iceclear / stablesr
Exploiting Diffusion Prior for Real-World Image Super-Resolution
Prediction
iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51bIDvwqsxtrbx64uwtd2aetfzir55aStatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedInput
- seed
- 42
- upscale
- 4
- ddpm_steps
- 200
- input_image
- tile_overlap
- 32
- colorfix_type
- adain
- fidelity_weight
- 0.5
{ "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JPdHjT2nuixBTTtKrwMFyy9UE1QqB7Mr0T7baVtgnq7l4ogK/OST_120.png", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run iceclear/stablesr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b", { input: { seed: 42, upscale: 4, ddpm_steps: 200, input_image: "https://replicate.delivery/pbxt/JPdHjT2nuixBTTtKrwMFyy9UE1QqB7Mr0T7baVtgnq7l4ogK/OST_120.png", tile_overlap: 32, colorfix_type: "adain", fidelity_weight: 0.5 } } ); // 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 replicateImport the client:import replicateRun iceclear/stablesr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b", input={ "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JPdHjT2nuixBTTtKrwMFyy9UE1QqB7Mr0T7baVtgnq7l4ogK/OST_120.png", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run iceclear/stablesr 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": "iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b", "input": { "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JPdHjT2nuixBTTtKrwMFyy9UE1QqB7Mr0T7baVtgnq7l4ogK/OST_120.png", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-25T15:19:29.174935Z", "created_at": "2023-08-25T15:19:06.422027Z", "data_removed": false, "error": null, "id": "vwqsxtrbx64uwtd2aetfzir55a", "input": { "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JPdHjT2nuixBTTtKrwMFyy9UE1QqB7Mr0T7baVtgnq7l4ogK/OST_120.png", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 }, "logs": "Using seed: 42\nGlobal seed set to 42\nloaded input image of size (128, 128) from /tmp/tmpe7rru6n3OST_120.png\ntorch.Size([1, 3, 512, 512])\nSampling t: 0%| | 0/200 [00:00<?, ?it/s]\nSampling t: 0%| | 1/200 [00:00<00:21, 9.20it/s]\nSampling t: 1%| | 2/200 [00:00<00:21, 9.38it/s]\nSampling t: 2%|▏ | 3/200 [00:00<00:21, 9.02it/s]\nSampling t: 2%|▏ | 4/200 [00:00<00:22, 8.90it/s]\nSampling t: 2%|▎ | 5/200 [00:00<00:21, 8.95it/s]\nSampling t: 3%|▎ | 6/200 [00:00<00:22, 8.77it/s]\nSampling t: 4%|▎ | 7/200 [00:00<00:21, 8.97it/s]\nSampling t: 4%|▍ | 9/200 [00:00<00:20, 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}, "version": "01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b" }Generated inUsing seed: 42 Global seed set to 42 loaded input image of size (128, 128) from /tmp/tmpe7rru6n3OST_120.png torch.Size([1, 3, 512, 512]) Sampling t: 0%| | 0/200 [00:00<?, ?it/s] Sampling t: 0%| | 1/200 [00:00<00:21, 9.20it/s] Sampling t: 1%| | 2/200 [00:00<00:21, 9.38it/s] Sampling t: 2%|▏ | 3/200 [00:00<00:21, 9.02it/s] Sampling t: 2%|▏ | 4/200 [00:00<00:22, 8.90it/s] Sampling t: 2%|▎ | 5/200 [00:00<00:21, 8.95it/s] Sampling t: 3%|▎ | 6/200 [00:00<00:22, 8.77it/s] Sampling t: 4%|▎ | 7/200 [00:00<00:21, 8.97it/s] Sampling t: 4%|▍ | 9/200 [00:00<00:20, 9.29it/s] Sampling t: 5%|▌ | 10/200 [00:01<00:20, 9.16it/s] Sampling t: 6%|▌ | 11/200 [00:01<00:20, 9.19it/s] Sampling t: 6%|▌ | 12/200 [00:01<00:21, 8.88it/s] Sampling t: 6%|▋ | 13/200 [00:01<00:20, 9.02it/s] Sampling t: 8%|▊ | 15/200 [00:01<00:19, 9.47it/s] Sampling t: 8%|▊ | 16/200 [00:01<00:19, 9.49it/s] Sampling t: 9%|▉ | 18/200 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iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51bIDcsrc6njbe6n7dtsgg7szvumlpmStatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedInput
- seed
- 42
- upscale
- 4
- ddpm_steps
- 200
- input_image
- tile_overlap
- 32
- colorfix_type
- adain
- fidelity_weight
- 0.5
{ "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JPdJCH1GSMb9UxE4FVwaAHWqeUYV32KU403thFcjpnkj4wVM/comic3.png", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run iceclear/stablesr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b", { input: { seed: 42, upscale: 4, ddpm_steps: 200, input_image: "https://replicate.delivery/pbxt/JPdJCH1GSMb9UxE4FVwaAHWqeUYV32KU403thFcjpnkj4wVM/comic3.png", tile_overlap: 32, colorfix_type: "adain", fidelity_weight: 0.5 } } ); // 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 replicateImport the client:import replicateRun iceclear/stablesr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b", input={ "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JPdJCH1GSMb9UxE4FVwaAHWqeUYV32KU403thFcjpnkj4wVM/comic3.png", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run iceclear/stablesr 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": "iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b", "input": { "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JPdJCH1GSMb9UxE4FVwaAHWqeUYV32KU403thFcjpnkj4wVM/comic3.png", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-25T15:23:41.029168Z", "created_at": "2023-08-25T15:20:36.674608Z", "data_removed": false, "error": null, "id": "csrc6njbe6n7dtsgg7szvumlpm", "input": { "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JPdJCH1GSMb9UxE4FVwaAHWqeUYV32KU403thFcjpnkj4wVM/comic3.png", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 }, "logs": "Using seed: 42\nGlobal seed set to 42\nloaded input image of size (256, 256) from /tmp/tmp_b2tnjymcomic3.png\ntorch.Size([1, 3, 1024, 1024])\nSampling t: 0%| | 0/200 [00:00<?, ?it/s]\nSampling t: 0%| | 1/200 [00:00<02:53, 1.15it/s]\nSampling t: 1%| | 2/200 [00:01<02:54, 1.13it/s]\nSampling t: 2%|▏ | 3/200 [00:02<02:52, 1.14it/s]\nSampling t: 2%|▏ | 4/200 [00:03<02:52, 1.14it/s]\nSampling t: 2%|▎ | 5/200 [00:04<03:03, 1.06it/s]\nSampling t: 3%|▎ | 6/200 [00:05<03:03, 1.06it/s]\nSampling t: 4%|▎ | 7/200 [00:06<03:01, 1.07it/s]\nSampling t: 4%|▍ | 8/200 [00:07<02:54, 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1.21it/s]\nSampling t: 100%|██████████| 200/200 [03:00<00:00, 1.11it/s]", "metrics": { "predict_time": 184.384418, "total_time": 184.35456 }, "output": "https://replicate.delivery/pbxt/eNI7hNd4OSysTKVL3zWRvKFIW6ef8N2nu4xJa6ZFeOyzXesLC/out.png", "started_at": "2023-08-25T15:20:36.644750Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/csrc6njbe6n7dtsgg7szvumlpm", "cancel": "https://api.replicate.com/v1/predictions/csrc6njbe6n7dtsgg7szvumlpm/cancel" }, "version": "01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b" }Generated inUsing seed: 42 Global seed set to 42 loaded input image of size (256, 256) from /tmp/tmp_b2tnjymcomic3.png torch.Size([1, 3, 1024, 1024]) Sampling t: 0%| | 0/200 [00:00<?, ?it/s] Sampling t: 0%| | 1/200 [00:00<02:53, 1.15it/s] Sampling t: 1%| | 2/200 [00:01<02:54, 1.13it/s] Sampling t: 2%|▏ | 3/200 [00:02<02:52, 1.14it/s] Sampling t: 2%|▏ | 4/200 [00:03<02:52, 1.14it/s] Sampling t: 2%|▎ | 5/200 [00:04<03:03, 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1.11it/s]Prediction
iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51bID3qdszwbbcnet72dzpozws6zx2iStatusSucceededSourceWebHardwareA100 (40GB)Total durationCreatedInput
- seed
- 42
- upscale
- 4
- ddpm_steps
- 200
- input_image
- tile_overlap
- 32
- colorfix_type
- adain
- fidelity_weight
- 0.5
{ "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JXi09Nq70PwtG7i0prOFLoXj3WQcZ7az72NBV3dmoey6rzlq/ADE_val_00000711.jpg", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run iceclear/stablesr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b", { input: { seed: 42, upscale: 4, ddpm_steps: 200, input_image: "https://replicate.delivery/pbxt/JXi09Nq70PwtG7i0prOFLoXj3WQcZ7az72NBV3dmoey6rzlq/ADE_val_00000711.jpg", tile_overlap: 32, colorfix_type: "adain", fidelity_weight: 0.5 } } ); // 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 replicateImport the client:import replicateRun iceclear/stablesr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b", input={ "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JXi09Nq70PwtG7i0prOFLoXj3WQcZ7az72NBV3dmoey6rzlq/ADE_val_00000711.jpg", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run iceclear/stablesr 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": "iceclear/stablesr:01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b", "input": { "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JXi09Nq70PwtG7i0prOFLoXj3WQcZ7az72NBV3dmoey6rzlq/ADE_val_00000711.jpg", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-17T09:26:56.489582Z", "created_at": "2023-09-17T09:22:23.804048Z", "data_removed": false, "error": null, "id": "3qdszwbbcnet72dzpozws6zx2i", "input": { "seed": 42, "upscale": 4, "ddpm_steps": 200, "input_image": "https://replicate.delivery/pbxt/JXi09Nq70PwtG7i0prOFLoXj3WQcZ7az72NBV3dmoey6rzlq/ADE_val_00000711.jpg", "tile_overlap": 32, "colorfix_type": "adain", "fidelity_weight": 0.5 }, "logs": "Using seed: 42\nGlobal seed set to 42\nloaded input image of size (352, 224) from /tmp/tmpsevgvpumADE_val_00000711.jpg\ntorch.Size([1, 3, 896, 1408])\nSampling t: 0%| | 0/200 [00:00<?, ?it/s]\nSampling t: 0%| | 1/200 [00:01<04:30, 1.36s/it]\nSampling t: 1%| | 2/200 [00:02<04:31, 1.37s/it]\nSampling t: 2%|▏ | 3/200 [00:04<04:29, 1.37s/it]\nSampling t: 2%|▏ | 4/200 [00:05<04:26, 1.36s/it]\nSampling t: 2%|▎ | 5/200 [00:06<04:26, 1.36s/it]\nSampling t: 3%|▎ | 6/200 [00:08<04:24, 1.36s/it]\nSampling t: 4%|▎ | 7/200 [00:09<04:22, 1.36s/it]\nSampling t: 4%|▍ | 8/200 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1.37s/it]\nSampling t: 100%|██████████| 200/200 [04:30<00:00, 1.35s/it]", "metrics": { "predict_time": 272.710049, "total_time": 272.685534 }, "output": "https://pbxt.replicate.delivery/DCi4xNf4bCT1J6Ge7jnkHwK8UtQrzwxEpHpq7ZWhoZXfCPKjA/out.png", "started_at": "2023-09-17T09:22:23.779533Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3qdszwbbcnet72dzpozws6zx2i", "cancel": "https://api.replicate.com/v1/predictions/3qdszwbbcnet72dzpozws6zx2i/cancel" }, "version": "01e431cbcf30e2307c61dadca4db988411bc297d35f9bcad8b84ec1462cfe51b" }Generated inUsing seed: 42 Global seed set to 42 loaded input image of size (352, 224) from /tmp/tmpsevgvpumADE_val_00000711.jpg torch.Size([1, 3, 896, 1408]) Sampling t: 0%| | 0/200 [00:00<?, ?it/s] Sampling t: 0%| | 1/200 [00:01<04:30, 1.36s/it] Sampling t: 1%| | 2/200 [00:02<04:31, 1.37s/it] Sampling t: 2%|▏ | 3/200 [00:04<04:29, 1.37s/it] Sampling t: 2%|▏ | 4/200 [00:05<04:26, 1.36s/it] Sampling t: 2%|▎ | 5/200 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1.35s/it]
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