# Bria Fibo Edit Colorize > Add realistic color to black-and-white photos, or apply a curated color treatment (vivid, sepia vintage), with commercially safe outputs. ## Overview - **Endpoint**: `https://queue.modelrunner.run/bria/fibo-edit/colorize` - **Model ID**: `bria/fibo-edit/colorize` - **Category**: image-to-image - **Kind**: inference - **Tags**: bria, fibo-edit, colorize, colorization, color-grading, image-editing, image-to-image ## Pricing - **Price**: $0.04 per output ## Request Lifecycle This model runs on the ModelRunner **asynchronous queue API** — a single POST does not return the output. Every call requires an `Authorization: Key $MODEL_RUNNER_KEY` header. Run three steps: 1. **Submit** — `POST https://queue.modelrunner.run/bria/fibo-edit/colorize` with a JSON body holding the input fields at the top level. The body may also include a reserved top-level `metadata` object — a flat string map (max 16 keys, key ≤64 / value ≤512 chars) stored on the request for your own tagging. It is never sent to the model; filter your request history with `GET https://queue.modelrunner.run/requests?metadata=` (exact key=value matches, AND-ed). The response carries request handles only (no output yet): ```json { "status": "IN_QUEUE", "request_id": "<21-char id>", "status_url": "https://queue.modelrunner.run/bria/fibo-edit/colorize/requests//status", "response_url": "https://queue.modelrunner.run/bria/fibo-edit/colorize/requests/", "cancel_url": "https://queue.modelrunner.run/bria/fibo-edit/colorize/requests//cancel" } ``` 2. **Poll status** — `GET ` until `status` is `COMPLETED`. Possible values are `IN_QUEUE`, `IN_PROGRESS`, `COMPLETED`, `FAILED`, `CANCELLED`. A `FAILED` request responds with HTTP 400 and an `error` field. 3. **Read result** — `GET `. Returns the finished request, including the generated `output`: ```json { "id": "", "status": "COMPLETED", "output": ..., "input": ... } ``` The JavaScript and Python SDKs below perform steps 2–3 for you. In any language without an SDK (Swift, Go, Kotlin, etc.) you must implement the polling loop and the final result fetch yourself — see the cURL example for the full flow. ### Input Schema - **`color`** (`ColorEnum`, _required_): The color palette or aesthetic for the output image. - Default: `"contemporary color"` - Options: `"contemporary color"`, `"vivid color"`, `"black and white colors"`, `"sepia vintage"` - **`image_url`** (`string`, _required_): The source image to colorize or color-grade. ### Output Schema _No `Output` schema properties are available._ ## Default Example **Input** ```json { "color": "contemporary color", "image_url": "https://media.modelrunner.ai/QFYAnSxCxrkaSsDm-bw-landscape-forest.jpg" } ``` **Output** ```json [ "https://media.modelrunner.ai/4P52d8QRi7Co6zY7HC7yl.png" ] ``` ## Usage Examples ### cURL The queue API is asynchronous: submit the request, poll `status_url` until it is `COMPLETED`, then read the result from `response_url`. Requires `jq`. ```bash # 1. Submit the request (returns request handles, not the output) SUBMIT=$(curl --silent --request POST \ --url https://queue.modelrunner.run/bria/fibo-edit/colorize \ --header "Authorization: Key $MODEL_RUNNER_KEY" \ --header "Content-Type: application/json" \ --data '{ "color": "contemporary color", "image_url": "https://media.modelrunner.ai/QFYAnSxCxrkaSsDm-bw-landscape-forest.jpg" }') STATUS_URL=$(echo "$SUBMIT" | jq -r '.status_url') RESPONSE_URL=$(echo "$SUBMIT" | jq -r '.response_url') # 2. Poll until the request leaves the queue / in-progress state while true; do STATUS=$(curl --silent --url "$STATUS_URL" \ --header "Authorization: Key $MODEL_RUNNER_KEY" | jq -r '.status') echo "Status: $STATUS" case "$STATUS" in COMPLETED) break ;; FAILED|CANCELLED) echo "Request $STATUS"; exit 1 ;; esac sleep 1 done # 3. Read the finished request, including the generated output curl --silent --url "$RESPONSE_URL" \ --header "Authorization: Key $MODEL_RUNNER_KEY" ``` ### JavaScript ```javascript import { modelrunner } from "@modelrunner/client"; const result = await modelrunner.subscribe("bria/fibo-edit/colorize", { input: { "color": "contemporary color", "image_url": "https://media.modelrunner.ai/QFYAnSxCxrkaSsDm-bw-landscape-forest.jpg" } }); console.log(result.data); ``` ### Python ```python import asyncio import modelrunner_ai async def main(): response = await modelrunner_ai.submit_async( "bria/fibo-edit/colorize", arguments={ "color": "contemporary color", "image_url": "https://media.modelrunner.ai/QFYAnSxCxrkaSsDm-bw-landscape-forest.jpg" } ) result = await response.get() print(result["output"]) asyncio.run(main()) ``` ## Additional Resources - [Playground](https://modelrunner.ai/models/bria/fibo-edit/colorize) - [OpenAPI Schema](https://modelrunner.ai/models/bria/fibo-edit/colorize/openapi.json) - [LLM Instructions](https://modelrunner.ai/models/bria/fibo-edit/colorize/llms.txt)