cjwbw / diffedit-stable-diffusion
Diffusion-based semantic image editing with mask guidance
Prediction
cjwbw/diffedit-stable-diffusion:8c51da11578f75df306db64e27fd337b8b18de902f49b4404b0b340dced96f48IDvra43nyuunhdxeb7jhipbjux6mStatusSucceededSourceWebHardwareT4Total durationCreatedInput
- source_prompt
- a bowl of fruits
- target_prompt
- a basket of fruits
- guidance_scale
- 7.5
- num_inference_steps
- 50
{ "image": "https://replicate.delivery/pbxt/IyIBdgYw3DehQHUxK1t0dkX5vmS7QYqzgHmeEYGaxSv4uDUE/origin.png", "source_prompt": "a bowl of fruits", "target_prompt": "a basket of fruits", "guidance_scale": 7.5, "num_inference_steps": 50 }
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 cjwbw/diffedit-stable-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/diffedit-stable-diffusion:8c51da11578f75df306db64e27fd337b8b18de902f49b4404b0b340dced96f48", { input: { image: "https://replicate.delivery/pbxt/IyIBdgYw3DehQHUxK1t0dkX5vmS7QYqzgHmeEYGaxSv4uDUE/origin.png", source_prompt: "a bowl of fruits", target_prompt: "a basket of fruits", guidance_scale: 7.5, num_inference_steps: 50 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);
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 cjwbw/diffedit-stable-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/diffedit-stable-diffusion:8c51da11578f75df306db64e27fd337b8b18de902f49b4404b0b340dced96f48", input={ "image": "https://replicate.delivery/pbxt/IyIBdgYw3DehQHUxK1t0dkX5vmS7QYqzgHmeEYGaxSv4uDUE/origin.png", "source_prompt": "a bowl of fruits", "target_prompt": "a basket of fruits", "guidance_scale": 7.5, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run cjwbw/diffedit-stable-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": "cjwbw/diffedit-stable-diffusion:8c51da11578f75df306db64e27fd337b8b18de902f49b4404b0b340dced96f48", "input": { "image": "https://replicate.delivery/pbxt/IyIBdgYw3DehQHUxK1t0dkX5vmS7QYqzgHmeEYGaxSv4uDUE/origin.png", "source_prompt": "a bowl of fruits", "target_prompt": "a basket of fruits", "guidance_scale": 7.5, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-06-09T14:47:52.403818Z", "created_at": "2023-06-09T14:43:56.305702Z", "data_removed": false, "error": null, "id": "vra43nyuunhdxeb7jhipbjux6m", "input": { "image": "https://replicate.delivery/pbxt/IyIBdgYw3DehQHUxK1t0dkX5vmS7QYqzgHmeEYGaxSv4uDUE/origin.png", "source_prompt": "a bowl of fruits", "target_prompt": "a basket of fruits", "guidance_scale": 7.5, "num_inference_steps": 50 }, "logs": "Using seed: 43695\n/root/.pyenv/versions/3.10.12/lib/python3.10/site-packages/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_diffedit.py:162: FutureWarning: The preprocess method is deprecated and will be removed in a future version. Please use VaeImageProcessor.preprocess instead\nwarnings.warn(\n 0%| | 0/39 [00:00<?, ?it/s]\n 3%|▎ | 1/39 [00:01<00:49, 1.31s/it]\n 5%|▌ | 2/39 [00:01<00:27, 1.33it/s]\n 8%|▊ | 3/39 [00:01<00:20, 1.80it/s]\n 10%|█ | 4/39 [00:02<00:16, 2.15it/s]\n 13%|█▎ | 5/39 [00:02<00:14, 2.42it/s]\n 15%|█▌ | 6/39 [00:02<00:12, 2.62it/s]\n 18%|█▊ | 7/39 [00:03<00:11, 2.77it/s]\n 21%|██ | 8/39 [00:03<00:10, 2.87it/s]\n 23%|██▎ | 9/39 [00:03<00:10, 2.94it/s]\n 26%|██▌ | 10/39 [00:04<00:09, 2.98it/s]\n 28%|██▊ | 11/39 [00:04<00:09, 3.04it/s]\n 31%|███ | 12/39 [00:04<00:08, 3.06it/s]\n 33%|███▎ | 13/39 [00:05<00:08, 3.07it/s]\n 36%|███▌ | 14/39 [00:05<00:08, 3.09it/s]\n 38%|███▊ | 15/39 [00:05<00:07, 3.09it/s]\n 41%|████ | 16/39 [00:06<00:07, 3.05it/s]\n 44%|████▎ | 17/39 [00:06<00:07, 3.07it/s]\n 46%|████▌ | 18/39 [00:06<00:06, 3.07it/s]\n 49%|████▊ | 19/39 [00:07<00:06, 3.08it/s]\n 51%|█████▏ | 20/39 [00:07<00:06, 3.07it/s]\n 54%|█████▍ | 21/39 [00:07<00:05, 3.08it/s]\n 56%|█████▋ | 22/39 [00:08<00:05, 3.08it/s]\n 59%|█████▉ | 23/39 [00:08<00:05, 3.09it/s]\n 62%|██████▏ | 24/39 [00:08<00:04, 3.08it/s]\n 64%|██████▍ | 25/39 [00:09<00:04, 3.09it/s]\n 67%|██████▋ | 26/39 [00:09<00:04, 3.09it/s]\n 69%|██████▉ | 27/39 [00:09<00:03, 3.09it/s]\n 72%|███████▏ | 28/39 [00:10<00:03, 3.09it/s]\n 74%|███████▍ | 29/39 [00:10<00:03, 3.09it/s]\n 77%|███████▋ | 30/39 [00:10<00:02, 3.08it/s]\n 79%|███████▉ | 31/39 [00:11<00:02, 3.10it/s]\n 82%|████████▏ | 32/39 [00:11<00:02, 3.11it/s]\n 85%|████████▍ | 33/39 [00:11<00:01, 3.10it/s]\n 87%|████████▋ | 34/39 [00:12<00:01, 3.10it/s]\n 90%|████████▉ | 35/39 [00:12<00:01, 3.09it/s]\n 92%|█████████▏| 36/39 [00:12<00:00, 3.09it/s]\n 95%|█████████▍| 37/39 [00:12<00:00, 3.10it/s]\n 97%|█████████▋| 38/39 [00:13<00:00, 3.09it/s]\n100%|██████████| 39/39 [00:13<00:00, 3.08it/s]\n100%|██████████| 39/39 [00:13<00:00, 2.86it/s]\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:23, 1.69it/s]\n 5%|▌ | 2/40 [00:00<00:16, 2.30it/s]\n 8%|▊ | 3/40 [00:01<00:14, 2.58it/s]\n 10%|█ | 4/40 [00:01<00:13, 2.75it/s]\n 12%|█▎ | 5/40 [00:01<00:12, 2.85it/s]\n 15%|█▌ | 6/40 [00:02<00:11, 2.93it/s]\n 18%|█▊ | 7/40 [00:02<00:10, 3.01it/s]\n 20%|██ | 8/40 [00:02<00:10, 3.00it/s]\n 22%|██▎ | 9/40 [00:03<00:10, 3.03it/s]\n 25%|██▌ | 10/40 [00:03<00:09, 3.05it/s]\n 28%|██▊ | 11/40 [00:03<00:09, 3.06it/s]\n 30%|███ | 12/40 [00:04<00:09, 3.07it/s]\n 32%|███▎ | 13/40 [00:04<00:08, 3.08it/s]\n 35%|███▌ | 14/40 [00:04<00:08, 3.09it/s]\n 38%|███▊ | 15/40 [00:05<00:08, 3.09it/s]\n 40%|████ | 16/40 [00:05<00:07, 3.08it/s]\n 42%|████▎ | 17/40 [00:05<00:07, 3.08it/s]\n 45%|████▌ | 18/40 [00:06<00:07, 3.07it/s]\n 48%|████▊ | 19/40 [00:06<00:06, 3.07it/s]\n 50%|█████ | 20/40 [00:06<00:06, 3.08it/s]\n 52%|█████▎ | 21/40 [00:07<00:06, 3.07it/s]\n 55%|█████▌ | 22/40 [00:07<00:05, 3.06it/s]\n 57%|█████▊ | 23/40 [00:07<00:05, 3.06it/s]\n 60%|██████ | 24/40 [00:08<00:05, 3.06it/s]\n 62%|██████▎ | 25/40 [00:08<00:04, 3.01it/s]\n 65%|██████▌ | 26/40 [00:08<00:04, 3.03it/s]\n 68%|██████▊ | 27/40 [00:09<00:04, 3.04it/s]\n 70%|███████ | 28/40 [00:09<00:03, 3.04it/s]\n 72%|███████▎ | 29/40 [00:09<00:03, 3.05it/s]\n 75%|███████▌ | 30/40 [00:10<00:03, 3.04it/s]\n 78%|███████▊ | 31/40 [00:10<00:02, 3.05it/s]\n 80%|████████ | 32/40 [00:10<00:02, 3.06it/s]\n 82%|████████▎ | 33/40 [00:11<00:02, 3.07it/s]\n 85%|████████▌ | 34/40 [00:11<00:01, 3.08it/s]\n 88%|████████▊ | 35/40 [00:11<00:01, 3.08it/s]\n 90%|█████████ | 36/40 [00:12<00:01, 3.08it/s]\n 92%|█████████▎| 37/40 [00:12<00:00, 3.06it/s]\n 95%|█████████▌| 38/40 [00:12<00:00, 3.04it/s]\n 98%|█████████▊| 39/40 [00:13<00:00, 3.03it/s]\n100%|██████████| 40/40 [00:13<00:00, 3.03it/s]\n100%|██████████| 40/40 [00:13<00:00, 3.00it/s]", "metrics": { "predict_time": 44.264369, "total_time": 236.098116 }, "output": "https://replicate.delivery/pbxt/uQL969AiMJ6GIdI3iO2sxFik9amSKgpC3e0Tef4O1ohvsdIiA/out.png", "started_at": "2023-06-09T14:47:08.139449Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vra43nyuunhdxeb7jhipbjux6m", "cancel": "https://api.replicate.com/v1/predictions/vra43nyuunhdxeb7jhipbjux6m/cancel" }, "version": "8c51da11578f75df306db64e27fd337b8b18de902f49b4404b0b340dced96f48" }
Generated inUsing seed: 43695 /root/.pyenv/versions/3.10.12/lib/python3.10/site-packages/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_diffedit.py:162: FutureWarning: The preprocess method is deprecated and will be removed in a future version. Please use VaeImageProcessor.preprocess instead warnings.warn( 0%| | 0/39 [00:00<?, ?it/s] 3%|▎ | 1/39 [00:01<00:49, 1.31s/it] 5%|▌ | 2/39 [00:01<00:27, 1.33it/s] 8%|▊ | 3/39 [00:01<00:20, 1.80it/s] 10%|█ | 4/39 [00:02<00:16, 2.15it/s] 13%|█▎ | 5/39 [00:02<00:14, 2.42it/s] 15%|█▌ | 6/39 [00:02<00:12, 2.62it/s] 18%|█▊ | 7/39 [00:03<00:11, 2.77it/s] 21%|██ | 8/39 [00:03<00:10, 2.87it/s] 23%|██▎ | 9/39 [00:03<00:10, 2.94it/s] 26%|██▌ | 10/39 [00:04<00:09, 2.98it/s] 28%|██▊ | 11/39 [00:04<00:09, 3.04it/s] 31%|███ | 12/39 [00:04<00:08, 3.06it/s] 33%|███▎ | 13/39 [00:05<00:08, 3.07it/s] 36%|███▌ | 14/39 [00:05<00:08, 3.09it/s] 38%|███▊ | 15/39 [00:05<00:07, 3.09it/s] 41%|████ | 16/39 [00:06<00:07, 3.05it/s] 44%|████▎ | 17/39 [00:06<00:07, 3.07it/s] 46%|████▌ | 18/39 [00:06<00:06, 3.07it/s] 49%|████▊ | 19/39 [00:07<00:06, 3.08it/s] 51%|█████▏ | 20/39 [00:07<00:06, 3.07it/s] 54%|█████▍ | 21/39 [00:07<00:05, 3.08it/s] 56%|█████▋ | 22/39 [00:08<00:05, 3.08it/s] 59%|█████▉ | 23/39 [00:08<00:05, 3.09it/s] 62%|██████▏ | 24/39 [00:08<00:04, 3.08it/s] 64%|██████▍ | 25/39 [00:09<00:04, 3.09it/s] 67%|██████▋ | 26/39 [00:09<00:04, 3.09it/s] 69%|██████▉ | 27/39 [00:09<00:03, 3.09it/s] 72%|███████▏ | 28/39 [00:10<00:03, 3.09it/s] 74%|███████▍ | 29/39 [00:10<00:03, 3.09it/s] 77%|███████▋ | 30/39 [00:10<00:02, 3.08it/s] 79%|███████▉ | 31/39 [00:11<00:02, 3.10it/s] 82%|████████▏ | 32/39 [00:11<00:02, 3.11it/s] 85%|████████▍ | 33/39 [00:11<00:01, 3.10it/s] 87%|████████▋ | 34/39 [00:12<00:01, 3.10it/s] 90%|████████▉ | 35/39 [00:12<00:01, 3.09it/s] 92%|█████████▏| 36/39 [00:12<00:00, 3.09it/s] 95%|█████████▍| 37/39 [00:12<00:00, 3.10it/s] 97%|█████████▋| 38/39 [00:13<00:00, 3.09it/s] 100%|██████████| 39/39 [00:13<00:00, 3.08it/s] 100%|██████████| 39/39 [00:13<00:00, 2.86it/s] 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:23, 1.69it/s] 5%|▌ | 2/40 [00:00<00:16, 2.30it/s] 8%|▊ | 3/40 [00:01<00:14, 2.58it/s] 10%|█ | 4/40 [00:01<00:13, 2.75it/s] 12%|█▎ | 5/40 [00:01<00:12, 2.85it/s] 15%|█▌ | 6/40 [00:02<00:11, 2.93it/s] 18%|█▊ | 7/40 [00:02<00:10, 3.01it/s] 20%|██ | 8/40 [00:02<00:10, 3.00it/s] 22%|██▎ | 9/40 [00:03<00:10, 3.03it/s] 25%|██▌ | 10/40 [00:03<00:09, 3.05it/s] 28%|██▊ | 11/40 [00:03<00:09, 3.06it/s] 30%|███ | 12/40 [00:04<00:09, 3.07it/s] 32%|███▎ | 13/40 [00:04<00:08, 3.08it/s] 35%|███▌ | 14/40 [00:04<00:08, 3.09it/s] 38%|███▊ | 15/40 [00:05<00:08, 3.09it/s] 40%|████ | 16/40 [00:05<00:07, 3.08it/s] 42%|████▎ | 17/40 [00:05<00:07, 3.08it/s] 45%|████▌ | 18/40 [00:06<00:07, 3.07it/s] 48%|████▊ | 19/40 [00:06<00:06, 3.07it/s] 50%|█████ | 20/40 [00:06<00:06, 3.08it/s] 52%|█████▎ | 21/40 [00:07<00:06, 3.07it/s] 55%|█████▌ | 22/40 [00:07<00:05, 3.06it/s] 57%|█████▊ | 23/40 [00:07<00:05, 3.06it/s] 60%|██████ | 24/40 [00:08<00:05, 3.06it/s] 62%|██████▎ | 25/40 [00:08<00:04, 3.01it/s] 65%|██████▌ | 26/40 [00:08<00:04, 3.03it/s] 68%|██████▊ | 27/40 [00:09<00:04, 3.04it/s] 70%|███████ | 28/40 [00:09<00:03, 3.04it/s] 72%|███████▎ | 29/40 [00:09<00:03, 3.05it/s] 75%|███████▌ | 30/40 [00:10<00:03, 3.04it/s] 78%|███████▊ | 31/40 [00:10<00:02, 3.05it/s] 80%|████████ | 32/40 [00:10<00:02, 3.06it/s] 82%|████████▎ | 33/40 [00:11<00:02, 3.07it/s] 85%|████████▌ | 34/40 [00:11<00:01, 3.08it/s] 88%|████████▊ | 35/40 [00:11<00:01, 3.08it/s] 90%|█████████ | 36/40 [00:12<00:01, 3.08it/s] 92%|█████████▎| 37/40 [00:12<00:00, 3.06it/s] 95%|█████████▌| 38/40 [00:12<00:00, 3.04it/s] 98%|█████████▊| 39/40 [00:13<00:00, 3.03it/s] 100%|██████████| 40/40 [00:13<00:00, 3.03it/s] 100%|██████████| 40/40 [00:13<00:00, 3.00it/s]
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