tommoore515 / pix2pix_tf_albedo2pbrmaps
pix2pix model for predicting pbr texture maps from an albedo texture
Prediction
tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825eIDlfftbzredvdpfj57wyirdmvexiStatusSucceededSourceWebHardware–Total durationCreatedInput
{ "model": "albedo2normal", "imagepath": "https://replicate.delivery/mgxm/9089cccc-0e7b-4f1b-9ff4-d91bb47b9449/Tan_marble.jpg" }
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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", { input: { model: "albedo2normal", imagepath: "https://replicate.delivery/mgxm/9089cccc-0e7b-4f1b-9ff4-d91bb47b9449/Tan_marble.jpg" } } ); // 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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", input={ "model": "albedo2normal", "imagepath": "https://replicate.delivery/mgxm/9089cccc-0e7b-4f1b-9ff4-d91bb47b9449/Tan_marble.jpg" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run tommoore515/pix2pix_tf_albedo2pbrmaps 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": "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", "input": { "model": "albedo2normal", "imagepath": "https://replicate.delivery/mgxm/9089cccc-0e7b-4f1b-9ff4-d91bb47b9449/Tan_marble.jpg" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-09-27T12:40:30.370795Z", "created_at": "2022-09-27T12:37:19.466566Z", "data_removed": false, "error": null, "id": "lfftbzredvdpfj57wyirdmvexi", "input": { "model": "albedo2normal", "imagepath": "https://replicate.delivery/mgxm/9089cccc-0e7b-4f1b-9ff4-d91bb47b9449/Tan_marble.jpg" }, "logs": "Loading image...\n2022-09-27 12:40:22.596401: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n2022-09-27 12:40:22.709319: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n2022-09-27 12:40:22.710273: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n2022-09-27 12:40:22.711626: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\nTo enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n2022-09-27 12:40:22.712309: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n2022-09-27 12:40:22.713028: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n2022-09-27 12:40:22.713709: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n2022-09-27 12:40:23.548811: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n2022-09-27 12:40:23.549636: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n2022-09-27 12:40:23.550334: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n2022-09-27 12:40:23.550988: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 13793 MB memory: -> device: 0, name: Tesla T4, pci bus id: 0000:00:04.0, compute capability: 7.5\nLoading model (albedo2normal)...\nModel Loaded\n2022-09-27 12:40:26.104899: I tensorflow/stream_executor/cuda/cuda_dnn.cc:384] Loaded cuDNN version 8101\nPrediction Successful", "metrics": { "predict_time": 7.747255, "total_time": 190.904229 }, "output": "https://replicate.delivery/mgxm/f35a9c7c-34f7-40fc-be6a-8ce61f92132f/output.jpg", "started_at": "2022-09-27T12:40:22.623540Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/lfftbzredvdpfj57wyirdmvexi", "cancel": "https://api.replicate.com/v1/predictions/lfftbzredvdpfj57wyirdmvexi/cancel" }, "version": "21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e" }
Generated inLoading image... 2022-09-27 12:40:22.596401: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-27 12:40:22.709319: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-27 12:40:22.710273: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-27 12:40:22.711626: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2022-09-27 12:40:22.712309: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-27 12:40:22.713028: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-27 12:40:22.713709: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-27 12:40:23.548811: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-27 12:40:23.549636: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-27 12:40:23.550334: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-27 12:40:23.550988: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 13793 MB memory: -> device: 0, name: Tesla T4, pci bus id: 0000:00:04.0, compute capability: 7.5 Loading model (albedo2normal)... Model Loaded 2022-09-27 12:40:26.104899: I tensorflow/stream_executor/cuda/cuda_dnn.cc:384] Loaded cuDNN version 8101 Prediction Successful
Prediction
tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825eIDd2bmegilyvdi5ikysphvllxdyiStatusSucceededSourceWebHardware–Total durationCreatedInput
{ "model": "albedo2height", "imagepath": "https://replicate.delivery/mgxm/b766c89e-c5ec-456d-b9c4-7209dbb0a4b6/brown_planks_03.jpg" }
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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", { input: { model: "albedo2height", imagepath: "https://replicate.delivery/mgxm/b766c89e-c5ec-456d-b9c4-7209dbb0a4b6/brown_planks_03.jpg" } } ); // 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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", input={ "model": "albedo2height", "imagepath": "https://replicate.delivery/mgxm/b766c89e-c5ec-456d-b9c4-7209dbb0a4b6/brown_planks_03.jpg" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run tommoore515/pix2pix_tf_albedo2pbrmaps 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": "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", "input": { "model": "albedo2height", "imagepath": "https://replicate.delivery/mgxm/b766c89e-c5ec-456d-b9c4-7209dbb0a4b6/brown_planks_03.jpg" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-09-27T12:44:18.594862Z", "created_at": "2022-09-27T12:44:15.882571Z", "data_removed": false, "error": null, "id": "d2bmegilyvdi5ikysphvllxdyi", "input": { "model": "albedo2height", "imagepath": "https://replicate.delivery/mgxm/b766c89e-c5ec-456d-b9c4-7209dbb0a4b6/brown_planks_03.jpg" }, "logs": "Loading image...\nLoading model (albedo2height)...\nModel Loaded\nPrediction Successful", "metrics": { "predict_time": 2.502377, "total_time": 2.712291 }, "output": "https://replicate.delivery/mgxm/d713cddb-33f2-403a-ae3c-6ca08f41b4c6/output.jpg", "started_at": "2022-09-27T12:44:16.092485Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/d2bmegilyvdi5ikysphvllxdyi", "cancel": "https://api.replicate.com/v1/predictions/d2bmegilyvdi5ikysphvllxdyi/cancel" }, "version": "21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e" }
Generated inLoading image... Loading model (albedo2height)... Model Loaded Prediction Successful
Prediction
tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825eIDacbftqbmfjbl5lutt75qnknraeStatusSucceededSourceWebHardware–Total durationCreatedInput
{ "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/54b4d93c-45f4-4ba4-aec8-fad65fb1cba6/Bricks076C_1K.jpg" }
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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", { input: { model: "height2ao", imagepath: "https://replicate.delivery/mgxm/54b4d93c-45f4-4ba4-aec8-fad65fb1cba6/Bricks076C_1K.jpg" } } ); // 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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", input={ "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/54b4d93c-45f4-4ba4-aec8-fad65fb1cba6/Bricks076C_1K.jpg" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run tommoore515/pix2pix_tf_albedo2pbrmaps 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": "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", "input": { "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/54b4d93c-45f4-4ba4-aec8-fad65fb1cba6/Bricks076C_1K.jpg" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-09-27T12:45:14.634821Z", "created_at": "2022-09-27T12:45:11.943620Z", "data_removed": false, "error": null, "id": "acbftqbmfjbl5lutt75qnknrae", "input": { "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/54b4d93c-45f4-4ba4-aec8-fad65fb1cba6/Bricks076C_1K.jpg" }, "logs": "Loading image...\nLoading model (height2ao)...\nModel Loaded\nPrediction Successful", "metrics": { "predict_time": 2.476493, "total_time": 2.691201 }, "output": "https://replicate.delivery/mgxm/0f196574-9c78-45f3-9eb0-4827be27fa99/output.jpg", "started_at": "2022-09-27T12:45:12.158328Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/acbftqbmfjbl5lutt75qnknrae", "cancel": "https://api.replicate.com/v1/predictions/acbftqbmfjbl5lutt75qnknrae/cancel" }, "version": "21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e" }
Generated inLoading image... Loading model (height2ao)... Model Loaded Prediction Successful
Prediction
tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825eIDr4rznss5bvcttfbhurncimnqeuStatusSucceededSourceWebHardware–Total durationCreatedInput
{ "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/b125e8a5-b9e2-44e8-a58e-96fc8425ebd2/floor_pattern_02.jpg" }
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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", { input: { model: "height2ao", imagepath: "https://replicate.delivery/mgxm/b125e8a5-b9e2-44e8-a58e-96fc8425ebd2/floor_pattern_02.jpg" } } ); // 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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", input={ "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/b125e8a5-b9e2-44e8-a58e-96fc8425ebd2/floor_pattern_02.jpg" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run tommoore515/pix2pix_tf_albedo2pbrmaps 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": "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", "input": { "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/b125e8a5-b9e2-44e8-a58e-96fc8425ebd2/floor_pattern_02.jpg" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-09-27T12:45:40.779400Z", "created_at": "2022-09-27T12:45:37.646696Z", "data_removed": false, "error": null, "id": "r4rznss5bvcttfbhurncimnqeu", "input": { "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/b125e8a5-b9e2-44e8-a58e-96fc8425ebd2/floor_pattern_02.jpg" }, "logs": "Loading image...\nLoading model (height2ao)...\nModel Loaded\nPrediction Successful", "metrics": { "predict_time": 2.574689, "total_time": 3.132704 }, "output": "https://replicate.delivery/mgxm/1e3fdaad-fd4b-49b7-9a01-a83d2c29edc4/output.jpg", "started_at": "2022-09-27T12:45:38.204711Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/r4rznss5bvcttfbhurncimnqeu", "cancel": "https://api.replicate.com/v1/predictions/r4rznss5bvcttfbhurncimnqeu/cancel" }, "version": "21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e" }
Generated inLoading image... Loading model (height2ao)... Model Loaded Prediction Successful
Prediction
tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825eInput
{ "model": "albedo2smoothness", "imagepath": "https://replicate.delivery/mgxm/513af690-1c40-4245-9475-adb3f21b05d2/Diagonal_cedar.jpg" }
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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", { input: { model: "albedo2smoothness", imagepath: "https://replicate.delivery/mgxm/513af690-1c40-4245-9475-adb3f21b05d2/Diagonal_cedar.jpg" } } ); // 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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", input={ "model": "albedo2smoothness", "imagepath": "https://replicate.delivery/mgxm/513af690-1c40-4245-9475-adb3f21b05d2/Diagonal_cedar.jpg" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run tommoore515/pix2pix_tf_albedo2pbrmaps 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": "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", "input": { "model": "albedo2smoothness", "imagepath": "https://replicate.delivery/mgxm/513af690-1c40-4245-9475-adb3f21b05d2/Diagonal_cedar.jpg" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-09-27T12:46:08.016208Z", "created_at": "2022-09-27T12:46:05.069543Z", "data_removed": false, "error": null, "id": "vbpki5vkljhzplgfqpwjadn4ha", "input": { "model": "albedo2smoothness", "imagepath": "https://replicate.delivery/mgxm/513af690-1c40-4245-9475-adb3f21b05d2/Diagonal_cedar.jpg" }, "logs": "Loading image...\nLoading model (albedo2smoothness)...\nModel Loaded\nPrediction Successful", "metrics": { "predict_time": 2.308755, "total_time": 2.946665 }, "output": "https://replicate.delivery/mgxm/4c1d9f9f-dd49-4a40-a90e-fb6fb87fa6d2/output.jpg", "started_at": "2022-09-27T12:46:05.707453Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vbpki5vkljhzplgfqpwjadn4ha", "cancel": "https://api.replicate.com/v1/predictions/vbpki5vkljhzplgfqpwjadn4ha/cancel" }, "version": "21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e" }
Generated inLoading image... Loading model (albedo2smoothness)... Model Loaded Prediction Successful
Prediction
tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825eIDp73wcungxvdsva5vhpxmh4myfmStatusSucceededSourceWebHardware–Total durationCreatedInput
{ "model": "albedo2normal", "imagepath": "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg" }
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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", { input: { model: "albedo2normal", imagepath: "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg" } } ); // 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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", input={ "model": "albedo2normal", "imagepath": "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run tommoore515/pix2pix_tf_albedo2pbrmaps 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": "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", "input": { "model": "albedo2normal", "imagepath": "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-09-27T12:47:17.535489Z", "created_at": "2022-09-27T12:47:14.791697Z", "data_removed": false, "error": null, "id": "p73wcungxvdsva5vhpxmh4myfm", "input": { "model": "albedo2normal", "imagepath": "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg" }, "logs": "Loading image...\nLoading model (albedo2normal)...\nModel Loaded\nPrediction Successful", "metrics": { "predict_time": 2.522707, "total_time": 2.743792 }, "output": "https://replicate.delivery/mgxm/6ae67768-8b1b-4f54-a2f3-83737eae454f/output.jpg", "started_at": "2022-09-27T12:47:15.012782Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/p73wcungxvdsva5vhpxmh4myfm", "cancel": "https://api.replicate.com/v1/predictions/p73wcungxvdsva5vhpxmh4myfm/cancel" }, "version": "21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e" }
Generated inLoading image... Loading model (albedo2normal)... Model Loaded Prediction Successful
Prediction
tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825eID5i6dhoq4djh5pgqzxecp26nyr4StatusSucceededSourceWebHardware–Total durationCreatedInput
{ "model": "albedo2height", "imagepath": "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg" }
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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", { input: { model: "albedo2height", imagepath: "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg" } } ); // 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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", input={ "model": "albedo2height", "imagepath": "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run tommoore515/pix2pix_tf_albedo2pbrmaps 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": "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", "input": { "model": "albedo2height", "imagepath": "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-09-27T12:47:51.255760Z", "created_at": "2022-09-27T12:47:48.391602Z", "data_removed": false, "error": null, "id": "5i6dhoq4djh5pgqzxecp26nyr4", "input": { "model": "albedo2height", "imagepath": "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg" }, "logs": "Loading image...\nLoading model (albedo2height)...\nModel Loaded\nPrediction Successful", "metrics": { "predict_time": 1.945114, "total_time": 2.864158 }, "output": "https://replicate.delivery/mgxm/cd6cba65-38a1-4df0-8279-aedf38a627c4/output.jpg", "started_at": "2022-09-27T12:47:49.310646Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/5i6dhoq4djh5pgqzxecp26nyr4", "cancel": "https://api.replicate.com/v1/predictions/5i6dhoq4djh5pgqzxecp26nyr4/cancel" }, "version": "21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e" }
Generated inLoading image... Loading model (albedo2height)... Model Loaded Prediction Successful
Prediction
tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825eID4ytxlnzdzbdslks5mkw2gei7raStatusSucceededSourceWebHardware–Total durationCreatedInput
{ "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/efec74ed-3221-4227-b759-a3112cfe59e8/output_1.jpg" }
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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", { input: { model: "height2ao", imagepath: "https://replicate.delivery/mgxm/efec74ed-3221-4227-b759-a3112cfe59e8/output_1.jpg" } } ); // 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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", input={ "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/efec74ed-3221-4227-b759-a3112cfe59e8/output_1.jpg" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run tommoore515/pix2pix_tf_albedo2pbrmaps 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": "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e", "input": { "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/efec74ed-3221-4227-b759-a3112cfe59e8/output_1.jpg" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-09-27T12:48:16.469261Z", "created_at": "2022-09-27T12:48:13.422420Z", "data_removed": false, "error": null, "id": "4ytxlnzdzbdslks5mkw2gei7ra", "input": { "model": "height2ao", "imagepath": "https://replicate.delivery/mgxm/efec74ed-3221-4227-b759-a3112cfe59e8/output_1.jpg" }, "logs": "Loading image...\nLoading model (height2ao)...\nModel Loaded\nPrediction Successful", "metrics": { "predict_time": 2.67757, "total_time": 3.046841 }, "output": "https://replicate.delivery/mgxm/23bd0ddb-6544-4531-9bff-fc46649d52ad/output.jpg", "started_at": "2022-09-27T12:48:13.791691Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4ytxlnzdzbdslks5mkw2gei7ra", "cancel": "https://api.replicate.com/v1/predictions/4ytxlnzdzbdslks5mkw2gei7ra/cancel" }, "version": "21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e" }
Generated inLoading image... Loading model (height2ao)... Model Loaded Prediction Successful
Want to make some of these yourself?
Run this model