SDR to HDR

Product ID: sdr_to_hdr · Billing: Beeble Cloud credits Reconstruct clipped highlights and crushed shadows while preserving well-exposed areas of the source. SDR to HDR uses SwitchHDR to recover detail for HDR grading and compositing. See the SDR to HDR product guide for highlight and shadow examples and the ACES finishing workflow.

Before you start

Create an API key for an organization with this product enabled.
Prepare your media as Beeble URIs, authorized CDN URLs, public/presigned HTTPS URLs, or base64 data URIs.
Select an available model below; complete any required consent in Beeble Cloud.

Models and inputs

Set BEEBLE_API_KEY and, for internal teams, BEEBLE_TEAM_ID.

curl --fail-with-body "https://api.beeble.ai/v1/products/sdr_to_hdr/models" \
  -H "x-api-key: $BEEBLE_API_KEY" \
  -H "X-Beeble-Team-Id: ${BEEBLE_TEAM_ID:-}"

import json
import os
import requests

headers = {"x-api-key": os.environ["BEEBLE_API_KEY"]}
if team_id := os.environ.get("BEEBLE_TEAM_ID"):
    headers["X-Beeble-Team-Id"] = team_id

response = requests.get(
    "https://api.beeble.ai/v1/products/sdr_to_hdr/models",
    headers=headers,
    timeout=30,
)
response.raise_for_status()
print(json.dumps(response.json(), indent=2))

const headers = { "x-api-key": process.env.BEEBLE_API_KEY }
if (process.env.BEEBLE_TEAM_ID) {
  headers["X-Beeble-Team-Id"] = process.env.BEEBLE_TEAM_ID
}
const response = await fetch(
  "https://api.beeble.ai/v1/products/sdr_to_hdr/models",
  {
    headers,
    signal: AbortSignal.timeout(30_000),
  },
)
if (!response.ok) throw new Error(await response.text())
console.log(JSON.stringify(await response.json(), null, 2))

Response (200): models contains each model’s id, name, input_schema, and any requires_consent value. Use the selected model’s input_schema for required inputs, types, defaults, and supported values. Request parameters and response schema The API model ID is sdr-to-hdr-1; SwitchHDR is the product-facing model name. Optional prompt_over and prompt_under describe what to reconstruct in highlights and shadows, respectively.

Submit a job

Schemas: Request body · Response. The inputs object follows your selected model’s input_schema above. Save as request.json with your media URIs. The Beeble URIs below can be replaced with any supported single-file media input. Use a unique idempotency_key for each new job; keep it unchanged on retries.

{
  "model_id": "sdr-to-hdr-1",
  "billing_unit": "credits",
  "idempotency_key": "sdr_to_hdr-example-001",
  "inputs": {
    "source": "beeble://uploads/your-upload-id/source.png",
    "generation_type": "image",
    "max_resolution": 720
  }
}

Python requires requests; JavaScript examples run in Node.js.

curl --fail-with-body https://api.beeble.ai/v1/products/sdr_to_hdr/jobs \
  -H "x-api-key: $BEEBLE_API_KEY" \
  -H "X-Beeble-Team-Id: ${BEEBLE_TEAM_ID:-}" \
  -H "Content-Type: application/json" \
  --data-binary @request.json

import json
import os
from pathlib import Path

import requests

headers = {"x-api-key": os.environ["BEEBLE_API_KEY"]}
if team_id := os.environ.get("BEEBLE_TEAM_ID"):
    headers["X-Beeble-Team-Id"] = team_id

response = requests.post(
    "https://api.beeble.ai/v1/products/sdr_to_hdr/jobs",
    headers=headers,
    json=json.loads(Path("request.json").read_text()),
    timeout=120,
)
response.raise_for_status()
job_id = response.json()["id"]
print(job_id)

import { readFile } from "node:fs/promises"

const headers = {
  "x-api-key": process.env.BEEBLE_API_KEY,
  "Content-Type": "application/json",
}
if (process.env.BEEBLE_TEAM_ID) {
  headers["X-Beeble-Team-Id"] = process.env.BEEBLE_TEAM_ID
}

const response = await fetch(
  "https://api.beeble.ai/v1/products/sdr_to_hdr/jobs",
  {
    method: "POST",
    headers,
    body: await readFile("request.json", "utf8"),
    signal: AbortSignal.timeout(120_000),
  },
)
if (!response.ok) throw new Error(await response.text())
const { id: jobId } = await response.json()
console.log(jobId)

Response (202, abbreviated):

{
  "id": "dap_example",
  "status": "processing",
  "outputs": {}
}

Results and constraints

The server measures source metadata, including video frame count. You can omit generation_type and frame_count; use the selected model’s duration and resolution limits. Use HDR output files for finishing; exposure previews are for inspection. See Billing & credits for spending caps and refunds.

Completed response

Poll the job using the returned id until status is success. Stop on failed, cancelled, or credit_required. Example response (200, success; abbreviated): URLs are illustrative. Available outputs depend on the model and input media.

{
  "id": "dap_example",
  "product": "sdr_to_hdr",
  "status": "success",
  "outputs": {
    "hdr": "https://cdn.beeble.ai/example/hdr.exr?signed-parameters",
    "hdr_preview": "https://cdn.beeble.ai/example/hdr-preview.webp?signed-parameters",
    "source": "https://cdn.beeble.ai/example/source.png?signed-parameters"
  }
}

Download outputs.hdr for the HDR image and outputs.hdr_preview for a tone-mapped preview. Video results can also include outputs.hdr_seq_zip and outputs.hdr_hlg_mov.

Get started

Products

Core concepts

Integrations

Before you start

Models and inputs

Submit a job

Results and constraints

Completed response

​Before you start

​Models and inputs

​Submit a job

​Results and constraints

​Completed response

Before you start

Models and inputs

Submit a job

Results and constraints

Completed response