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google-research /frame-interpolation:4f88a16a
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
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:4f88a16a13673a8b589c18866e540556170a5bcb2ccdc12de556e800e9456d3d",
{
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.
pip install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run 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:4f88a16a13673a8b589c18866e540556170a5bcb2ccdc12de556e800e9456d3d",
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
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
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": "4f88a16a13673a8b589c18866e540556170a5bcb2ccdc12de556e800e9456d3d",
"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/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/google-research/frame-interpolation@sha256:4f88a16a13673a8b589c18866e540556170a5bcb2ccdc12de556e800e9456d3d \
-i 'frame1="https://replicate.delivery/mgxm/5de85319-a354-4178-a2b0-aab4a65fa480/start.png"' \
-i 'frame2="https://replicate.delivery/mgxm/aebabf54-c730-4efe-857d-1182960918d4/end.png"' \
-i 'times_to_interpolate=7'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/google-research/frame-interpolation@sha256:4f88a16a13673a8b589c18866e540556170a5bcb2ccdc12de556e800e9456d3d
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "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 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
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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"
}
2022-02-13 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.
This example was created by a different version, google-research/frame-interpolation:53bc438f.