google-research
/
frame-interpolation
Frame Interpolation for Large Scene Motion
Prediction
google-research/frame-interpolation:b32da6e382a155169388ca9046bae303398b4db21ec8ee0ada832bb9c8d48481IDt6hpx4ci4jc7flikqferxbjj24StatusSucceededSourceWebHardware–Total durationCreatedInput
- frame1
- frame2
- times_to_interpolate
- "7"
{ "frame1": "https://replicate.delivery/mgxm/8e21c0d6-27b9-4ef5-b430-74dc2f686696/Screen_Shot_2022-02-11_at_17.08.06.png", "frame2": "https://replicate.delivery/mgxm/8e0bea7e-e6fc-4923-a9bc-3af357c78479/Screen_Shot_2022-02-11_at_17.07.57.png", "times_to_interpolate": "7" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run google-research/frame-interpolation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "google-research/frame-interpolation:b32da6e382a155169388ca9046bae303398b4db21ec8ee0ada832bb9c8d48481", { input: { frame1: "https://replicate.delivery/mgxm/8e21c0d6-27b9-4ef5-b430-74dc2f686696/Screen_Shot_2022-02-11_at_17.08.06.png", frame2: "https://replicate.delivery/mgxm/8e0bea7e-e6fc-4923-a9bc-3af357c78479/Screen_Shot_2022-02-11_at_17.07.57.png", times_to_interpolate: "7" } } ); console.log(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 google-research/frame-interpolation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "google-research/frame-interpolation:b32da6e382a155169388ca9046bae303398b4db21ec8ee0ada832bb9c8d48481", input={ "frame1": "https://replicate.delivery/mgxm/8e21c0d6-27b9-4ef5-b430-74dc2f686696/Screen_Shot_2022-02-11_at_17.08.06.png", "frame2": "https://replicate.delivery/mgxm/8e0bea7e-e6fc-4923-a9bc-3af357c78479/Screen_Shot_2022-02-11_at_17.07.57.png", "times_to_interpolate": "7" } ) # The google-research/frame-interpolation model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/google-research/frame-interpolation/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run google-research/frame-interpolation 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": "b32da6e382a155169388ca9046bae303398b4db21ec8ee0ada832bb9c8d48481", "input": { "frame1": "https://replicate.delivery/mgxm/8e21c0d6-27b9-4ef5-b430-74dc2f686696/Screen_Shot_2022-02-11_at_17.08.06.png", "frame2": "https://replicate.delivery/mgxm/8e0bea7e-e6fc-4923-a9bc-3af357c78479/Screen_Shot_2022-02-11_at_17.07.57.png", "times_to_interpolate": "7" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-02-12T01:12:23.713898Z", "created_at": "2022-02-12T01:10:10.069464Z", "data_removed": false, "error": null, "id": "t6hpx4ci4jc7flikqferxbjj24", "input": { "frame1": "https://replicate.delivery/mgxm/8e21c0d6-27b9-4ef5-b430-74dc2f686696/Screen_Shot_2022-02-11_at_17.08.06.png", "frame2": "https://replicate.delivery/mgxm/8e0bea7e-e6fc-4923-a9bc-3af357c78479/Screen_Shot_2022-02-11_at_17.07.57.png", "times_to_interpolate": "7" }, "logs": "Interpolated frames generated, saving now as output video.", "metrics": { "predict_time": 133.457729, "total_time": 133.644434 }, "output": [ { "file": "https://replicate.delivery/mgxm/beeea271-5840-474d-a40a-5155f4be26dd/out.mp4" } ], "started_at": "2022-02-12T01:10:10.256169Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/t6hpx4ci4jc7flikqferxbjj24", "cancel": "https://api.replicate.com/v1/predictions/t6hpx4ci4jc7flikqferxbjj24/cancel" }, "version": "b32da6e382a155169388ca9046bae303398b4db21ec8ee0ada832bb9c8d48481" }Generated inInterpolated frames generated, saving now as output video.Prediction
google-research/frame-interpolation:b32da6e382a155169388ca9046bae303398b4db21ec8ee0ada832bb9c8d48481IDzx6jhp2ljvbinc4ypptp4xhf3uStatusSucceededSourceWebHardware–Total durationCreatedInput
- frame1
- frame2
- times_to_interpolate
- "7"
{ "frame1": "https://replicate.delivery/mgxm/3f12c7d1-46b3-43c8-bc16-9d2c30119bf1/neutral.png", "frame2": "https://replicate.delivery/mgxm/1fc4e037-66b0-44a1-9c32-9290a66b0b67/smile.png", "times_to_interpolate": "7" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run google-research/frame-interpolation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "google-research/frame-interpolation:b32da6e382a155169388ca9046bae303398b4db21ec8ee0ada832bb9c8d48481", { input: { frame1: "https://replicate.delivery/mgxm/3f12c7d1-46b3-43c8-bc16-9d2c30119bf1/neutral.png", frame2: "https://replicate.delivery/mgxm/1fc4e037-66b0-44a1-9c32-9290a66b0b67/smile.png", times_to_interpolate: "7" } } ); console.log(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 google-research/frame-interpolation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "google-research/frame-interpolation:b32da6e382a155169388ca9046bae303398b4db21ec8ee0ada832bb9c8d48481", input={ "frame1": "https://replicate.delivery/mgxm/3f12c7d1-46b3-43c8-bc16-9d2c30119bf1/neutral.png", "frame2": "https://replicate.delivery/mgxm/1fc4e037-66b0-44a1-9c32-9290a66b0b67/smile.png", "times_to_interpolate": "7" } ) # The google-research/frame-interpolation model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/google-research/frame-interpolation/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run google-research/frame-interpolation 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": "b32da6e382a155169388ca9046bae303398b4db21ec8ee0ada832bb9c8d48481", "input": { "frame1": "https://replicate.delivery/mgxm/3f12c7d1-46b3-43c8-bc16-9d2c30119bf1/neutral.png", "frame2": "https://replicate.delivery/mgxm/1fc4e037-66b0-44a1-9c32-9290a66b0b67/smile.png", "times_to_interpolate": "7" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-02-12T01:44:24.631800Z", "created_at": "2022-02-12T01:44:13.991771Z", "data_removed": false, "error": null, "id": "zx6jhp2ljvbinc4ypptp4xhf3u", "input": { "frame1": "https://replicate.delivery/mgxm/3f12c7d1-46b3-43c8-bc16-9d2c30119bf1/neutral.png", "frame2": "https://replicate.delivery/mgxm/1fc4e037-66b0-44a1-9c32-9290a66b0b67/smile.png", "times_to_interpolate": "7" }, "logs": "Interpolated frames generated, saving now as output video.", "metrics": { "predict_time": 10.460043, "total_time": 10.640029 }, "output": [ { "file": "https://replicate.delivery/mgxm/d0210404-1f80-4e8f-a4c0-031ef8af8677/out.mp4" } ], "started_at": "2022-02-12T01:44:14.171757Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zx6jhp2ljvbinc4ypptp4xhf3u", "cancel": "https://api.replicate.com/v1/predictions/zx6jhp2ljvbinc4ypptp4xhf3u/cancel" }, "version": "b32da6e382a155169388ca9046bae303398b4db21ec8ee0ada832bb9c8d48481" }Generated inInterpolated frames generated, saving now as output video.Prediction
google-research/frame-interpolation:53bc438f5d487596d7e25dd783c617224c9fb6a0f5fd9cee0370d22c60de8394Input
- frame1
- frame2
- times_to_interpolate
- "1"
{ "frame1": "https://replicate.delivery/mgxm/9cb24682-2872-42f8-bc32-54e9225f18e3/one.png", "frame2": "https://replicate.delivery/mgxm/90435fb7-2339-4f94-ade4-492956d9d9de/two.png", "times_to_interpolate": "1" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run google-research/frame-interpolation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "google-research/frame-interpolation:53bc438f5d487596d7e25dd783c617224c9fb6a0f5fd9cee0370d22c60de8394", { input: { frame1: "https://replicate.delivery/mgxm/9cb24682-2872-42f8-bc32-54e9225f18e3/one.png", frame2: "https://replicate.delivery/mgxm/90435fb7-2339-4f94-ade4-492956d9d9de/two.png", times_to_interpolate: "1" } } ); console.log(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 google-research/frame-interpolation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "google-research/frame-interpolation:53bc438f5d487596d7e25dd783c617224c9fb6a0f5fd9cee0370d22c60de8394", input={ "frame1": "https://replicate.delivery/mgxm/9cb24682-2872-42f8-bc32-54e9225f18e3/one.png", "frame2": "https://replicate.delivery/mgxm/90435fb7-2339-4f94-ade4-492956d9d9de/two.png", "times_to_interpolate": "1" } ) # The google-research/frame-interpolation model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/google-research/frame-interpolation/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run google-research/frame-interpolation 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": "53bc438f5d487596d7e25dd783c617224c9fb6a0f5fd9cee0370d22c60de8394", "input": { "frame1": "https://replicate.delivery/mgxm/9cb24682-2872-42f8-bc32-54e9225f18e3/one.png", "frame2": "https://replicate.delivery/mgxm/90435fb7-2339-4f94-ade4-492956d9d9de/two.png", "times_to_interpolate": "1" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-02-12T17:37:43.660343Z", "created_at": "2022-02-12T17:37:40.173651Z", "data_removed": false, "error": null, "id": "4qlmymgpencp5jovfmsd7tzqrm", "input": { "frame1": "https://replicate.delivery/mgxm/9cb24682-2872-42f8-bc32-54e9225f18e3/one.png", "frame2": "https://replicate.delivery/mgxm/90435fb7-2339-4f94-ade4-492956d9d9de/two.png", "times_to_interpolate": "1" }, "logs": null, "metrics": { "predict_time": 3.158709, "total_time": 3.486692 }, "output": [ { "file": "https://replicate.delivery/mgxm/0ef892f4-fe04-412f-9739-0a5a4ae95b40/out.png" } ], "started_at": "2022-02-12T17:37:40.501634Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4qlmymgpencp5jovfmsd7tzqrm", "cancel": "https://api.replicate.com/v1/predictions/4qlmymgpencp5jovfmsd7tzqrm/cancel" }, "version": "53bc438f5d487596d7e25dd783c617224c9fb6a0f5fd9cee0370d22c60de8394" }Generated inPrediction
google-research/frame-interpolation:53bc438f5d487596d7e25dd783c617224c9fb6a0f5fd9cee0370d22c60de8394IDs2x3romnsnhohnb5fdcinnv3aeStatusSucceededSourceWebHardware–Total durationCreatedInput
- frame1
- frame2
- times_to_interpolate
- "7"
{ "frame1": "https://replicate.delivery/mgxm/5de85319-a354-4178-a2b0-aab4a65fa480/start.png", "frame2": "https://replicate.delivery/mgxm/aebabf54-c730-4efe-857d-1182960918d4/end.png", "times_to_interpolate": "7" }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run google-research/frame-interpolation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "google-research/frame-interpolation:53bc438f5d487596d7e25dd783c617224c9fb6a0f5fd9cee0370d22c60de8394", { input: { frame1: "https://replicate.delivery/mgxm/5de85319-a354-4178-a2b0-aab4a65fa480/start.png", frame2: "https://replicate.delivery/mgxm/aebabf54-c730-4efe-857d-1182960918d4/end.png", times_to_interpolate: "7" } } ); console.log(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 google-research/frame-interpolation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "google-research/frame-interpolation:53bc438f5d487596d7e25dd783c617224c9fb6a0f5fd9cee0370d22c60de8394", input={ "frame1": "https://replicate.delivery/mgxm/5de85319-a354-4178-a2b0-aab4a65fa480/start.png", "frame2": "https://replicate.delivery/mgxm/aebabf54-c730-4efe-857d-1182960918d4/end.png", "times_to_interpolate": "7" } ) # The google-research/frame-interpolation model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/google-research/frame-interpolation/api#output-schema print(item)To learn more, take a look at the guide on getting started with Python.
Run google-research/frame-interpolation 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": "53bc438f5d487596d7e25dd783c617224c9fb6a0f5fd9cee0370d22c60de8394", "input": { "frame1": "https://replicate.delivery/mgxm/5de85319-a354-4178-a2b0-aab4a65fa480/start.png", "frame2": "https://replicate.delivery/mgxm/aebabf54-c730-4efe-857d-1182960918d4/end.png", "times_to_interpolate": "7" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-02-13T17:21:32Z", "created_at": "2022-02-13T17:19:37.025009Z", "data_removed": false, "error": "", "id": "s2x3romnsnhohnb5fdcinnv3ae", "input": { "frame1": "https://replicate.delivery/mgxm/5de85319-a354-4178-a2b0-aab4a65fa480/start.png", "frame2": "https://replicate.delivery/mgxm/aebabf54-c730-4efe-857d-1182960918d4/end.png", "times_to_interpolate": "7" }, "logs": "2022-02-13 17:20:45.241662: I tensorflow/stream_executor/cuda/cuda_dnn.cc:368] Loaded cuDNN version 8101\r\nInterpolated frames generated, saving now as output video.", "metrics": { "predict_time": 50, "total_time": 114.974991 }, "output": [ { "file": "https://replicate.delivery/mgxm/e2e879b9-5c2d-4a2f-ba2d-2bc651dfecf3/out.mp4" } ], "started_at": "2022-02-13T17:20:42Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/s2x3romnsnhohnb5fdcinnv3ae", "cancel": "https://api.replicate.com/v1/predictions/s2x3romnsnhohnb5fdcinnv3ae/cancel" }, "version": "53bc438f5d487596d7e25dd783c617224c9fb6a0f5fd9cee0370d22c60de8394" }Generated in2022-02-13 17:20:45.241662: I tensorflow/stream_executor/cuda/cuda_dnn.cc:368] Loaded cuDNN version 8101 Interpolated frames generated, saving now as output video.
Want to make some of these yourself?
Run this model