auto reframe

Choose what a clip shows when its picture does not match the box it fills (a 16:9 shot on a 9:16 timeline is centre-cropped by default); a video in another shape is a timeline at that shape (manage_timelines create with aspect_ratio and the clip), then this. view shows one area of the source for the whole clip. Otherwise the crop follows the person, or the largest thing in shot with subject any, cutting rather than panning, each shot framed on its own, centred where nobody is in it; with clip_id the answer carries check_timeline’s face-cut finding; two people hold on one, or with follow speaker cut to whoever is talking (needs speakers on the recording). A split-screen source is named in the answer and stacked with apply_layout, its clip_id in every slot. A picture that fits, or with nobody found, stays centred; framed says what was written on each clip. A subject not read yet is read in the background: the answer carries job_id, and the crop lands when it finishes (get_jobs). Writes the focus track only, so a punch-in and a camera move stack on it. A reframed cut also takes captions placed for the new shape and versions for other platforms. Reading a subject: cloud processing.

POST

tools

auto_reframe

auto reframe

curl --request POST \
  --url https://eversince.ai/api/v1/tools/auto_reframe \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "timeline_id": "<string>"
}
'

import requests

url = "https://eversince.ai/api/v1/tools/auto_reframe"

payload = { "timeline_id": "<string>" }
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({timeline_id: '<string>'})
};

fetch('https://eversince.ai/api/v1/tools/auto_reframe', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

{
  "ok": true,
  "data": {},
  "meta": {
    "request_id": "<string>",
    "cost": {},
    "cloud_processing": {
      "ran_on": "cloud",
      "minutes": 123,
      "charged_minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "held_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  },
  "media": [
    {}
  ]
}

{
  "ok": false,
  "error": {
    "code": "<string>",
    "message": "<string>",
    "retryable": true,
    "suggested_action": "<string>",
    "cloud_processing": {
      "ran_on": "cloud",
      "minutes": 123,
      "charged_minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "held_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  }
}

Authorizations

Authorization

string

header

required

An API key (es_live_…) from Settings, under API keys, or an OAuth access token.

Headers

Idempotency-Key

string

Retry a paid dispatch safely: the same key returns the job already dispatched instead of charging again.

x-workspace-id

string

The workspace this one call acts in, when it is not the default: for a key or a connected agent, one of the workspaces the user allowed it.

Body

application/json

timeline_id

string

required

The timeline id.

clip_id

string

The video clip to reframe. Absent: every video clip on the timeline.

clip_ids

string[]

Instead of clip_id: several video clips.

Required array length: 1 - 50 elements

view

object

Show one area of the source for the whole clip: its centre as fractions of the source (x 0 the source's left edge, y 0 its top; a larger x slides the picture left in the box) and, to zoom, its width as a fraction of the source width; no width shows as much as the box holds. Kept inside the picture, up to 5x. Needs clip_id (video or image). Replaces the clip's scale, pan and focus track.

Show child attributes

subject

enum<string>

What the crop follows: people (default; aimed at the head), or any: the largest thing detected when no person is in shot.

Available options:

person,

any

enum<string>

Where two people share the frame: speaker cuts the crop to whoever is talking, from a speaking-face read at a dozen of each voice's turns, once per recording. Needs speakers on the recording; where it cannot tell, the crop holds on one person and says which. On a split-screen source each person stays inside their own half, by the clip's scale and pan; a clip with scale or position keys keeps them.

Available options:

subject,

speaker

background

string

Show the whole picture instead of a crop: the clip fitted (a wide source as a centred band in a tall frame) over a blurred copy of itself that fills the frame, a silent clip on a layer below. Needs clip_id or clip_ids.

Allowed value: "blur"

if_revision

The revision get_timeline returned. A stale one fails with revision_conflict instead of applying; so does no revision once a user edited the timeline in the app since this connection last read it.

context

string

Optional: one sentence shown to the user beside this action.

Maximum string length: 600

Response

Done, or a job started for work that runs longer (follow it with get_jobs).

any

required

data

object

required

meta

object

required

Show child attributes

media

object[]

auto reframe

curl --request POST \
  --url https://eversince.ai/api/v1/tools/auto_reframe \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "timeline_id": "<string>"
}
'

import requests

url = "https://eversince.ai/api/v1/tools/auto_reframe"

payload = { "timeline_id": "<string>" }
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({timeline_id: '<string>'})
};

fetch('https://eversince.ai/api/v1/tools/auto_reframe', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

{
  "ok": true,
  "data": {},
  "meta": {
    "request_id": "<string>",
    "cost": {},
    "cloud_processing": {
      "ran_on": "cloud",
      "minutes": 123,
      "charged_minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "held_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  },
  "media": [
    {}
  ]
}

{
  "ok": false,
  "error": {
    "code": "<string>",
    "message": "<string>",
    "retryable": true,
    "suggested_action": "<string>",
    "cloud_processing": {
      "ran_on": "cloud",
      "minutes": 123,
      "charged_minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "held_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  }
}

Discovery

Timeline

Workspace

Library

Canvas

Generation

Research

Account

Models

Uploads

Webhooks

auto reframe

Authorizations

Headers

Body

Response