juergengunz / real-esrgan-v2
Real-ESRGAN Upscale with AI Face Correction
- Public
- 517.4K runs
-
T4
Prediction
juergengunz/real-esrgan-v2:80a276b4054186f8e0a8c1440549daadabc1ab30374247767e65447662ecaffeIDutx33dzcwx5cbowoy5socueo6iStatusSucceededSourceWebHardwareT4Total durationCreatedInput
- image
- scale
- 2
- face_enhance
{ "image": "https://replicate.delivery/pbxt/JvMdwcP4oPmxlG4NVKEKuX6tUxGAhFZ1obDVj9ClJyvizzpM/pose_1.png", "scale": 2, "face_enhance": true }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 juergengunz/real-esrgan-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "juergengunz/real-esrgan-v2:80a276b4054186f8e0a8c1440549daadabc1ab30374247767e65447662ecaffe", { input: { image: "https://replicate.delivery/pbxt/JvMdwcP4oPmxlG4NVKEKuX6tUxGAhFZ1obDVj9ClJyvizzpM/pose_1.png", scale: 2, face_enhance: true } } ); // 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 juergengunz/real-esrgan-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "juergengunz/real-esrgan-v2:80a276b4054186f8e0a8c1440549daadabc1ab30374247767e65447662ecaffe", input={ "image": "https://replicate.delivery/pbxt/JvMdwcP4oPmxlG4NVKEKuX6tUxGAhFZ1obDVj9ClJyvizzpM/pose_1.png", "scale": 2, "face_enhance": True } ) # 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 juergengunz/real-esrgan-v2 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": "juergengunz/real-esrgan-v2:80a276b4054186f8e0a8c1440549daadabc1ab30374247767e65447662ecaffe", "input": { "image": "https://replicate.delivery/pbxt/JvMdwcP4oPmxlG4NVKEKuX6tUxGAhFZ1obDVj9ClJyvizzpM/pose_1.png", "scale": 2, "face_enhance": true } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-23T00:49:12.652294Z", "created_at": "2023-11-23T00:48:57.940643Z", "data_removed": false, "error": null, "id": "utx33dzcwx5cbowoy5socueo6i", "input": { "image": "https://replicate.delivery/pbxt/JvMdwcP4oPmxlG4NVKEKuX6tUxGAhFZ1obDVj9ClJyvizzpM/pose_1.png", "scale": 2, "face_enhance": true }, "logs": null, "metrics": { "predict_time": 14.69153, "total_time": 14.711651 }, "output": "https://replicate.delivery/pbxt/xkplNUt2dQrwLBGqSybh4Idg4NhUeEzCqfBZf9AH1i1OcK2jA/output.png", "started_at": "2023-11-23T00:48:57.960764Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/utx33dzcwx5cbowoy5socueo6i", "cancel": "https://api.replicate.com/v1/predictions/utx33dzcwx5cbowoy5socueo6i/cancel" }, "version": "80a276b4054186f8e0a8c1440549daadabc1ab30374247767e65447662ecaffe" }Prediction
juergengunz/real-esrgan-v2:5ab5278a3cc3f43636383fd06ecda824759068ce589531d1ff75e05a6d714344IDfxssyhzbbhl25pu5rod3f6qlgiStatusSucceededSourceWebHardwareT4Total durationCreatedInput
- image
- scale
- 1
- mouth_eyes
- face_enhance
{ "image": "https://replicate.delivery/pbxt/KL9xy3oqD922mNUIJMKFoS3rb483pKjY8vKv3N4RwaBDwlOM/test.png", "scale": 1, "mouth_eyes": true, "face_enhance": true }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 juergengunz/real-esrgan-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "juergengunz/real-esrgan-v2:5ab5278a3cc3f43636383fd06ecda824759068ce589531d1ff75e05a6d714344", { input: { image: "https://replicate.delivery/pbxt/KL9xy3oqD922mNUIJMKFoS3rb483pKjY8vKv3N4RwaBDwlOM/test.png", scale: 1, mouth_eyes: true, face_enhance: true } } ); // 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 juergengunz/real-esrgan-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "juergengunz/real-esrgan-v2:5ab5278a3cc3f43636383fd06ecda824759068ce589531d1ff75e05a6d714344", input={ "image": "https://replicate.delivery/pbxt/KL9xy3oqD922mNUIJMKFoS3rb483pKjY8vKv3N4RwaBDwlOM/test.png", "scale": 1, "mouth_eyes": True, "face_enhance": True } ) # 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 juergengunz/real-esrgan-v2 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": "juergengunz/real-esrgan-v2:5ab5278a3cc3f43636383fd06ecda824759068ce589531d1ff75e05a6d714344", "input": { "image": "https://replicate.delivery/pbxt/KL9xy3oqD922mNUIJMKFoS3rb483pKjY8vKv3N4RwaBDwlOM/test.png", "scale": 1, "mouth_eyes": true, "face_enhance": true } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-02-03T17:01:24.293283Z", "created_at": "2024-02-03T16:57:13.151147Z", "data_removed": false, "error": null, "id": "fxssyhzbbhl25pu5rod3f6qlgi", "input": { "image": "https://replicate.delivery/pbxt/KL9xy3oqD922mNUIJMKFoS3rb483pKjY8vKv3N4RwaBDwlOM/test.png", "scale": 1, "mouth_eyes": true, "face_enhance": true }, "logs": "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\nE0000 00:00:1706979683.353118 301 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context)\nE0000 00:00:1706979683.353220 301 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context)\nE0000 00:00:1706979683.353241 301 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context)\nINFO: Created TensorFlow Lite XNNPACK delegate for CPU.", "metrics": { "predict_time": 5.262669, "total_time": 251.142136 }, "output": "https://replicate.delivery/pbxt/8Xx5G3fox8wRSiZOn8BNFhVuciub95CjodbMxhiv4rqxGhJJA/output.png", "started_at": "2024-02-03T17:01:19.030614Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/fxssyhzbbhl25pu5rod3f6qlgi", "cancel": "https://api.replicate.com/v1/predictions/fxssyhzbbhl25pu5rod3f6qlgi/cancel" }, "version": "5ab5278a3cc3f43636383fd06ecda824759068ce589531d1ff75e05a6d714344" }Generated inWARNING: All log messages before absl::InitializeLog() is called are written to STDERR E0000 00:00:1706979683.353118 301 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context) E0000 00:00:1706979683.353220 301 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context) E0000 00:00:1706979683.353241 301 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context) INFO: Created TensorFlow Lite XNNPACK delegate for CPU.Prediction
juergengunz/real-esrgan-v2:1da204436153abcf6d3668b80bc6a5a84aec45cb0e3c8467db6c632da8b10b9fIDd19d52hab1rga0cezh69qxy0jcStatusSucceededSourceWebHardwareT4Total durationCreatedInput
- image
- scale
- 1
- mouth_eyes
- face_enhance
{ "image": "https://replicate.delivery/pbxt/KmTutYmyDQXgoBvhrGYdn9VULPisOBZ4itzy5bJ6Q0Egp84A/test.png", "scale": 1, "mouth_eyes": true, "face_enhance": true }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 juergengunz/real-esrgan-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "juergengunz/real-esrgan-v2:1da204436153abcf6d3668b80bc6a5a84aec45cb0e3c8467db6c632da8b10b9f", { input: { image: "https://replicate.delivery/pbxt/KmTutYmyDQXgoBvhrGYdn9VULPisOBZ4itzy5bJ6Q0Egp84A/test.png", scale: 1, mouth_eyes: true, face_enhance: true } } ); // 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 juergengunz/real-esrgan-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "juergengunz/real-esrgan-v2:1da204436153abcf6d3668b80bc6a5a84aec45cb0e3c8467db6c632da8b10b9f", input={ "image": "https://replicate.delivery/pbxt/KmTutYmyDQXgoBvhrGYdn9VULPisOBZ4itzy5bJ6Q0Egp84A/test.png", "scale": 1, "mouth_eyes": True, "face_enhance": True } ) # 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 juergengunz/real-esrgan-v2 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": "juergengunz/real-esrgan-v2:1da204436153abcf6d3668b80bc6a5a84aec45cb0e3c8467db6c632da8b10b9f", "input": { "image": "https://replicate.delivery/pbxt/KmTutYmyDQXgoBvhrGYdn9VULPisOBZ4itzy5bJ6Q0Egp84A/test.png", "scale": 1, "mouth_eyes": true, "face_enhance": true } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-04-20T16:19:49.760405Z", "created_at": "2024-04-20T16:17:13.816000Z", "data_removed": false, "error": null, "id": "d19d52hab1rga0cezh69qxy0jc", "input": { "image": "https://replicate.delivery/pbxt/KmTutYmyDQXgoBvhrGYdn9VULPisOBZ4itzy5bJ6Q0Egp84A/test.png", "scale": 1, "mouth_eyes": true, "face_enhance": true }, "logs": "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\nE0000 00:00:1713629989.432544 312 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context)\nE0000 00:00:1713629989.432612 312 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context)\nE0000 00:00:1713629989.432629 312 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context)\nINFO: Created TensorFlow Lite XNNPACK delegate for CPU.", "metrics": { "predict_time": 3.910176, "total_time": 155.944405 }, "output": "https://replicate.delivery/pbxt/KMhHZ8MUexXJJ6RIpVjUdVXHf4Oj5Nn9ebv0c7aPBpsKpzYlA/output.png", "started_at": "2024-04-20T16:19:45.850229Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/d19d52hab1rga0cezh69qxy0jc", "cancel": "https://api.replicate.com/v1/predictions/d19d52hab1rga0cezh69qxy0jc/cancel" }, "version": "1da204436153abcf6d3668b80bc6a5a84aec45cb0e3c8467db6c632da8b10b9f" }Generated inWARNING: All log messages before absl::InitializeLog() is called are written to STDERR E0000 00:00:1713629989.432544 312 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context) E0000 00:00:1713629989.432612 312 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context) E0000 00:00:1713629989.432629 312 gl_context.cc:408] INTERNAL: ; RET_CHECK failure (mediapipe/gpu/gl_context_egl.cc:303) successeglMakeCurrent() returned error 0x3008; (entering GL context) INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
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