auto zoom

Short-form punch-ins on talking video: the picture jumps closer on sentence starts and pauses and settles back, cycling a few framings, with an even rhythm over stretches without words. Planned from the words the clip carries (dialogue on the video, else the narration under it, never lyrics); a clip with no words gets the rhythm alone. moments_seconds with clip_id punches on given clip-relative seconds instead; beats_of punches on the stored beats of a music clip on the timeline. One clip, or every video clip on the timeline. A punch holds on the face where the clip’s subject has been read in the cloud (auto_reframe reads it); otherwise it keeps the framing and favours the top of the frame. Writes the scale and position keyframe tracks, replacing what they held. Free.

POST

/

tools

/

auto_zoom

auto zoom

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

import requests

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

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_zoom', 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,
      "queued_minutes": 123,
      "left_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,
      "queued_minutes": 123,
      "left_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 key's own.

Body

application/json

timeline_id

string

required

The timeline id.

clip_id

string

The video clip to punch. Absent: every video clip that carries words.

intensity

enum<string>

How often and how close: light about one punch per 8s at 112%, medium per 5s cycling 115% and 130% (default), strong per 3s up to 145%.

Available options:

light,

medium,

strong

moments_seconds

number[]

Clip-relative seconds to punch on instead of reading the words: beats, key lines. Spacing and edge rules still apply.

beats_of

string

A music clip on this timeline: punch on its stored beats (detect_beats), mapped through its trim, speed and placement onto every target clip. Spacing and edge rules still apply.

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).

ok

any

required

data

object

required

meta

object

required

Show child attributes

media

object[]

auto zoom

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

import requests

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

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_zoom', 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,
      "queued_minutes": 123,
      "left_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,
      "queued_minutes": 123,
      "left_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  }
}