yuni-eng
/
inpainting
Mockup generator (bags, t-shirts, mugs, billboard etc) using Stable Diffusion in-painting
Prediction
yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752IDmkfcar3bpqzekis53vkej2ih6aStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 0
- prompt
- illustration of takashi murakami house next to a waterfall
- num_outputs
- 1
- guidance_scale
- 20
- negative_prompt
- poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling
- num_inference_steps
- 200
{ "mask": "https://replicate.delivery/pbxt/JuynKj9IO2816Mi6Ik3ynj37p9pj3eQypTf0rUjZIhsjL09t/Screenshot%202023-11-21%20at%202.40.57%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuynKtxWiFnpNEFIcz1UoWHb6WIJUuilToxGyn9ARsks5RR1/totebag.png", "prompt": "illustration of takashi murakami house next to a waterfall", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run yuni-eng/inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", { input: { mask: "https://replicate.delivery/pbxt/JuynKj9IO2816Mi6Ik3ynj37p9pj3eQypTf0rUjZIhsjL09t/Screenshot%202023-11-21%20at%202.40.57%20PM.png", seed: 0, image: "https://replicate.delivery/pbxt/JuynKtxWiFnpNEFIcz1UoWHb6WIJUuilToxGyn9ARsks5RR1/totebag.png", prompt: "illustration of takashi murakami house next to a waterfall", num_outputs: 1, guidance_scale: 20, negative_prompt: "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", num_inference_steps: 200 } } ); // 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 replicate
Import the client:import replicate
Run yuni-eng/inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", input={ "mask": "https://replicate.delivery/pbxt/JuynKj9IO2816Mi6Ik3ynj37p9pj3eQypTf0rUjZIhsjL09t/Screenshot%202023-11-21%20at%202.40.57%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuynKtxWiFnpNEFIcz1UoWHb6WIJUuilToxGyn9ARsks5RR1/totebag.png", "prompt": "illustration of takashi murakami house next to a waterfall", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run yuni-eng/inpainting 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": "062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", "input": { "mask": "https://replicate.delivery/pbxt/JuynKj9IO2816Mi6Ik3ynj37p9pj3eQypTf0rUjZIhsjL09t/Screenshot%202023-11-21%20at%202.40.57%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuynKtxWiFnpNEFIcz1UoWHb6WIJUuilToxGyn9ARsks5RR1/totebag.png", "prompt": "illustration of takashi murakami house next to a waterfall", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-30T03:23:10.098151Z", "created_at": "2023-11-30T03:21:21.875804Z", "data_removed": false, "error": null, "id": "mkfcar3bpqzekis53vkej2ih6a", "input": { "mask": "https://replicate.delivery/pbxt/JuynKj9IO2816Mi6Ik3ynj37p9pj3eQypTf0rUjZIhsjL09t/Screenshot%202023-11-21%20at%202.40.57%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuynKtxWiFnpNEFIcz1UoWHb6WIJUuilToxGyn9ARsks5RR1/totebag.png", "prompt": "illustration of takashi murakami house next to a waterfall", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 }, "logs": "Using seed: 22252\n 0%| | 0/200 [00:00<?, ?it/s]\n 0%| | 1/200 [00:00<00:27, 7.15it/s]\n 2%|▏ | 4/200 [00:00<00:10, 17.94it/s]\n 4%|▎ | 7/200 [00:00<00:08, 22.05it/s]\n 5%|▌ | 10/200 [00:00<00:07, 24.12it/s]\n 6%|▋ | 13/200 [00:00<00:07, 25.29it/s]\n 8%|▊ | 16/200 [00:00<00:07, 26.02it/s]\n 10%|▉ | 19/200 [00:00<00:06, 26.47it/s]\n 11%|█ | 22/200 [00:00<00:06, 26.77it/s]\n 12%|█▎ | 25/200 [00:01<00:06, 26.97it/s]\n 14%|█▍ | 28/200 [00:01<00:06, 27.07it/s]\n 16%|█▌ | 31/200 [00:01<00:06, 27.18it/s]\n 17%|█▋ | 34/200 [00:01<00:06, 27.22it/s]\n 18%|█▊ | 37/200 [00:01<00:05, 27.28it/s]\n 20%|██ | 40/200 [00:01<00:05, 27.28it/s]\n 22%|██▏ | 43/200 [00:01<00:05, 27.29it/s]\n 23%|██▎ | 46/200 [00:01<00:05, 27.30it/s]\n 24%|██▍ | 49/200 [00:01<00:05, 27.31it/s]\n 26%|██▌ | 52/200 [00:02<00:05, 27.32it/s]\n 28%|██▊ | 55/200 [00:02<00:05, 27.33it/s]\n 29%|██▉ | 58/200 [00:02<00:05, 27.28it/s]\n 30%|███ | 61/200 [00:02<00:05, 27.32it/s]\n 32%|███▏ | 64/200 [00:02<00:04, 27.34it/s]\n 34%|███▎ | 67/200 [00:02<00:04, 27.33it/s]\n 35%|███▌ | 70/200 [00:02<00:04, 27.31it/s]\n 36%|███▋ | 73/200 [00:02<00:04, 27.33it/s]\n 38%|███▊ | 76/200 [00:02<00:04, 27.33it/s]\n 40%|███▉ | 79/200 [00:02<00:04, 27.32it/s]\n 41%|████ | 82/200 [00:03<00:04, 27.32it/s]\n 42%|████▎ | 85/200 [00:03<00:04, 27.35it/s]\n 44%|████▍ | 88/200 [00:03<00:04, 27.36it/s]\n 46%|████▌ | 91/200 [00:03<00:03, 27.39it/s]\n 47%|████▋ | 94/200 [00:03<00:03, 27.35it/s]\n 48%|████▊ | 97/200 [00:03<00:03, 27.31it/s]\n 50%|█████ | 100/200 [00:03<00:03, 27.30it/s]\n 52%|█████▏ | 103/200 [00:03<00:03, 27.31it/s]\n 53%|█████▎ | 106/200 [00:03<00:03, 27.29it/s]\n 55%|█████▍ | 109/200 [00:04<00:03, 27.31it/s]\n 56%|█████▌ | 112/200 [00:04<00:03, 27.31it/s]\n 57%|█████▊ | 115/200 [00:04<00:03, 27.28it/s]\n 59%|█████▉ | 118/200 [00:04<00:03, 27.24it/s]\n 60%|██████ | 121/200 [00:04<00:02, 27.25it/s]\n 62%|██████▏ | 124/200 [00:04<00:02, 27.27it/s]\n 64%|██████▎ | 127/200 [00:04<00:02, 27.26it/s]\n 65%|██████▌ | 130/200 [00:04<00:02, 27.25it/s]\n 66%|██████▋ | 133/200 [00:04<00:02, 27.24it/s]\n 68%|██████▊ | 136/200 [00:05<00:02, 27.23it/s]\n 70%|██████▉ | 139/200 [00:05<00:02, 27.24it/s]\n 71%|███████ | 142/200 [00:05<00:02, 27.19it/s]\n 72%|███████▎ | 145/200 [00:05<00:02, 27.20it/s]\n 74%|███████▍ | 148/200 [00:05<00:01, 27.21it/s]\n 76%|███████▌ | 151/200 [00:05<00:01, 27.21it/s]\n 77%|███████▋ | 154/200 [00:05<00:01, 27.19it/s]\n 78%|███████▊ | 157/200 [00:05<00:01, 27.23it/s]\n 80%|████████ | 160/200 [00:05<00:01, 27.19it/s]\n 82%|████████▏ | 163/200 [00:06<00:01, 27.18it/s]\n 83%|████████▎ | 166/200 [00:06<00:01, 27.20it/s]\n 84%|████████▍ | 169/200 [00:06<00:01, 27.18it/s]\n 86%|████████▌ | 172/200 [00:06<00:01, 27.19it/s]\n 88%|████████▊ | 175/200 [00:06<00:00, 27.21it/s]\n 89%|████████▉ | 178/200 [00:06<00:00, 27.20it/s]\n 90%|█████████ | 181/200 [00:06<00:00, 27.21it/s]\n 92%|█████████▏| 184/200 [00:06<00:00, 27.18it/s]\n 94%|█████████▎| 187/200 [00:06<00:00, 27.22it/s]\n 95%|█████████▌| 190/200 [00:07<00:00, 27.20it/s]\n 96%|█████████▋| 193/200 [00:07<00:00, 27.22it/s]\n 98%|█████████▊| 196/200 [00:07<00:00, 27.18it/s]\n100%|█████████▉| 199/200 [00:07<00:00, 27.15it/s]\n100%|██████████| 200/200 [00:07<00:00, 26.91it/s]\nPrediction complete", "metrics": { "predict_time": 10.49638, "total_time": 108.222347 }, "output": [ "https://replicate.delivery/pbxt/NpeZ7PdvNhQYLau2sdOqJQW9uOKYJLKZf7vOaSOgAaVdIb9RA/out-0.png" ], "started_at": "2023-11-30T03:22:59.601771Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mkfcar3bpqzekis53vkej2ih6a", "cancel": "https://api.replicate.com/v1/predictions/mkfcar3bpqzekis53vkej2ih6a/cancel" }, "version": "062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752" }
Generated inUsing seed: 22252 0%| | 0/200 [00:00<?, ?it/s] 0%| | 1/200 [00:00<00:27, 7.15it/s] 2%|▏ | 4/200 [00:00<00:10, 17.94it/s] 4%|▎ | 7/200 [00:00<00:08, 22.05it/s] 5%|▌ | 10/200 [00:00<00:07, 24.12it/s] 6%|▋ | 13/200 [00:00<00:07, 25.29it/s] 8%|▊ | 16/200 [00:00<00:07, 26.02it/s] 10%|▉ | 19/200 [00:00<00:06, 26.47it/s] 11%|█ | 22/200 [00:00<00:06, 26.77it/s] 12%|█▎ | 25/200 [00:01<00:06, 26.97it/s] 14%|█▍ | 28/200 [00:01<00:06, 27.07it/s] 16%|█▌ | 31/200 [00:01<00:06, 27.18it/s] 17%|█▋ | 34/200 [00:01<00:06, 27.22it/s] 18%|█▊ | 37/200 [00:01<00:05, 27.28it/s] 20%|██ | 40/200 [00:01<00:05, 27.28it/s] 22%|██▏ | 43/200 [00:01<00:05, 27.29it/s] 23%|██▎ | 46/200 [00:01<00:05, 27.30it/s] 24%|██▍ | 49/200 [00:01<00:05, 27.31it/s] 26%|██▌ | 52/200 [00:02<00:05, 27.32it/s] 28%|██▊ | 55/200 [00:02<00:05, 27.33it/s] 29%|██▉ | 58/200 [00:02<00:05, 27.28it/s] 30%|███ | 61/200 [00:02<00:05, 27.32it/s] 32%|███▏ | 64/200 [00:02<00:04, 27.34it/s] 34%|███▎ | 67/200 [00:02<00:04, 27.33it/s] 35%|███▌ | 70/200 [00:02<00:04, 27.31it/s] 36%|███▋ | 73/200 [00:02<00:04, 27.33it/s] 38%|███▊ | 76/200 [00:02<00:04, 27.33it/s] 40%|███▉ | 79/200 [00:02<00:04, 27.32it/s] 41%|████ | 82/200 [00:03<00:04, 27.32it/s] 42%|████▎ | 85/200 [00:03<00:04, 27.35it/s] 44%|████▍ | 88/200 [00:03<00:04, 27.36it/s] 46%|████▌ | 91/200 [00:03<00:03, 27.39it/s] 47%|████▋ | 94/200 [00:03<00:03, 27.35it/s] 48%|████▊ | 97/200 [00:03<00:03, 27.31it/s] 50%|█████ | 100/200 [00:03<00:03, 27.30it/s] 52%|█████▏ | 103/200 [00:03<00:03, 27.31it/s] 53%|█████▎ | 106/200 [00:03<00:03, 27.29it/s] 55%|█████▍ | 109/200 [00:04<00:03, 27.31it/s] 56%|█████▌ | 112/200 [00:04<00:03, 27.31it/s] 57%|█████▊ | 115/200 [00:04<00:03, 27.28it/s] 59%|█████▉ | 118/200 [00:04<00:03, 27.24it/s] 60%|██████ | 121/200 [00:04<00:02, 27.25it/s] 62%|██████▏ | 124/200 [00:04<00:02, 27.27it/s] 64%|██████▎ | 127/200 [00:04<00:02, 27.26it/s] 65%|██████▌ | 130/200 [00:04<00:02, 27.25it/s] 66%|██████▋ | 133/200 [00:04<00:02, 27.24it/s] 68%|██████▊ | 136/200 [00:05<00:02, 27.23it/s] 70%|██████▉ | 139/200 [00:05<00:02, 27.24it/s] 71%|███████ | 142/200 [00:05<00:02, 27.19it/s] 72%|███████▎ | 145/200 [00:05<00:02, 27.20it/s] 74%|███████▍ | 148/200 [00:05<00:01, 27.21it/s] 76%|███████▌ | 151/200 [00:05<00:01, 27.21it/s] 77%|███████▋ | 154/200 [00:05<00:01, 27.19it/s] 78%|███████▊ | 157/200 [00:05<00:01, 27.23it/s] 80%|████████ | 160/200 [00:05<00:01, 27.19it/s] 82%|████████▏ | 163/200 [00:06<00:01, 27.18it/s] 83%|████████▎ | 166/200 [00:06<00:01, 27.20it/s] 84%|████████▍ | 169/200 [00:06<00:01, 27.18it/s] 86%|████████▌ | 172/200 [00:06<00:01, 27.19it/s] 88%|████████▊ | 175/200 [00:06<00:00, 27.21it/s] 89%|████████▉ | 178/200 [00:06<00:00, 27.20it/s] 90%|█████████ | 181/200 [00:06<00:00, 27.21it/s] 92%|█████████▏| 184/200 [00:06<00:00, 27.18it/s] 94%|█████████▎| 187/200 [00:06<00:00, 27.22it/s] 95%|█████████▌| 190/200 [00:07<00:00, 27.20it/s] 96%|█████████▋| 193/200 [00:07<00:00, 27.22it/s] 98%|█████████▊| 196/200 [00:07<00:00, 27.18it/s] 100%|█████████▉| 199/200 [00:07<00:00, 27.15it/s] 100%|██████████| 200/200 [00:07<00:00, 26.91it/s] Prediction complete
Prediction
yuni-eng/inpainting:a666728e3a49a48ecfe7a8ed4ddcf95bc25b4f445043c5e44475584098eb3095ID4qsdidlbvwydf32dkujwvrf2tyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 0
- prompt
- realistic photo of golden gate bridge in t-shirt, HD, 4k
- num_outputs
- 1
- guidance_scale
- 20
- negative_prompt
- poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling
- num_inference_steps
- 200
{ "mask": "https://replicate.delivery/pbxt/JuyQqrPGHTx5CP1q6Eqy6ZrkECuO0FAJYSlwgZJIbfw8jBvw/Screenshot%202023-11-21%20at%202.20.08%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuyQqRXn4cpriS4GXHWGOwopkTKjbpGxkJbN8IYJanHOMPKA/white-t-shirt-man-2.png", "prompt": "realistic photo of golden gate bridge in t-shirt, HD, 4k", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run yuni-eng/inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "yuni-eng/inpainting:a666728e3a49a48ecfe7a8ed4ddcf95bc25b4f445043c5e44475584098eb3095", { input: { mask: "https://replicate.delivery/pbxt/JuyQqrPGHTx5CP1q6Eqy6ZrkECuO0FAJYSlwgZJIbfw8jBvw/Screenshot%202023-11-21%20at%202.20.08%20PM.png", seed: 0, image: "https://replicate.delivery/pbxt/JuyQqRXn4cpriS4GXHWGOwopkTKjbpGxkJbN8IYJanHOMPKA/white-t-shirt-man-2.png", prompt: "realistic photo of golden gate bridge in t-shirt, HD, 4k", num_outputs: 1, guidance_scale: 20, negative_prompt: "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", num_inference_steps: 200 } } ); // 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 replicate
Import the client:import replicate
Run yuni-eng/inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "yuni-eng/inpainting:a666728e3a49a48ecfe7a8ed4ddcf95bc25b4f445043c5e44475584098eb3095", input={ "mask": "https://replicate.delivery/pbxt/JuyQqrPGHTx5CP1q6Eqy6ZrkECuO0FAJYSlwgZJIbfw8jBvw/Screenshot%202023-11-21%20at%202.20.08%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuyQqRXn4cpriS4GXHWGOwopkTKjbpGxkJbN8IYJanHOMPKA/white-t-shirt-man-2.png", "prompt": "realistic photo of golden gate bridge in t-shirt, HD, 4k", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run yuni-eng/inpainting 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": "a666728e3a49a48ecfe7a8ed4ddcf95bc25b4f445043c5e44475584098eb3095", "input": { "mask": "https://replicate.delivery/pbxt/JuyQqrPGHTx5CP1q6Eqy6ZrkECuO0FAJYSlwgZJIbfw8jBvw/Screenshot%202023-11-21%20at%202.20.08%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuyQqRXn4cpriS4GXHWGOwopkTKjbpGxkJbN8IYJanHOMPKA/white-t-shirt-man-2.png", "prompt": "realistic photo of golden gate bridge in t-shirt, HD, 4k", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-21T22:24:53.169602Z", "created_at": "2023-11-21T22:24:43.593345Z", "data_removed": false, "error": null, "id": "4qsdidlbvwydf32dkujwvrf2ty", "input": { "mask": "https://replicate.delivery/pbxt/JuyQqrPGHTx5CP1q6Eqy6ZrkECuO0FAJYSlwgZJIbfw8jBvw/Screenshot%202023-11-21%20at%202.20.08%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuyQqRXn4cpriS4GXHWGOwopkTKjbpGxkJbN8IYJanHOMPKA/white-t-shirt-man-2.png", "prompt": "realistic photo of golden gate bridge in t-shirt, HD, 4k", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 }, "logs": "Using seed: 7590\n 0%| | 0/200 [00:00<?, ?it/s]\n 0%| | 1/200 [00:00<00:20, 9.73it/s]\n 2%|▏ | 4/200 [00:00<00:09, 20.42it/s]\n 4%|▎ | 7/200 [00:00<00:08, 23.68it/s]\n 5%|▌ | 10/200 [00:00<00:07, 25.21it/s]\n 6%|▋ | 13/200 [00:00<00:07, 25.97it/s]\n 8%|▊ | 16/200 [00:00<00:06, 26.42it/s]\n 10%|▉ | 19/200 [00:00<00:06, 26.73it/s]\n 11%|█ | 22/200 [00:00<00:06, 26.90it/s]\n 12%|█▎ | 25/200 [00:00<00:06, 27.02it/s]\n 14%|█▍ | 28/200 [00:01<00:06, 27.11it/s]\n 16%|█▌ | 31/200 [00:01<00:06, 27.15it/s]\n 17%|█▋ | 34/200 [00:01<00:06, 27.15it/s]\n 18%|█▊ | 37/200 [00:01<00:05, 27.19it/s]\n 20%|██ | 40/200 [00:01<00:05, 27.21it/s]\n 22%|██▏ | 43/200 [00:01<00:05, 27.22it/s]\n 23%|██▎ | 46/200 [00:01<00:05, 27.21it/s]\n 24%|██▍ | 49/200 [00:01<00:05, 27.24it/s]\n 26%|██▌ | 52/200 [00:01<00:05, 27.23it/s]\n 28%|██▊ | 55/200 [00:02<00:05, 27.25it/s]\n 29%|██▉ | 58/200 [00:02<00:05, 27.22it/s]\n 30%|███ | 61/200 [00:02<00:05, 27.24it/s]\n 32%|███▏ | 64/200 [00:02<00:04, 27.25it/s]\n 34%|███▎ | 67/200 [00:02<00:04, 27.21it/s]\n 35%|███▌ | 70/200 [00:02<00:04, 27.19it/s]\n 36%|███▋ | 73/200 [00:02<00:04, 27.19it/s]\n 38%|███▊ | 76/200 [00:02<00:04, 27.18it/s]\n 40%|███▉ | 79/200 [00:02<00:04, 27.19it/s]\n 41%|████ | 82/200 [00:03<00:04, 27.18it/s]\n 42%|████▎ | 85/200 [00:03<00:04, 27.19it/s]\n 44%|████▍ | 88/200 [00:03<00:04, 27.15it/s]\n 46%|████▌ | 91/200 [00:03<00:04, 27.13it/s]\n 47%|████▋ | 94/200 [00:03<00:03, 27.13it/s]\n 48%|████▊ | 97/200 [00:03<00:03, 27.10it/s]\n 50%|█████ | 100/200 [00:03<00:03, 27.11it/s]\n 52%|█████▏ | 103/200 [00:03<00:03, 27.16it/s]\n 53%|█████▎ | 106/200 [00:03<00:03, 27.12it/s]\n 55%|█████▍ | 109/200 [00:04<00:03, 27.10it/s]\n 56%|█████▌ | 112/200 [00:04<00:03, 27.11it/s]\n 57%|█████▊ | 115/200 [00:04<00:03, 27.11it/s]\n 59%|█████▉ | 118/200 [00:04<00:03, 27.13it/s]\n 60%|██████ | 121/200 [00:04<00:02, 27.14it/s]\n 62%|██████▏ | 124/200 [00:04<00:02, 27.12it/s]\n 64%|██████▎ | 127/200 [00:04<00:02, 27.11it/s]\n 65%|██████▌ | 130/200 [00:04<00:02, 27.14it/s]\n 66%|██████▋ | 133/200 [00:04<00:02, 27.12it/s]\n 68%|██████▊ | 136/200 [00:05<00:02, 27.14it/s]\n 70%|██████▉ | 139/200 [00:05<00:02, 27.10it/s]\n 71%|███████ | 142/200 [00:05<00:02, 27.10it/s]\n 72%|███████▎ | 145/200 [00:05<00:02, 27.09it/s]\n 74%|███████▍ | 148/200 [00:05<00:01, 27.10it/s]\n 76%|███████▌ | 151/200 [00:05<00:01, 27.10it/s]\n 77%|███████▋ | 154/200 [00:05<00:01, 27.09it/s]\n 78%|███████▊ | 157/200 [00:05<00:01, 27.11it/s]\n 80%|████████ | 160/200 [00:05<00:01, 27.09it/s]\n 82%|████████▏ | 163/200 [00:06<00:01, 27.10it/s]\n 83%|████████▎ | 166/200 [00:06<00:01, 27.08it/s]\n 84%|████████▍ | 169/200 [00:06<00:01, 27.09it/s]\n 86%|████████▌ | 172/200 [00:06<00:01, 27.08it/s]\n 88%|████████▊ | 175/200 [00:06<00:00, 27.08it/s]\n 89%|████████▉ | 178/200 [00:06<00:00, 27.10it/s]\n 90%|█████████ | 181/200 [00:06<00:00, 27.09it/s]\n 92%|█████████▏| 184/200 [00:06<00:00, 27.06it/s]\n 94%|█████████▎| 187/200 [00:06<00:00, 27.09it/s]\n 95%|█████████▌| 190/200 [00:07<00:00, 27.09it/s]\n 96%|█████████▋| 193/200 [00:07<00:00, 27.06it/s]\n 98%|█████████▊| 196/200 [00:07<00:00, 27.07it/s]\n100%|█████████▉| 199/200 [00:07<00:00, 27.03it/s]\n100%|██████████| 200/200 [00:07<00:00, 26.92it/s]\nPrediction complete", "metrics": { "predict_time": 9.540297, "total_time": 9.576257 }, "output": [ "https://replicate.delivery/pbxt/H0W1XBzLywLjGFOsMfqvjkWl6VEJOSsaVLuOFuDhqZAaAX9IA/out-0.png" ], "started_at": "2023-11-21T22:24:43.629305Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4qsdidlbvwydf32dkujwvrf2ty", "cancel": "https://api.replicate.com/v1/predictions/4qsdidlbvwydf32dkujwvrf2ty/cancel" }, "version": "a666728e3a49a48ecfe7a8ed4ddcf95bc25b4f445043c5e44475584098eb3095" }
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Prediction
yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752ID6s5oculbvlyayrpgbc7gkr2u34StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 0
- prompt
- realistic photo of golden shoes, no text in billboard
- num_outputs
- 1
- guidance_scale
- 20
- negative_prompt
- poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling
- num_inference_steps
- 200
{ "mask": "https://replicate.delivery/pbxt/JuydgV8lA1U9R1xKiTVxO5PMCXUoYpOP3VxdLbMHIcNkY1nY/mask.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuydgiKU8Dnu68VP1C5yNMwqM7i0eD55I8uQQJMfdR3hUgxN/billboard.png", "prompt": "realistic photo of golden shoes, no text in billboard", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run yuni-eng/inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", { input: { mask: "https://replicate.delivery/pbxt/JuydgV8lA1U9R1xKiTVxO5PMCXUoYpOP3VxdLbMHIcNkY1nY/mask.png", seed: 0, image: "https://replicate.delivery/pbxt/JuydgiKU8Dnu68VP1C5yNMwqM7i0eD55I8uQQJMfdR3hUgxN/billboard.png", prompt: "realistic photo of golden shoes, no text in billboard", num_outputs: 1, guidance_scale: 20, negative_prompt: "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", num_inference_steps: 200 } } ); // 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 replicate
Import the client:import replicate
Run yuni-eng/inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", input={ "mask": "https://replicate.delivery/pbxt/JuydgV8lA1U9R1xKiTVxO5PMCXUoYpOP3VxdLbMHIcNkY1nY/mask.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuydgiKU8Dnu68VP1C5yNMwqM7i0eD55I8uQQJMfdR3hUgxN/billboard.png", "prompt": "realistic photo of golden shoes, no text in billboard", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run yuni-eng/inpainting 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": "062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", "input": { "mask": "https://replicate.delivery/pbxt/JuydgV8lA1U9R1xKiTVxO5PMCXUoYpOP3VxdLbMHIcNkY1nY/mask.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuydgiKU8Dnu68VP1C5yNMwqM7i0eD55I8uQQJMfdR3hUgxN/billboard.png", "prompt": "realistic photo of golden shoes, no text in billboard", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-21T22:38:26.086118Z", "created_at": "2023-11-21T22:38:16.635887Z", "data_removed": false, "error": null, "id": "6s5oculbvlyayrpgbc7gkr2u34", "input": { "mask": "https://replicate.delivery/pbxt/JuydgV8lA1U9R1xKiTVxO5PMCXUoYpOP3VxdLbMHIcNkY1nY/mask.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuydgiKU8Dnu68VP1C5yNMwqM7i0eD55I8uQQJMfdR3hUgxN/billboard.png", "prompt": "realistic photo of golden shoes, no text in billboard", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 }, "logs": "Using seed: 15078\n 0%| | 0/200 [00:00<?, ?it/s]\n 0%| | 1/200 [00:00<00:20, 9.73it/s]\n 2%|▏ | 4/200 [00:00<00:09, 20.27it/s]\n 4%|▎ | 7/200 [00:00<00:08, 23.44it/s]\n 5%|▌ | 10/200 [00:00<00:07, 24.91it/s]\n 6%|▋ | 13/200 [00:00<00:07, 25.67it/s]\n 8%|▊ | 16/200 [00:00<00:07, 26.06it/s]\n 10%|▉ | 19/200 [00:00<00:06, 26.39it/s]\n 11%|█ | 22/200 [00:00<00:06, 26.64it/s]\n 12%|█▎ | 25/200 [00:00<00:06, 26.72it/s]\n 14%|█▍ | 28/200 [00:01<00:06, 26.84it/s]\n 16%|█▌ | 31/200 [00:01<00:06, 26.94it/s]\n 17%|█▋ | 34/200 [00:01<00:06, 26.97it/s]\n 18%|█▊ | 37/200 [00:01<00:06, 27.05it/s]\n 20%|██ | 40/200 [00:01<00:05, 27.06it/s]\n 22%|██▏ | 43/200 [00:01<00:05, 27.08it/s]\n 23%|██▎ | 46/200 [00:01<00:05, 27.09it/s]\n 24%|██▍ | 49/200 [00:01<00:05, 27.13it/s]\n 26%|██▌ | 52/200 [00:01<00:05, 27.12it/s]\n 28%|██▊ | 55/200 [00:02<00:05, 27.13it/s]\n 29%|██▉ | 58/200 [00:02<00:05, 27.10it/s]\n 30%|███ | 61/200 [00:02<00:05, 27.10it/s]\n 32%|███▏ | 64/200 [00:02<00:05, 27.10it/s]\n 34%|███▎ | 67/200 [00:02<00:04, 27.09it/s]\n 35%|███▌ | 70/200 [00:02<00:04, 27.10it/s]\n 36%|███▋ | 73/200 [00:02<00:04, 27.09it/s]\n 38%|███▊ | 76/200 [00:02<00:04, 27.11it/s]\n 40%|███▉ | 79/200 [00:02<00:04, 27.13it/s]\n 41%|████ | 82/200 [00:03<00:04, 27.18it/s]\n 42%|████▎ | 85/200 [00:03<00:04, 27.21it/s]\n 44%|████▍ | 88/200 [00:03<00:04, 27.28it/s]\n 46%|████▌ | 91/200 [00:03<00:03, 27.28it/s]\n 47%|████▋ | 94/200 [00:03<00:03, 27.29it/s]\n 48%|████▊ | 97/200 [00:03<00:03, 27.28it/s]\n 50%|█████ | 100/200 [00:03<00:03, 27.29it/s]\n 52%|█████▏ | 103/200 [00:03<00:03, 27.25it/s]\n 53%|█████▎ | 106/200 [00:03<00:03, 27.29it/s]\n 55%|█████▍ | 109/200 [00:04<00:03, 27.27it/s]\n 56%|█████▌ | 112/200 [00:04<00:03, 27.26it/s]\n 57%|█████▊ | 115/200 [00:04<00:03, 27.24it/s]\n 59%|█████▉ | 118/200 [00:04<00:03, 27.25it/s]\n 60%|██████ | 121/200 [00:04<00:02, 27.26it/s]\n 62%|██████▏ | 124/200 [00:04<00:02, 27.29it/s]\n 64%|██████▎ | 127/200 [00:04<00:02, 27.27it/s]\n 65%|██████▌ | 130/200 [00:04<00:02, 27.27it/s]\n 66%|██████▋ | 133/200 [00:04<00:02, 27.28it/s]\n 68%|██████▊ | 136/200 [00:05<00:02, 27.30it/s]\n 70%|██████▉ | 139/200 [00:05<00:02, 27.27it/s]\n 71%|███████ | 142/200 [00:05<00:02, 27.30it/s]\n 72%|███████▎ | 145/200 [00:05<00:02, 27.25it/s]\n 74%|███████▍ | 148/200 [00:05<00:01, 27.24it/s]\n 76%|███████▌ | 151/200 [00:05<00:01, 27.24it/s]\n 77%|███████▋ | 154/200 [00:05<00:01, 27.28it/s]\n 78%|███████▊ | 157/200 [00:05<00:01, 27.26it/s]\n 80%|████████ | 160/200 [00:05<00:01, 27.27it/s]\n 82%|████████▏ | 163/200 [00:06<00:01, 27.27it/s]\n 83%|████████▎ | 166/200 [00:06<00:01, 27.27it/s]\n 84%|████████▍ | 169/200 [00:06<00:01, 27.27it/s]\n 86%|████████▌ | 172/200 [00:06<00:01, 27.29it/s]\n 88%|████████▊ | 175/200 [00:06<00:00, 27.28it/s]\n 89%|████████▉ | 178/200 [00:06<00:00, 27.30it/s]\n 90%|█████████ | 181/200 [00:06<00:00, 27.29it/s]\n 92%|█████████▏| 184/200 [00:06<00:00, 27.29it/s]\n 94%|█████████▎| 187/200 [00:06<00:00, 27.27it/s]\n 95%|█████████▌| 190/200 [00:07<00:00, 27.28it/s]\n 96%|█████████▋| 193/200 [00:07<00:00, 27.26it/s]\n 98%|█████████▊| 196/200 [00:07<00:00, 27.29it/s]\n100%|█████████▉| 199/200 [00:07<00:00, 27.24it/s]\n100%|██████████| 200/200 [00:07<00:00, 26.96it/s]\nPrediction complete", "metrics": { "predict_time": 9.383412, "total_time": 9.450231 }, "output": [ "https://replicate.delivery/pbxt/vDyJdsMz3orfUaCUvxFQPwPHrchopZmNtV7Srish0O3wGX9IA/out-0.png" ], "started_at": "2023-11-21T22:38:16.702706Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/6s5oculbvlyayrpgbc7gkr2u34", "cancel": "https://api.replicate.com/v1/predictions/6s5oculbvlyayrpgbc7gkr2u34/cancel" }, "version": "062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752" }
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Prediction
yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752IDfqgexplbjxosdqgpg6fvfpimzeStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 0
- prompt
- US flag in mug
- num_outputs
- 1
- guidance_scale
- 20
- negative_prompt
- poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling
- num_inference_steps
- 200
{ "mask": "https://replicate.delivery/pbxt/JuyqK87y9CQcekfV81qGifvJsBZ0RQbbi6dv7Fv2YXYxn794/Screenshot%202023-11-21%20at%202.43.30%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuyqJpkVv53J5qvMtIZazBhQXutLTJ33gHi0j8kvVrQa3KXy/white-mug.png", "prompt": "US flag in mug", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run yuni-eng/inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", { input: { mask: "https://replicate.delivery/pbxt/JuyqK87y9CQcekfV81qGifvJsBZ0RQbbi6dv7Fv2YXYxn794/Screenshot%202023-11-21%20at%202.43.30%20PM.png", seed: 0, image: "https://replicate.delivery/pbxt/JuyqJpkVv53J5qvMtIZazBhQXutLTJ33gHi0j8kvVrQa3KXy/white-mug.png", prompt: "US flag in mug", num_outputs: 1, guidance_scale: 20, negative_prompt: "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", num_inference_steps: 200 } } ); // 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 replicate
Import the client:import replicate
Run yuni-eng/inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", input={ "mask": "https://replicate.delivery/pbxt/JuyqK87y9CQcekfV81qGifvJsBZ0RQbbi6dv7Fv2YXYxn794/Screenshot%202023-11-21%20at%202.43.30%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuyqJpkVv53J5qvMtIZazBhQXutLTJ33gHi0j8kvVrQa3KXy/white-mug.png", "prompt": "US flag in mug", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run yuni-eng/inpainting 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": "062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", "input": { "mask": "https://replicate.delivery/pbxt/JuyqK87y9CQcekfV81qGifvJsBZ0RQbbi6dv7Fv2YXYxn794/Screenshot%202023-11-21%20at%202.43.30%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuyqJpkVv53J5qvMtIZazBhQXutLTJ33gHi0j8kvVrQa3KXy/white-mug.png", "prompt": "US flag in mug", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-21T22:51:46.025029Z", "created_at": "2023-11-21T22:51:35.766590Z", "data_removed": false, "error": null, "id": "fqgexplbjxosdqgpg6fvfpimze", "input": { "mask": "https://replicate.delivery/pbxt/JuyqK87y9CQcekfV81qGifvJsBZ0RQbbi6dv7Fv2YXYxn794/Screenshot%202023-11-21%20at%202.43.30%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuyqJpkVv53J5qvMtIZazBhQXutLTJ33gHi0j8kvVrQa3KXy/white-mug.png", "prompt": "US flag in mug", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 }, "logs": "Using seed: 20668\n 0%| | 0/200 [00:00<?, ?it/s]\n 0%| | 1/200 [00:00<00:20, 9.71it/s]\n 2%|▏ | 4/200 [00:00<00:09, 20.35it/s]\n 4%|▎ | 7/200 [00:00<00:08, 23.53it/s]\n 5%|▌ | 10/200 [00:00<00:07, 24.99it/s]\n 6%|▋ | 13/200 [00:00<00:07, 25.87it/s]\n 8%|▊ | 16/200 [00:00<00:06, 26.38it/s]\n 10%|▉ | 19/200 [00:00<00:06, 26.74it/s]\n 11%|█ | 22/200 [00:00<00:06, 26.95it/s]\n 12%|█▎ | 25/200 [00:00<00:06, 27.07it/s]\n 14%|█▍ | 28/200 [00:01<00:06, 27.14it/s]\n 16%|█▌ | 31/200 [00:01<00:06, 27.19it/s]\n 17%|█▋ | 34/200 [00:01<00:06, 27.24it/s]\n 18%|█▊ | 37/200 [00:01<00:05, 27.23it/s]\n 20%|██ | 40/200 [00:01<00:05, 27.27it/s]\n 22%|██▏ | 43/200 [00:01<00:05, 27.30it/s]\n 23%|██▎ | 46/200 [00:01<00:05, 27.32it/s]\n 24%|██▍ | 49/200 [00:01<00:05, 27.32it/s]\n 26%|██▌ | 52/200 [00:01<00:05, 27.30it/s]\n 28%|██▊ | 55/200 [00:02<00:05, 27.34it/s]\n 29%|██▉ | 58/200 [00:02<00:05, 27.33it/s]\n 30%|███ | 61/200 [00:02<00:05, 27.32it/s]\n 32%|███▏ | 64/200 [00:02<00:04, 27.31it/s]\n 34%|███▎ | 67/200 [00:02<00:04, 27.30it/s]\n 35%|███▌ | 70/200 [00:02<00:04, 27.31it/s]\n 36%|███▋ | 73/200 [00:02<00:04, 27.29it/s]\n 38%|███▊ | 76/200 [00:02<00:04, 27.28it/s]\n 40%|███▉ | 79/200 [00:02<00:04, 27.28it/s]\n 41%|████ | 82/200 [00:03<00:04, 27.29it/s]\n 42%|████▎ | 85/200 [00:03<00:04, 27.27it/s]\n 44%|████▍ | 88/200 [00:03<00:04, 27.26it/s]\n 46%|████▌ | 91/200 [00:03<00:03, 27.26it/s]\n 47%|████▋ | 94/200 [00:03<00:03, 27.24it/s]\n 48%|████▊ | 97/200 [00:03<00:03, 27.22it/s]\n 50%|█████ | 100/200 [00:03<00:03, 27.13it/s]\n 52%|█████▏ | 103/200 [00:03<00:03, 27.15it/s]\n 53%|█████▎ | 106/200 [00:03<00:03, 27.19it/s]\n 55%|█████▍ | 109/200 [00:04<00:03, 27.22it/s]\n 56%|█████▌ | 112/200 [00:04<00:03, 27.24it/s]\n 57%|█████▊ | 115/200 [00:04<00:03, 27.24it/s]\n 59%|█████▉ | 118/200 [00:04<00:03, 27.26it/s]\n 60%|██████ | 121/200 [00:04<00:02, 27.25it/s]\n 62%|██████▏ | 124/200 [00:04<00:02, 27.25it/s]\n 64%|██████▎ | 127/200 [00:04<00:02, 27.22it/s]\n 65%|██████▌ | 130/200 [00:04<00:02, 27.22it/s]\n 66%|██████▋ | 133/200 [00:04<00:02, 27.21it/s]\n 68%|██████▊ | 136/200 [00:05<00:02, 27.20it/s]\n 70%|██████▉ | 139/200 [00:05<00:02, 27.22it/s]\n 71%|███████ | 142/200 [00:05<00:02, 27.22it/s]\n 72%|███████▎ | 145/200 [00:05<00:02, 27.20it/s]\n 74%|███████▍ | 148/200 [00:05<00:01, 27.17it/s]\n 76%|███████▌ | 151/200 [00:05<00:01, 27.16it/s]\n 77%|███████▋ | 154/200 [00:05<00:01, 27.18it/s]\n 78%|███████▊ | 157/200 [00:05<00:01, 27.17it/s]\n 80%|████████ | 160/200 [00:05<00:01, 27.20it/s]\n 82%|████████▏ | 163/200 [00:06<00:01, 27.18it/s]\n 83%|████████▎ | 166/200 [00:06<00:01, 27.18it/s]\n 84%|████████▍ | 169/200 [00:06<00:01, 27.18it/s]\n 86%|████████▌ | 172/200 [00:06<00:01, 27.19it/s]\n 88%|████████▊ | 175/200 [00:06<00:00, 27.16it/s]\n 89%|████████▉ | 178/200 [00:06<00:00, 27.13it/s]\n 90%|█████████ | 181/200 [00:06<00:00, 27.15it/s]\n 92%|█████████▏| 184/200 [00:06<00:00, 27.18it/s]\n 94%|█████████▎| 187/200 [00:06<00:00, 27.19it/s]\n 95%|█████████▌| 190/200 [00:07<00:00, 27.20it/s]\n 96%|█████████▋| 193/200 [00:07<00:00, 27.20it/s]\n 98%|█████████▊| 196/200 [00:07<00:00, 27.19it/s]\n100%|█████████▉| 199/200 [00:07<00:00, 27.17it/s]\n100%|██████████| 200/200 [00:07<00:00, 27.00it/s]\nPrediction complete", "metrics": { "predict_time": 10.218301, "total_time": 10.258439 }, "output": [ "https://replicate.delivery/pbxt/jLzB59eW3nQkFC5W5ND2WJiFg27nvbdKSr3KfgOE7vLBau6RA/out-0.png" ], "started_at": "2023-11-21T22:51:35.806728Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/fqgexplbjxosdqgpg6fvfpimze", "cancel": "https://api.replicate.com/v1/predictions/fqgexplbjxosdqgpg6fvfpimze/cancel" }, "version": "062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752" }
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Prediction
yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752IDpbl5bxlb6svhssnqkqwyxsauwmStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 0
- prompt
- illustration of takashi murakami colored tiger in bag
- num_outputs
- 1
- guidance_scale
- 20
- negative_prompt
- poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling
- num_inference_steps
- 200
{ "mask": "https://replicate.delivery/pbxt/JuynKj9IO2816Mi6Ik3ynj37p9pj3eQypTf0rUjZIhsjL09t/Screenshot%202023-11-21%20at%202.40.57%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuynKtxWiFnpNEFIcz1UoWHb6WIJUuilToxGyn9ARsks5RR1/totebag.png", "prompt": "illustration of takashi murakami colored tiger in bag", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run yuni-eng/inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", { input: { mask: "https://replicate.delivery/pbxt/JuynKj9IO2816Mi6Ik3ynj37p9pj3eQypTf0rUjZIhsjL09t/Screenshot%202023-11-21%20at%202.40.57%20PM.png", seed: 0, image: "https://replicate.delivery/pbxt/JuynKtxWiFnpNEFIcz1UoWHb6WIJUuilToxGyn9ARsks5RR1/totebag.png", prompt: "illustration of takashi murakami colored tiger in bag", num_outputs: 1, guidance_scale: 20, negative_prompt: "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", num_inference_steps: 200 } } ); // 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 replicate
Import the client:import replicate
Run yuni-eng/inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "yuni-eng/inpainting:062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", input={ "mask": "https://replicate.delivery/pbxt/JuynKj9IO2816Mi6Ik3ynj37p9pj3eQypTf0rUjZIhsjL09t/Screenshot%202023-11-21%20at%202.40.57%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuynKtxWiFnpNEFIcz1UoWHb6WIJUuilToxGyn9ARsks5RR1/totebag.png", "prompt": "illustration of takashi murakami colored tiger in bag", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run yuni-eng/inpainting 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": "062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752", "input": { "mask": "https://replicate.delivery/pbxt/JuynKj9IO2816Mi6Ik3ynj37p9pj3eQypTf0rUjZIhsjL09t/Screenshot%202023-11-21%20at%202.40.57%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuynKtxWiFnpNEFIcz1UoWHb6WIJUuilToxGyn9ARsks5RR1/totebag.png", "prompt": "illustration of takashi murakami colored tiger in bag", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-21T23:41:03.877909Z", "created_at": "2023-11-21T23:40:54.050533Z", "data_removed": false, "error": null, "id": "pbl5bxlb6svhssnqkqwyxsauwm", "input": { "mask": "https://replicate.delivery/pbxt/JuynKj9IO2816Mi6Ik3ynj37p9pj3eQypTf0rUjZIhsjL09t/Screenshot%202023-11-21%20at%202.40.57%20PM.png", "seed": 0, "image": "https://replicate.delivery/pbxt/JuynKtxWiFnpNEFIcz1UoWHb6WIJUuilToxGyn9ARsks5RR1/totebag.png", "prompt": "illustration of takashi murakami colored tiger in bag", "num_outputs": 1, "guidance_scale": 20, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, poorly drawn eyes, extra limbs, disfigured, deformed, bad anatomy, distorted text, incorrect text spelling", "num_inference_steps": 200 }, "logs": "Using seed: 3991\n 0%| | 0/200 [00:00<?, ?it/s]\n 0%| | 1/200 [00:00<00:20, 9.73it/s]\n 2%|▏ | 4/200 [00:00<00:09, 20.45it/s]\n 4%|▎ | 7/200 [00:00<00:08, 23.73it/s]\n 5%|▌ | 10/200 [00:00<00:07, 25.25it/s]\n 6%|▋ | 13/200 [00:00<00:07, 26.05it/s]\n 8%|▊ | 16/200 [00:00<00:06, 26.54it/s]\n 10%|▉ | 19/200 [00:00<00:06, 26.80it/s]\n 11%|█ | 22/200 [00:00<00:06, 26.96it/s]\n 12%|█▎ | 25/200 [00:00<00:06, 27.10it/s]\n 14%|█▍ | 28/200 [00:01<00:06, 27.18it/s]\n 16%|█▌ | 31/200 [00:01<00:06, 27.21it/s]\n 17%|█▋ | 34/200 [00:01<00:06, 27.26it/s]\n 18%|█▊ | 37/200 [00:01<00:05, 27.28it/s]\n 20%|██ | 40/200 [00:01<00:05, 27.32it/s]\n 22%|██▏ | 43/200 [00:01<00:05, 27.33it/s]\n 23%|██▎ | 46/200 [00:01<00:05, 27.32it/s]\n 24%|██▍ | 49/200 [00:01<00:05, 27.30it/s]\n 26%|██▌ | 52/200 [00:01<00:05, 27.30it/s]\n 28%|██▊ | 55/200 [00:02<00:05, 27.27it/s]\n 29%|██▉ | 58/200 [00:02<00:05, 27.27it/s]\n 30%|███ | 61/200 [00:02<00:05, 27.27it/s]\n 32%|███▏ | 64/200 [00:02<00:04, 27.28it/s]\n 34%|███▎ | 67/200 [00:02<00:04, 27.28it/s]\n 35%|███▌ | 70/200 [00:02<00:04, 27.31it/s]\n 36%|███▋ | 73/200 [00:02<00:04, 27.31it/s]\n 38%|███▊ | 76/200 [00:02<00:04, 27.34it/s]\n 40%|███▉ | 79/200 [00:02<00:04, 27.35it/s]\n 41%|████ | 82/200 [00:03<00:04, 27.33it/s]\n 42%|████▎ | 85/200 [00:03<00:04, 27.37it/s]\n 44%|████▍ | 88/200 [00:03<00:04, 27.33it/s]\n 46%|████▌ | 91/200 [00:03<00:03, 27.34it/s]\n 47%|████▋ | 94/200 [00:03<00:03, 27.27it/s]\n 48%|████▊ | 97/200 [00:03<00:03, 27.27it/s]\n 50%|█████ | 100/200 [00:03<00:03, 27.30it/s]\n 52%|█████▏ | 103/200 [00:03<00:03, 27.32it/s]\n 53%|█████▎ | 106/200 [00:03<00:03, 27.32it/s]\n 55%|█████▍ | 109/200 [00:04<00:03, 27.33it/s]\n 56%|█████▌ | 112/200 [00:04<00:03, 27.34it/s]\n 57%|█████▊ | 115/200 [00:04<00:03, 27.34it/s]\n 59%|█████▉ | 118/200 [00:04<00:03, 27.30it/s]\n 60%|██████ | 121/200 [00:04<00:02, 27.25it/s]\n 62%|██████▏ | 124/200 [00:04<00:02, 27.27it/s]\n 64%|██████▎ | 127/200 [00:04<00:02, 27.28it/s]\n 65%|██████▌ | 130/200 [00:04<00:02, 27.24it/s]\n 66%|██████▋ | 133/200 [00:04<00:02, 27.26it/s]\n 68%|██████▊ | 136/200 [00:05<00:02, 27.23it/s]\n 70%|██████▉ | 139/200 [00:05<00:02, 27.19it/s]\n 71%|███████ | 142/200 [00:05<00:02, 27.16it/s]\n 72%|███████▎ | 145/200 [00:05<00:02, 27.18it/s]\n 74%|███████▍ | 148/200 [00:05<00:01, 27.18it/s]\n 76%|███████▌ | 151/200 [00:05<00:01, 27.21it/s]\n 77%|███████▋ | 154/200 [00:05<00:01, 27.19it/s]\n 78%|███████▊ | 157/200 [00:05<00:01, 27.19it/s]\n 80%|████████ | 160/200 [00:05<00:01, 27.22it/s]\n 82%|████████▏ | 163/200 [00:06<00:01, 27.22it/s]\n 83%|████████▎ | 166/200 [00:06<00:01, 27.22it/s]\n 84%|████████▍ | 169/200 [00:06<00:01, 27.17it/s]\n 86%|████████▌ | 172/200 [00:06<00:01, 27.17it/s]\n 88%|████████▊ | 175/200 [00:06<00:00, 27.18it/s]\n 89%|████████▉ | 178/200 [00:06<00:00, 27.22it/s]\n 90%|█████████ | 181/200 [00:06<00:00, 27.23it/s]\n 92%|█████████▏| 184/200 [00:06<00:00, 27.23it/s]\n 94%|█████████▎| 187/200 [00:06<00:00, 27.24it/s]\n 95%|█████████▌| 190/200 [00:07<00:00, 27.25it/s]\n 96%|█████████▋| 193/200 [00:07<00:00, 27.25it/s]\n 98%|█████████▊| 196/200 [00:07<00:00, 27.24it/s]\n100%|█████████▉| 199/200 [00:07<00:00, 27.27it/s]\n100%|██████████| 200/200 [00:07<00:00, 27.05it/s]\nPrediction complete", "metrics": { "predict_time": 9.796392, "total_time": 9.827376 }, "output": [ "https://replicate.delivery/pbxt/7weLwx38AYXeoUH1dsYtLifrHrTVLkWB1vTPK2VEYdkdQeqHB/out-0.png" ], "started_at": "2023-11-21T23:40:54.081517Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/pbl5bxlb6svhssnqkqwyxsauwm", "cancel": "https://api.replicate.com/v1/predictions/pbl5bxlb6svhssnqkqwyxsauwm/cancel" }, "version": "062d8ed6016c7bf957101afbe2d279b5698a6b822def8d592a36a5efdf372752" }
Generated inUsing seed: 3991 0%| | 0/200 [00:00<?, ?it/s] 0%| | 1/200 [00:00<00:20, 9.73it/s] 2%|▏ | 4/200 [00:00<00:09, 20.45it/s] 4%|▎ | 7/200 [00:00<00:08, 23.73it/s] 5%|▌ | 10/200 [00:00<00:07, 25.25it/s] 6%|▋ | 13/200 [00:00<00:07, 26.05it/s] 8%|▊ | 16/200 [00:00<00:06, 26.54it/s] 10%|▉ | 19/200 [00:00<00:06, 26.80it/s] 11%|█ | 22/200 [00:00<00:06, 26.96it/s] 12%|█▎ | 25/200 [00:00<00:06, 27.10it/s] 14%|█▍ | 28/200 [00:01<00:06, 27.18it/s] 16%|█▌ | 31/200 [00:01<00:06, 27.21it/s] 17%|█▋ | 34/200 [00:01<00:06, 27.26it/s] 18%|█▊ | 37/200 [00:01<00:05, 27.28it/s] 20%|██ | 40/200 [00:01<00:05, 27.32it/s] 22%|██▏ | 43/200 [00:01<00:05, 27.33it/s] 23%|██▎ | 46/200 [00:01<00:05, 27.32it/s] 24%|██▍ | 49/200 [00:01<00:05, 27.30it/s] 26%|██▌ | 52/200 [00:01<00:05, 27.30it/s] 28%|██▊ | 55/200 [00:02<00:05, 27.27it/s] 29%|██▉ | 58/200 [00:02<00:05, 27.27it/s] 30%|███ | 61/200 [00:02<00:05, 27.27it/s] 32%|███▏ | 64/200 [00:02<00:04, 27.28it/s] 34%|███▎ | 67/200 [00:02<00:04, 27.28it/s] 35%|███▌ | 70/200 [00:02<00:04, 27.31it/s] 36%|███▋ | 73/200 [00:02<00:04, 27.31it/s] 38%|███▊ | 76/200 [00:02<00:04, 27.34it/s] 40%|███▉ | 79/200 [00:02<00:04, 27.35it/s] 41%|████ | 82/200 [00:03<00:04, 27.33it/s] 42%|████▎ | 85/200 [00:03<00:04, 27.37it/s] 44%|████▍ | 88/200 [00:03<00:04, 27.33it/s] 46%|████▌ | 91/200 [00:03<00:03, 27.34it/s] 47%|████▋ | 94/200 [00:03<00:03, 27.27it/s] 48%|████▊ | 97/200 [00:03<00:03, 27.27it/s] 50%|█████ | 100/200 [00:03<00:03, 27.30it/s] 52%|█████▏ | 103/200 [00:03<00:03, 27.32it/s] 53%|█████▎ | 106/200 [00:03<00:03, 27.32it/s] 55%|█████▍ | 109/200 [00:04<00:03, 27.33it/s] 56%|█████▌ | 112/200 [00:04<00:03, 27.34it/s] 57%|█████▊ | 115/200 [00:04<00:03, 27.34it/s] 59%|█████▉ | 118/200 [00:04<00:03, 27.30it/s] 60%|██████ | 121/200 [00:04<00:02, 27.25it/s] 62%|██████▏ | 124/200 [00:04<00:02, 27.27it/s] 64%|██████▎ | 127/200 [00:04<00:02, 27.28it/s] 65%|██████▌ | 130/200 [00:04<00:02, 27.24it/s] 66%|██████▋ | 133/200 [00:04<00:02, 27.26it/s] 68%|██████▊ | 136/200 [00:05<00:02, 27.23it/s] 70%|██████▉ | 139/200 [00:05<00:02, 27.19it/s] 71%|███████ | 142/200 [00:05<00:02, 27.16it/s] 72%|███████▎ | 145/200 [00:05<00:02, 27.18it/s] 74%|███████▍ | 148/200 [00:05<00:01, 27.18it/s] 76%|███████▌ | 151/200 [00:05<00:01, 27.21it/s] 77%|███████▋ | 154/200 [00:05<00:01, 27.19it/s] 78%|███████▊ | 157/200 [00:05<00:01, 27.19it/s] 80%|████████ | 160/200 [00:05<00:01, 27.22it/s] 82%|████████▏ | 163/200 [00:06<00:01, 27.22it/s] 83%|████████▎ | 166/200 [00:06<00:01, 27.22it/s] 84%|████████▍ | 169/200 [00:06<00:01, 27.17it/s] 86%|████████▌ | 172/200 [00:06<00:01, 27.17it/s] 88%|████████▊ | 175/200 [00:06<00:00, 27.18it/s] 89%|████████▉ | 178/200 [00:06<00:00, 27.22it/s] 90%|█████████ | 181/200 [00:06<00:00, 27.23it/s] 92%|█████████▏| 184/200 [00:06<00:00, 27.23it/s] 94%|█████████▎| 187/200 [00:06<00:00, 27.24it/s] 95%|█████████▌| 190/200 [00:07<00:00, 27.25it/s] 96%|█████████▋| 193/200 [00:07<00:00, 27.25it/s] 98%|█████████▊| 196/200 [00:07<00:00, 27.24it/s] 100%|█████████▉| 199/200 [00:07<00:00, 27.27it/s] 100%|██████████| 200/200 [00:07<00:00, 27.05it/s] Prediction complete
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