Prediction

Model

lucataco/real-esrgan-video:c2376823

b76kwvlbq3l5gumj7zdsa24e6i

Status

Succeeded

Source

Web

Hardware

A100 (40GB)

Total duration

25.0s

Created

about 2 years ago

Webhook

–

Input

video_path: https://replicate.delivery/pbxt/JvzJwGbiuwhpRVTBdOOt3L49WAsYlBmB2yNqcyxeIlTRQ5xl/replicate-prediction-wkusuc3brp5hwd27zaymz5rgdi.mp4
resolution: FHD
model: RealESRGAN_x4plus

{
  "model": "RealESRGAN_x4plus",
  "resolution": "FHD",
  "video_path": "https://replicate.delivery/pbxt/JvzJwGbiuwhpRVTBdOOt3L49WAsYlBmB2yNqcyxeIlTRQ5xl/replicate-prediction-wkusuc3brp5hwd27zaymz5rgdi.mp4"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_SRT**********************************

This is your API token. Keep it to yourself.

Import 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 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"
    }
  }
);

// 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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_SRT**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run 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"
    }
)

# 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.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_SRT**********************************

This is your API token. Keep it to yourself.

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": "lucataco/real-esrgan-video:c23768236472c41b7a121ee735c8073e29080c01b32907740cfada61bff75320",
    "input": {
      "model": "RealESRGAN_x4plus",
      "resolution": "FHD",
      "video_path": "https://replicate.delivery/pbxt/JvzJwGbiuwhpRVTBdOOt3L49WAsYlBmB2yNqcyxeIlTRQ5xl/replicate-prediction-wkusuc3brp5hwd27zaymz5rgdi.mp4"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "id": "b76kwvlbq3l5gumj7zdsa24e6i",
  "model": "lucataco/real-esrgan-video",
  "version": "c23768236472c41b7a121ee735c8073e29080c01b32907740cfada61bff75320",
  "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",
  "output": "https://replicate.delivery/pbxt/PpWmE8IEmDppOZiqAOhr22BZfm7ZNNkC0Zq8iXohdKvdK19IA/tmp84vybs1breplicate-prediction-wkusuc3brp5hwd27zaymz5rgdi_out.mp4",
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2023-11-24T19:01:54.394895Z",
  "started_at": "2023-11-24T19:01:54.411075Z",
  "completed_at": "2023-11-24T19:02:19.363909Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/b76kwvlbq3l5gumj7zdsa24e6i/cancel",
    "get": "https://api.replicate.com/v1/predictions/b76kwvlbq3l5gumj7zdsa24e6i"
  },
  "metrics": {
    "predict_time": 24.952834,
    "total_time": 24.969014
  }
}

Generated in

25.0 seconds

Tweak it Report

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