POST
javascript
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 const axios = require('axios'); const fs = require('fs'); const path = require('path'); async function toB64(imgPath) { const data = fs.readFileSync(path.resolve(imgPath)); return Buffer.from(data).toString('base64'); } const api_key = "YOUR API-KEY"; const url = "https://api.segmind.com/v1/v-express"; const data = { "input_image": "toB64('https://segmind-sd-models.s3.amazonaws.com/display_images/v_express/v-express-ip.jpg')", "input_audio": "https://segmind-sd-models.s3.amazonaws.com/display_images/v_express/v_express_audio.mp3", "fps": 30, "num_inference_steps": 20, "guidance_scale": 2, "retarget_strategy": "fix_face", "base64": false }; (async function() { try { const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } }); console.log(response.data); } catch (error) { console.error('Error:', error.response.data); } })();
RESPONSE
image/jpeg
HTTP Response Codes
200 - OKImage Generated
401 - UnauthorizedUser authentication failed
404 - Not FoundThe requested URL does not exist
405 - Method Not AllowedThe requested HTTP method is not allowed
406 - Not AcceptableNot enough credits
500 - Server ErrorServer had some issue with processing

Attributes


input_imageimage *

Input image of a talking-head.


input_audiostr *

Input audio file. Avoid special symbol in the filename as it may cause ffmpeg erros.


fpsint ( default: 30 ) Affects Pricing

Output frames per second.

min : 10,

max : 60


num_inference_stepsint ( default: 20 ) Affects Pricing

Number of steps to generate.

min : 5,

max : 50


guidance_scaleint ( default: 2 ) Affects Pricing

Scale for classifier-free guidance

min : 1,

max : 15


retarget_strategystr ( default: fix_face ) Affects Pricing

Retarget Strategy.


base64boolean ( default: 1 )

Base64 encoding of the output image.

To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.

V-Express

The V-Express model is a groundbreaking advancement in the realm of portrait video generation. It combines deep learning techniques with progressive training and conditional dropout operations. V-Express leverages generative models to create portrait videos from single images. It takes into account pose, input image, and audio, resulting in emotionally resonant videos. V-Express addresses the challenge of balancing different control signals. Whether it’s text, audio, pose, or image reference, V-Express ensures that weaker conditions contribute effectively to the final output.

Applications of V-Express

  • Content Creation: Writers, filmmakers, and artists can harness V-Express to craft moving narratives. Imagine generating heartfelt monologues or poignant dialogues effortlessly.

  • Chatbots with Empathy: Mental health chatbots powered by V-Express can empathize with users. When words alone aren’t enough, V-Express bridges the gap.

  • Character Animation: Game designers and animators can breathe life into characters. V-Express infuses emotions into their expressions, making them relatable.

  • Music Videos: V-Express isn’t limited to faces. It can create soul-stirring music videos, syncing lyrics with visuals.