What platforms does each::labs support?

each::labs is available on Web App.

What are the limitations of each::labs?

No prompt or creative controls: the choreography and setting are locked to the template. Output quality depends heavily on the three source portraits being framing compatible. Usage based pricing has several tiers, so cost is not obvious before you run a request.

each::labs

Name: each::labs
Author: each::labs

Three portraits, one gas station dance clip

Beginner API

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Screenshot of each::labs, Three portraits, one gas station dance clip

What is each::labs?

each::labs is a change dress in video tool. A template based video model on each::labs that maps three person photos to fixed roles in a three shot gas station dance clip, with 480p, 720p or 1080p output. No prompt field: the supplied portraits and resolution are the only controls.

Gas Station Dance is a template model on each::labs that builds a short, choreographed dance video from three uploaded portraits. Each photo is mapped to a fixed role in a predetermined three shot sequence: the opening dancer, the person filming a selfie in the middle shot, and the person stepping out of a car in the closing shot. The output is a single rendered clip with the supplied faces standing in for the performers in the template. The workflow is deliberately narrow. You provide three retrievable image URLs, pick an output resolution of 480p, 720p or 1080p, and submit the request. There is no free text prompt field and no creative direction to give: the named parameters control everything, and an invented prompt will not substitute for a missing photo. Results return as video, typically within a few minutes (the page lists a p50 runtime around five minutes). Ordering matters, so image1, image2 and image3 should each be matched to the shot they are meant to fill. The tool suits creators producing personalised social clips, marketing teams testing which portraits work inside the template, and developers who need a repeatable video step inside a pipeline. It sits in the eachlabs family beside other template driven models such as Central Cee Clip Trend and Fan Wipe Fashion, and it can be invoked through the eachlabs prediction API rather than the browser playground for anyone wiring it into an application. Against general image to video generators, Gas Station Dance trades flexibility for speed and predictability. That makes it a poor fit for custom scenes or written direction, but a quick route when the shot is already decided and only the faces need swapping. Review the full clip rather than a thumbnail, checking identity, motion continuity, transitions and the ending before publishing.

How do you use each::labs?

1Gather three portrait photos
Pick one clear photo per role: the opening dancer, the selfie filer in the middle shot, and the person stepping out of the car at the end. Keep identity and appearance consistent across all three.
2Open the Gas Station Dance model page
Sign in to each::labs and load the model page in the playground to expose the image1, image2 and image3 input fields plus the resolution selector.
3Upload each photo to its matching slot
Place the dancer photo in image1, the selfie photo in image2 and the car exit photo in image3. Ordering is the only way to control casting, so check the mapping before running.
4Choose a resolution and run
Select 480p, 720p or 1080p depending on where the clip will be shown. Submit and wait for the render, which takes a few minutes.
5Review the full clip
Watch the whole video rather than a still: check face identity, motion continuity, the cut between shots and the ending. Adjust portrait choices and re-run if needed.
6Move to the API for repeat runs
For batch or pipeline work, read the API introduction and send the same three image URLs to the prediction endpoint with your key and settings recorded alongside the result.

Pros and cons

Pros

Three fixed shot roles make casting straightforward: opener, selfie filer, car exitAI
Output resolution is selectable at 480p, 720p or 1080p with a documented defaultAI
Accessible both through the eachlabs playground and a documented prediction APIAI
Sits alongside related templates (Central Cee Clip Trend, Fan Wipe Fashion) for quick style comparisonsAI
Runtime is short enough for iterative testing, listed around five minutes at p50AI

Cons

No prompt or creative controls: the choreography and setting are locked to the templateAI
Output quality depends heavily on the three source portraits being framing compatibleAI
Usage based pricing has several tiers, so cost is not obvious before you run a requestAI
Source image URLs must stay directly retrievable while the job processesAI
Face identity can drift across the shot changes and needs manual review of the whole clipAI

How much does each::labs cost?

Pricing

Usage based pricing with several tiers rather than a flat charge per video. The page notes that the full pricing reference should be checked for the chosen resolution and supplied references before estimating a batch, and there is no subscription.

Learn more

Integrations

Runs through the each::labs API using a bearer key against the prediction endpoint, with optional webhook delivery. The same platform also hosts image, video and audio models from other providers under one integration.

Learn more

Features

Three ordered portrait inputs (image1, image2, image3) each cast a different shot in a fixed gas station dance template. Resolution is the only adjustable setting, with 480p, 720p and 1080p options and a 480p default. Output is video, and there is no creative prompt field, so the choreography and framing stay constant while the faces change.

Frequently asked questions about each::labs

How much does each::labs cost?
Usage based pricing with several tiers rather than a flat charge per video. The page notes that the full pricing reference should be checked for the chosen resolution and supplied references before estimating a batch, and there is no subscription.
Does each::labs have an API?
Yes, each::labs offers an API.
How do you use each::labs?
The walkthrough on this page covers 6 steps: 1. Gather three portrait photos 2. Open the Gas Station Dance model page 3. Upload each photo to its matching slot 4. Choose a resolution and run 5. Review the full clip 6. Move to the API for repeat runs.
What platforms does each::labs support?
each::labs is available on Web App.
What does each::labs integrate with?
Runs through the each::labs API using a bearer key against the prediction endpoint, with optional webhook delivery. The same platform also hosts image, video and audio models from other providers under one integration.
What are the limitations of each::labs?
No prompt or creative controls: the choreography and setting are locked to the template. Output quality depends heavily on the three source portraits being framing compatible. Usage based pricing has several tiers, so cost is not obvious before you run a request.