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lucataco /real-esrgan-video:c2376823
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=lucataco/real-esrgan-video
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run lucataco/real-esrgan-video using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"lucataco/real-esrgan-video:c23768236472c41b7a121ee735c8073e29080c01b32907740cfada61bff75320",
{
input: {
model: "RealESRGAN_x4plus",
resolution: "FHD",
video_path: "https://replicate.delivery/pbxt/JvzJwGbiuwhpRVTBdOOt3L49WAsYlBmB2yNqcyxeIlTRQ5xl/replicate-prediction-wkusuc3brp5hwd27zaymz5rgdi.mp4"
}
}
);
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 replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun lucataco/real-esrgan-video using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"lucataco/real-esrgan-video:c23768236472c41b7a121ee735c8073e29080c01b32907740cfada61bff75320",
input={
"model": "RealESRGAN_x4plus",
"resolution": "FHD",
"video_path": "https://replicate.delivery/pbxt/JvzJwGbiuwhpRVTBdOOt3L49WAsYlBmB2yNqcyxeIlTRQ5xl/replicate-prediction-wkusuc3brp5hwd27zaymz5rgdi.mp4"
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run lucataco/real-esrgan-video 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": "c23768236472c41b7a121ee735c8073e29080c01b32907740cfada61bff75320",
"input": {
"model": "RealESRGAN_x4plus",
"resolution": "FHD",
"video_path": "https://replicate.delivery/pbxt/JvzJwGbiuwhpRVTBdOOt3L49WAsYlBmB2yNqcyxeIlTRQ5xl/replicate-prediction-wkusuc3brp5hwd27zaymz5rgdi.mp4"
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
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Output
{
"completed_at": "2023-11-24T19:02:19.363909Z",
"created_at": "2023-11-24T19:01:54.394895Z",
"data_removed": false,
"error": null,
"id": "b76kwvlbq3l5gumj7zdsa24e6i",
"input": {
"model": "RealESRGAN_x4plus",
"resolution": "FHD",
"video_path": "https://replicate.delivery/pbxt/JvzJwGbiuwhpRVTBdOOt3L49WAsYlBmB2yNqcyxeIlTRQ5xl/replicate-prediction-wkusuc3brp5hwd27zaymz5rgdi.mp4"
},
"logs": "Upscaling from 1024x512 to 1920x1080, crop_to_fit=True\n/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/torchvision/transforms/functional_tensor.py:5: UserWarning: The torchvision.transforms.functional_tensor module is deprecated in 0.15 and will be **removed in 0.17**. Please don't rely on it. You probably just need to use APIs in torchvision.transforms.functional or in torchvision.transforms.v2.functional.\nwarnings.warn(\ninference: 0%| | 0/25 [00:00<?, ?frame/s]\ninference: 4%|▍ | 1/25 [00:01<00:47, 1.96s/frame]\ninference: 8%|▊ | 2/25 [00:02<00:26, 1.16s/frame]\ninference: 12%|█▏ | 3/25 [00:03<00:19, 1.10frame/s]\ninference: 16%|█▌ | 4/25 [00:03<00:16, 1.27frame/s]\ninference: 20%|██ | 5/25 [00:04<00:14, 1.39frame/s]\ninference: 24%|██▍ | 6/25 [00:04<00:12, 1.47frame/s]\ninference: 28%|██▊ | 7/25 [00:05<00:11, 1.53frame/s]\ninference: 32%|███▏ | 8/25 [00:06<00:10, 1.57frame/s]\ninference: 36%|███▌ | 9/25 [00:06<00:10, 1.60frame/s]\ninference: 40%|████ | 10/25 [00:07<00:09, 1.62frame/s]\ninference: 44%|████▍ | 11/25 [00:07<00:08, 1.64frame/s]\ninference: 48%|████▊ | 12/25 [00:08<00:07, 1.64frame/s]\ninference: 52%|█████▏ | 13/25 [00:09<00:07, 1.65frame/s]\ninference: 56%|█████▌ | 14/25 [00:09<00:06, 1.66frame/s]\ninference: 60%|██████ | 15/25 [00:10<00:06, 1.66frame/s]\ninference: 64%|██████▍ | 16/25 [00:10<00:05, 1.67frame/s]\ninference: 68%|██████▊ | 17/25 [00:11<00:04, 1.66frame/s]\ninference: 72%|███████▏ | 18/25 [00:12<00:04, 1.66frame/s]\ninference: 76%|███████▌ | 19/25 [00:12<00:03, 1.67frame/s]\ninference: 80%|████████ | 20/25 [00:13<00:03, 1.66frame/s]\ninference: 84%|████████▍ | 21/25 [00:13<00:02, 1.66frame/s]\ninference: 88%|████████▊ | 22/25 [00:14<00:01, 1.67frame/s]\ninference: 92%|█████████▏| 23/25 [00:15<00:01, 1.67frame/s]\ninference: 96%|█████████▌| 24/25 [00:15<00:00, 1.67frame/s]\ninference: 100%|██████████| 25/25 [00:16<00:00, 1.67frame/s]\ninference: 100%|██████████| 25/25 [00:17<00:00, 1.46frame/s]\n[h264 @ 0x564bdc2f31c0] Cannot load libnvcuvid.so.1\n[h264 @ 0x564bdc2f31c0] Failed loading nvcuvid.\n[h264 @ 0x564bdc2f31c0] Failed setup for format cuda: hwaccel initialisation returned error.\nCropping to fit done..\nUpscaled video saved to: /src/ouput/tmp84vybs1breplicate-prediction-wkusuc3brp5hwd27zaymz5rgdi_upscaled_1920_1080.mp4",
"metrics": {
"predict_time": 24.952834,
"total_time": 24.969014
},
"output": "https://replicate.delivery/pbxt/PpWmE8IEmDppOZiqAOhr22BZfm7ZNNkC0Zq8iXohdKvdK19IA/tmp84vybs1breplicate-prediction-wkusuc3brp5hwd27zaymz5rgdi_out.mp4",
"started_at": "2023-11-24T19:01:54.411075Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/b76kwvlbq3l5gumj7zdsa24e6i",
"cancel": "https://api.replicate.com/v1/predictions/b76kwvlbq3l5gumj7zdsa24e6i/cancel"
},
"version": "c23768236472c41b7a121ee735c8073e29080c01b32907740cfada61bff75320"
}Generated in
Upscaling from 1024x512 to 1920x1080, crop_to_fit=True
/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/torchvision/transforms/functional_tensor.py:5: UserWarning: The torchvision.transforms.functional_tensor module is deprecated in 0.15 and will be **removed in 0.17**. Please don't rely on it. You probably just need to use APIs in torchvision.transforms.functional or in torchvision.transforms.v2.functional.
warnings.warn(
inference: 0%| | 0/25 [00:00<?, ?frame/s]
inference: 4%|▍ | 1/25 [00:01<00:47, 1.96s/frame]
inference: 8%|▊ | 2/25 [00:02<00:26, 1.16s/frame]
inference: 12%|█▏ | 3/25 [00:03<00:19, 1.10frame/s]
inference: 16%|█▌ | 4/25 [00:03<00:16, 1.27frame/s]
inference: 20%|██ | 5/25 [00:04<00:14, 1.39frame/s]
inference: 24%|██▍ | 6/25 [00:04<00:12, 1.47frame/s]
inference: 28%|██▊ | 7/25 [00:05<00:11, 1.53frame/s]
inference: 32%|███▏ | 8/25 [00:06<00:10, 1.57frame/s]
inference: 36%|███▌ | 9/25 [00:06<00:10, 1.60frame/s]
inference: 40%|████ | 10/25 [00:07<00:09, 1.62frame/s]
inference: 44%|████▍ | 11/25 [00:07<00:08, 1.64frame/s]
inference: 48%|████▊ | 12/25 [00:08<00:07, 1.64frame/s]
inference: 52%|█████▏ | 13/25 [00:09<00:07, 1.65frame/s]
inference: 56%|█████▌ | 14/25 [00:09<00:06, 1.66frame/s]
inference: 60%|██████ | 15/25 [00:10<00:06, 1.66frame/s]
inference: 64%|██████▍ | 16/25 [00:10<00:05, 1.67frame/s]
inference: 68%|██████▊ | 17/25 [00:11<00:04, 1.66frame/s]
inference: 72%|███████▏ | 18/25 [00:12<00:04, 1.66frame/s]
inference: 76%|███████▌ | 19/25 [00:12<00:03, 1.67frame/s]
inference: 80%|████████ | 20/25 [00:13<00:03, 1.66frame/s]
inference: 84%|████████▍ | 21/25 [00:13<00:02, 1.66frame/s]
inference: 88%|████████▊ | 22/25 [00:14<00:01, 1.67frame/s]
inference: 92%|█████████▏| 23/25 [00:15<00:01, 1.67frame/s]
inference: 96%|█████████▌| 24/25 [00:15<00:00, 1.67frame/s]
inference: 100%|██████████| 25/25 [00:16<00:00, 1.67frame/s]
inference: 100%|██████████| 25/25 [00:17<00:00, 1.46frame/s]
[h264 @ 0x564bdc2f31c0] Cannot load libnvcuvid.so.1
[h264 @ 0x564bdc2f31c0] Failed loading nvcuvid.
[h264 @ 0x564bdc2f31c0] Failed setup for format cuda: hwaccel initialisation returned error.
Cropping to fit done..
Upscaled video saved to: /src/ouput/tmp84vybs1breplicate-prediction-wkusuc3brp5hwd27zaymz5rgdi_upscaled_1920_1080.mp4