | 44/50 [00:12<00:01, 3.53it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.54it/s] 92%|█████████▏| 46/50 [00:13<00:01, 3.54it/s] 94%|█████████▍| 47/50 [00:13<00:00, 3.54it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.54it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.53it/s] 100%|██████████| 50/50 [00:14<00:00, 3.54it/s] 100%|██████████| 50/50 [00:14<00:00, 3.53it/s]
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