# alibaba/qwen-image/translate

> Qwen Vision Translate offers OCR-based image understanding and multilingual in-image text translation for context-aware results. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

## Overview

- **Endpoint**: `https://api.wavespeed.ai/api/v3/alibaba/qwen-image/translate`
- **Polling/result URL**: `https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result`
- **Model ID**: `alibaba/qwen-image/translate`
- **Category**: image-to-image

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
The API is asynchronous: submit a prediction, then poll its result URL until it completes.

### Input Schema

The API accepts the following input parameters:

- **`image`** (`string`, _required_):
  The image to process for translation

- **`target_lang`** (`string`, _required_):
  Target language code for translation
  - Default: `"zh"`
  - Options: "en", "zh", "ja", "ko", "fr", "de", "es", "ru", "ar"

- **`source_lang`** (`string`, _optional_):
  Source language code (auto for auto-detection)
  - Default: `"auto"`
  - Options: "auto", "en", "zh", "ja", "ko", "fr", "de", "es", "ru", "ar"

- **`domain_hint`** (`string`, _optional_):
  If you want the translation style to be more in line with the characteristics of a certain field, you can use English to describe the usage scenario, translation style and other field requirements. In order to ensure the translation effect, it is recommended that the length does not exceed 200 English words.

- **`sensitives`** (`array of string`, _optional_):
  Array of sensitive words to filter

- **`terminologies`** (`array of object`, _optional_):
  Array of terminoogies to use for translation

- **`skip_image_segment`** (`boolean`, _optional_):
  Whether to skip image segmentation
  - Default: `false`



**Required Parameters Example**:

```json
{
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "target_lang": "zh"
}
```

**Full Example**:

```json
{
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "target_lang": "zh",
  "source_lang": "auto",
  "domain_hint": "example",
  "sensitives": [],
  "terminologies": [],
  "skip_image_segment": false
}
```

### Result Data Schema

The `data` object returned by the API has the following fields:

- **`created_at`** (`string (date-time)`, _optional_):
  ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction, the ID of the prediction to get.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array of string | object`, _optional_):
  Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example `data` Object**:

```json
{
  "created_at": "example",
  "id": "example",
  "model": "example",
  "outputs": [],
  "status": "example",
  "urls": {}
}
```

## Usage Examples

The examples use `jq` to read JSON. Set your API key first:

```bash
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
```

### 1. Submit a prediction

```bash
REQUEST_BODY=$(cat <<'JSON'
{
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "target_lang": "zh"
}
JSON
)

SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  --request POST \
  --url https://api.wavespeed.ai/api/v3/alibaba/qwen-image/translate \
  --header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  --header "Content-Type: application/json" \
  --data "${REQUEST_BODY}")

printf '%s\n' "${SUBMIT_RESPONSE}" | jq .
```

The response contains the prediction ID in `data.id`.

### 2. Poll until complete and read `outputs`

```bash
PREDICTION_ID=$(printf '%s' "${SUBMIT_RESPONSE}" | jq -r '.data.id')
if [ -z "${PREDICTION_ID}" ] || [ "${PREDICTION_ID}" = "null" ]; then
  printf 'Submission response did not contain data.id\n' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    --request GET \
    --url "${RESULT_URL}" \
    --header "Authorization: Bearer ${WAVESPEED_API_KEY}")

  RESULT=$(printf '%s' "${RESPONSE}" | jq -e '.data')
  STATUS=$(printf '%s' "${RESULT}" | jq -er '.status')
  case "${STATUS}" in
    completed)
      # Generated files are returned in the outputs array.
      printf '%s\n' "${RESULT}" | jq '.outputs'
      break
      ;;
    failed|cancelled|timeout|deleted)
      printf '%s\n' "${RESULT}" | jq '{status, error, code}'
      exit 1
      ;;
    *)
      sleep 2
      ;;
  esac
done
```

## Additional Resources

### Documentation

- [Model Playground](https://wavespeed.ai/models/alibaba/qwen-image/translate)
- [API Documentation](https://wavespeed.ai/docs/docs-api/alibaba/alibaba-qwen-image-translate)