> ## Documentation Index
> Fetch the complete documentation index at: https://docs.oxen.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Topaz Image Upscaler

> Professional AI image upscaling

<CardGroup cols={1}>
  <Card title="Try Topaz Image Upscaler in the Workbench" icon="flask" href="https://www.oxen.ai/ai/workbench?model=topazlabs-image-upscale">
    Run this model interactively, tune parameters, and compare outputs.
  </Card>
</CardGroup>

**Model ID:** `topazlabs-image-upscale`

Professional-grade image upscaling powered by AI, from Topaz Labs.

Standard V2 (general purpose) Low Resolution V2 (for low-res images) CGI (for digital art) High Fidelity V2 (preserves details) Text Refine (optimized for text)

## Example request

<Tip>
  Use the [Workbench](https://www.oxen.ai/ai/workbench?model=topazlabs-image-upscale) as a request builder: configure parameters for this model in the UI, then open the **API** tab to copy the exact cURL or Python call.
</Tip>

<Tabs>
  <Tab title="Sync">
    See the [image editing reference](/inference-api/reference/image_editing) for more details.

    <Tabs>
      <Tab title="Minimal">
        <CodeGroup>
          ```bash cURL theme={null}
          curl -X POST https://hub.oxen.ai/api/ai/images/edit \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "topazlabs-image-upscale",
            "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png"
          }'
          ```

          ```python Python theme={null}
          import os
          import requests

          response = requests.post(
              "https://hub.oxen.ai/api/ai/images/edit",
              headers={
                  "Content-Type": "application/json",
                  "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
              },
              json={
                  "model": "topazlabs-image-upscale",
                  "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png"
              },
          )
          response.raise_for_status()
          print(response.json())
          ```
        </CodeGroup>
      </Tab>

      <Tab title="All parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          curl -X POST https://hub.oxen.ai/api/ai/images/edit \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "topazlabs-image-upscale",
            "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png",
            "enhance_model": "High Fidelity V2",
            "upscale_factor": "2x",
            "output_format": "png"
          }'
          ```

          ```python Python theme={null}
          import os
          import requests

          response = requests.post(
              "https://hub.oxen.ai/api/ai/images/edit",
              headers={
                  "Content-Type": "application/json",
                  "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
              },
              json={
                  "model": "topazlabs-image-upscale",
                  "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png",
                  "enhance_model": "High Fidelity V2",
                  "upscale_factor": "2x",
                  "output_format": "png"
              },
          )
          response.raise_for_status()
          print(response.json())
          ```
        </CodeGroup>
      </Tab>
    </Tabs>
  </Tab>

  <Tab title="Async">
    See the [async queue reference](/inference-api/reference/async_queue) for more details.

    <Tabs>
      <Tab title="Minimal">
        <CodeGroup>
          ```bash cURL theme={null}
          # Enqueue, capture the generation id.
          GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "topazlabs-image-upscale",
            "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png"
          }' | jq -r '.generations[0].generation_id')

          # Poll until the generation reaches a terminal status.
          while true; do
            STATUS=$(curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
              "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq -r '.status')
            echo "Status: $STATUS"
            case $STATUS in succeeded|failed|cancelled) break;; esac
            sleep 5
          done

          # Print the result.
          curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
            "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq .
          ```

          ```python Python theme={null}
          import os
          import time
          import requests

          HEADERS = {
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          }

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers=HEADERS,
              json={
                  "model": "topazlabs-image-upscale",
                  "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          while True:
              data = requests.get(
                  f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
                  headers=HEADERS,
              ).json()
              if data["status"] in {"succeeded", "failed", "cancelled"}:
                  break
              time.sleep(5)

          if data["status"] == "succeeded":
              print(f"Result: {data['result_url']}")
          else:
              print(f"Generation {data['status']}: {data.get('error_message')}")
          ```
        </CodeGroup>
      </Tab>

      <Tab title="All parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          # Enqueue, capture the generation id.
          GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "topazlabs-image-upscale",
            "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png",
            "enhance_model": "High Fidelity V2",
            "upscale_factor": "2x",
            "output_format": "png"
          }' | jq -r '.generations[0].generation_id')

          # Poll until the generation reaches a terminal status.
          while true; do
            STATUS=$(curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
              "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq -r '.status')
            echo "Status: $STATUS"
            case $STATUS in succeeded|failed|cancelled) break;; esac
            sleep 5
          done

          # Print the result.
          curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
            "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq .
          ```

          ```python Python theme={null}
          import os
          import time
          import requests

          HEADERS = {
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          }

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers=HEADERS,
              json={
                  "model": "topazlabs-image-upscale",
                  "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png",
                  "enhance_model": "High Fidelity V2",
                  "upscale_factor": "2x",
                  "output_format": "png"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          while True:
              data = requests.get(
                  f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
                  headers=HEADERS,
              ).json()
              if data["status"] in {"succeeded", "failed", "cancelled"}:
                  break
              time.sleep(5)

          if data["status"] == "succeeded":
              print(f"Result: {data['result_url']}")
          else:
              print(f"Generation {data['status']}: {data.get('error_message')}")
          ```
        </CodeGroup>
      </Tab>
    </Tabs>
  </Tab>

  <Tab title="Async with SSE">
    See the [async queue reference](/inference-api/reference/async_queue) for more details.

    <Tabs>
      <Tab title="Minimal">
        <CodeGroup>
          ```bash cURL theme={null}
          # Enqueue, capture the generation id.
          GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "topazlabs-image-upscale",
            "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png"
          }' | jq -r '.generations[0].generation_id')

          # Stream the SSE channel, grab the data line that follows a
          # media_generation_completed event for our id, and pretty-print it.
          curl -sN -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/events \
            | awk -v id="$GEN_ID" '
              /^event: media_generation_completed$/ { expect=1; next }
              /^data: / && expect {
                payload = substr($0, 7)
                if (index(payload, "\"generation_id\":\"" id "\"")) { print payload; exit }
                expect = 0
              }
            ' | jq .
          ```

          ```python Python theme={null}
          import json
          import os
          import requests

          API_KEY = os.environ["OXEN_API_KEY"]
          AUTH = {"Authorization": f"Bearer {API_KEY}"}

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers={**AUTH, "Content-Type": "application/json"},
              json={
                  "model": "topazlabs-image-upscale",
                  "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          with requests.get(
              "https://hub.oxen.ai/api/events",
              headers=AUTH,
              stream=True,
          ) as stream:
              event_name = None
              for line in stream.iter_lines(decode_unicode=True):
                  if line.startswith("event: "):
                      event_name = line.removeprefix("event: ")
                  elif line.startswith("data: ") and event_name == "media_generation_completed":
                      payload = json.loads(line.removeprefix("data: "))
                      if payload.get("generation_id") == generation_id:
                          print(payload)
                          break
          ```
        </CodeGroup>
      </Tab>

      <Tab title="All parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          # Enqueue, capture the generation id.
          GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
            -H "Content-Type: application/json" \
            -H "Authorization: Bearer $OXEN_API_KEY" \
            -d '{
            "model": "topazlabs-image-upscale",
            "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png",
            "enhance_model": "High Fidelity V2",
            "upscale_factor": "2x",
            "output_format": "png"
          }' | jq -r '.generations[0].generation_id')

          # Stream the SSE channel, grab the data line that follows a
          # media_generation_completed event for our id, and pretty-print it.
          curl -sN -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/events \
            | awk -v id="$GEN_ID" '
              /^event: media_generation_completed$/ { expect=1; next }
              /^data: / && expect {
                payload = substr($0, 7)
                if (index(payload, "\"generation_id\":\"" id "\"")) { print payload; exit }
                expect = 0
              }
            ' | jq .
          ```

          ```python Python theme={null}
          import json
          import os
          import requests

          API_KEY = os.environ["OXEN_API_KEY"]
          AUTH = {"Authorization": f"Bearer {API_KEY}"}

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers={**AUTH, "Content-Type": "application/json"},
              json={
                  "model": "topazlabs-image-upscale",
                  "input_image": "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png",
                  "enhance_model": "High Fidelity V2",
                  "upscale_factor": "2x",
                  "output_format": "png"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          with requests.get(
              "https://hub.oxen.ai/api/events",
              headers=AUTH,
              stream=True,
          ) as stream:
              event_name = None
              for line in stream.iter_lines(decode_unicode=True):
                  if line.startswith("event: "):
                      event_name = line.removeprefix("event: ")
                  elif line.startswith("data: ") and event_name == "media_generation_completed":
                      payload = json.loads(line.removeprefix("data: "))
                      if payload.get("generation_id") == generation_id:
                          print(payload)
                          break
          ```
        </CodeGroup>
      </Tab>
    </Tabs>
  </Tab>
</Tabs>

## Fetch model details

The [models endpoint](/inference-api/reference/models/overview) returns the full model object, including its `json_request_schema`.

```bash theme={null}
curl -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/ai/models/topazlabs-image-upscale
```

## Request parameters

### Required parameters

| Field         | Type     | Default                                                                                                                 | Description                                                              |
| ------------- | -------- | ----------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| `input_image` | `string` | `"https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png"` | Image to use as reference. Must be jpeg, png, gif, or webp. Format: uri. |

### Optional parameters

| Field            | Type     | Default              | Description                                                                                                                                                                                                                                                     |
| ---------------- | -------- | -------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `enhance_model`  | `string` | `"High Fidelity V2"` | Models to Use: Standard V2 (general purpose), Low Resolution V2 (for low-res images), CGI (for digital art), High Fidelity V2 (preserves details), Text Refine (optimized for text) One of: Standard V2, Low Resolution V2, CGI, High Fidelity V2, Text Refine. |
| `upscale_factor` | `string` | `"2x"`               | How much to upscale the image One of: 4x, 2x.                                                                                                                                                                                                                   |
| `output_format`  | `string` | `"png"`              | Format of the output images One of: jpg, png.                                                                                                                                                                                                                   |