Enterprise: Video to Video Endpoint

• text2video
• image2video
• video2video
• fetchvideo
• clear_cache
• restart_server
• system details
• open-sora
• update server
• v6/scenecreator

Overview

Video to Video endpoint allows you to generates video from an existing video

The resolution of the output is 1024x576

caution

Make sure you add your s3 details for video server, so you can receive image generated in your bucket. Images generated without s3 details being added will be delete after 24 hours

Request

--request POST 'https://modelslab.com/api/v1/enterprise/video/video2video' \

Make a POST request to https://modelslab.com/api/v1/enterprise/video/video2video endpoint and pass the required parameters in the request body.

Body Attributes

Parameter	Description
key	Your API Key used for request authorization.
model_id	The ID of the model to use. The available model includes dark-sushi-mix ,epicrealismnaturalsi,hellonijicute25d
negative_prompt	Items you don't want in the video.
seed	Seed is used to reproduce results, same seed will give you same image in return again. Pass null for a random number.
height	Max height: 768px.
width	Max width: 768px.
init_video	Link equivalent of a valid mp4 of gif file to use as initial video conditioning.
num_frames	Number of frames in generated video. Max: 25. Defaults to 16.
num_inference_steps	Number of denoising steps. Max: 50. Defaults to 20.
guidance_scale	Scale for classifier-free guidance.
clip_skip	Number of CLIP layers to skip. 2 leads to more aesthetic defaults. Defauls to null.
strength	Amount of variation you want between original video and final video. Higher values lead to more variation. Must be between 0 and 1. Defaults to 0.7.
output_type	The output type could be mp4,gif.
fps	Frames per second rate of generated video.
lora_models	lora models to be used with the model id - default=null
lora_strength	comma separated lora strengths - default=1.0
motion_loras	motion lora models to be used with the model id - default=null
motion_lora_strength	comma separated motion lora strengths - default=1.0
domain_lora_scale	animate diff v3 scale - default=1.0
adapter_lora	motion model lora for v3 - default is v2_sd15_adapter
upscale_height	height upscaling while inference - default=None max=1024
upscale_width	width upscaling while inference - default=None max=1024
upscale_strength	upscaling strength - default is 0.6 maximum is 1
upscale_guidance_scale	upscaling guidance scale - default is 15.0
upscale_num_inference_steps	num inference steps for upscaling - default is 20
motion_module	motion models - default is v2_sd15_mm. Other options include animatelcm,v2_sd15_mm,animateDiff-lightning
instant_response	true if you'd like a response with future links for queued requests instantly instead of waiting for a fixed amount of time. Defaults to false.
temp	true if you want to store your generations on our temporary storage. Temporary files are cleaned every 24 hours. Defaults to false.
webhook	Set an URL to get a POST API call once the image generation is complete.
track_id	This ID is returned in the response to the webhook API call. This will be used to identify the webhook request.

Example

Body

Body

{
    "key":"",
    "model_id":"dark-sushi-mix",
    "prompt":"fox playing ukulele on a boat floating on magma flowing under the boat",
    "negative_prompt":"low quality",
    "init_video":"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatediff-vid2vid-output-1.gif",
    "clip_skip":2,
    "num_inference_steps":40,
    "use_improved_sampling": false,
    "guidance_scale":9.5,
    "strength":0.8,
    "base64":false,
    "webhook":null,
    "track_id": null
}

Request

JS

var myHeaders = new Headers();
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
     "key":"",
    "model_id":"dark-sushi-mix",
    "prompt":"fox playing ukulele on a boat floating on magma flowing under the boat",
    "negative_prompt":"low quality",
    "init_video":"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatediff-vid2vid-output-1.gif",
    "clip_skip":2,
    "num_inference_steps":40,
    "use_improved_sampling": false,
    "guidance_scale":9.5,
    "strength":0.8,
    "base64":false,
    "webhook":null,
    "track_id": null
});

var requestOptions = {
  method: 'POST',
  headers: myHeaders,
  body: raw,
  redirect: 'follow'
};

fetch("https://modelslab.com/api/v1/enterprise/video/video2video", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

PHP

<?php

$payload = [
    "key" =>"",
    "model_id" => "dark-sushi-mix",
    "prompt" => "fox playing ukulele on a boat floating on magma flowing under the boat",
    "negative_prompt" => "low quality",
    "init_video" => "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatediff-vid2vid-output-1.gif",
    "clip_skip"=> 2,
    "num_inference_steps" => 40,
    "use_improved_sampling" => false,
    "guidance_scale" =>9.5,
    "strength" => 0.8,
    "base64" => false,
    "webhook" => null,
    "track_id" => null
];

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://modelslab.com/api/v1/enterprise/video/video2video',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS => json_encode($payload),
  CURLOPT_HTTPHEADER => array(
    'Content-Type: application/json'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

NODE

var request = require('request');
var options = {
  'method': 'POST',
  'url': 'https://modelslab.com/api/v1/enterprise/video/video2video',
  'headers': {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
     "key":"",
    "model_id":"dark-sushi-mix",
    "prompt":"fox playing ukulele on a boat floating on magma flowing under the boat",
    "negative_prompt":"low quality",
    "init_video":"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatediff-vid2vid-output-1.gif",
    "clip_skip":2,
    "num_inference_steps":40,
    "use_improved_sampling": false,
    "guidance_scale":9.5,
    "strength":0.8,
    "base64":false,
    "webhook":null,
    "track_id": null
  })
};

request(options, function (error, response) {
  if (error) throw new Error(error);
  console.log(response.body);
});

PYTHON

import requests
import json

url = "https://modelslab.com/api/v1/enterprise/video/video2video"

payload = json.dumps({
   "key":"",
    "model_id":"dark-sushi-mix",
    "prompt":"fox playing ukulele on a boat floating on magma flowing under the boat",
    "negative_prompt":"low quality",
    "init_video":"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatediff-vid2vid-output-1.gif",
    "clip_skip":2,
    "num_inference_steps":40,
    "use_improved_sampling": false,
    "guidance_scale":9.5,
    "strength":0.8,
    "base64":false,
    "webhook":None,
    "track_id":None
})

headers = {
  'Content-Type': 'application/json'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

JAVA

OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{\n    \"key\":\"\",\n    \"model_id\":\"dark-sushi-mix\",\n    \"prompt\":\"fox playing ukulele on a boat floating on magma flowing under the boat\",\n    \"negative_prompt\":\"low quality\",\n    \"init_video\":\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatediff-vid2vid-output-1.gif\",\n    \"clip_skip\":2,\n    \"num_inference_steps\":40,\n    \"use_improved_sampling\": false,\n    \"guidance_scale\":9.5,\n    \"strength\":0.8,\n    \"base64\":false,\n    \"webhook\": null,\n    \"track_id\": null\n}");
Request request = new Request.Builder()
  .url("https://modelslab.com/api/v1/enterprise/video/video2video")
  .method("POST", body)
  .addHeader("Content-Type", "application/json")
  .build();
Response response = client.newCall(request).execute();

Response

Example Response

{
    "status": "success",
    "generationTime": 8.49,
    "id": 500,
    "output": [
        "https://pub-3626123a908346a7a8be8d9295f44e26.r2.dev/generations/05ffff8d-a0ba-4019-9df0-5de966c52ad5.gif"
    ],
    "proxy_links": [
        "https://cdn2.stablediffusionapi.com/generations/05ffff8d-a0ba-4019-9df0-5de966c52ad5.gif"
    ],
    "meta": {
        "base64": "no",
        "clip_skip": null,
        "file_prefix": "05ffff8d-a0ba-4019-9df0-5de966c52ad5",
        "fps": 7,
        "guidance_scale": 7,
        "height": 512,
        "init_video": "https://pub-3626123a908346a7a8be8d9295f44e26.r2.dev/generations/af5057ce-2a53-4d8f-bdb7-f0e5a6d4064c.mp4",
        "instant_response": "no",
        "model_id": "midjourney",
        "negative_prompt": "low quality",
        "num_frames": 16,
        "num_inference_steps": 20,
        "output_type": "gif",
        "prompt": "An astronaut riding a horse",
        "seed": 3276424082,
        "strength": 0.7,
        "temp": "no",
        "width": 512
    }
}