> For the complete documentation index, see [llms.txt](https://doc.faceplugin.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://doc.faceplugin.com/face-recognition-sdk/face-recognition-windows-sdk.md).

# Face Recognition Windows SDK

Faceplugin Face Recognition Windows SDK. Fully on-premise HTTP API on port 8083. detect, quality, feature, match, similarity. No Docker.

Fully on-premise **commercial Face Recognition HTTP API for Windows**. Default port **8083**. Gradio **9003**. No Docker on Windows.

This is not the [Open Source Face Recognition Windows SDK](/face-recognition-sdk/open-source-face-recognition-windows-sdk.md). For recognition **and** liveness in one App, use [Face Recognition SDK Windows (Recognition + Liveness)](/face-recognition-sdk/face-recognition-sdk-windows.md).

### Code <a href="#setup" id="setup"></a>

{% embed url="<https://github.com/Faceplugin-ltd/FaceRecognition-Windows>" %}

### Setup <a href="#setup" id="setup"></a>

1. Copy the runtime from [Google Drive](https://drive.google.com/drive/folders/12i5d2-TahuJumre2EVYqWO8cIi_unTBz) into `lib\cpu\`.
2. Install and run:

```
pip install -r requirements.txt
run.bat
```

3. Copy `FPMC1.…` from the terminal or `GET /api/machinecode`, request `FP1.…`, then `POST /api/activate`.

### APIs

Same routes as [Face Recognition Linux SDK](/face-recognition-sdk/face-recognition-linux-sdk.md):

| Endpoint                 | Purpose                           |
| ------------------------ | --------------------------------- |
| `GET /api/health`        | Process is listening (no license) |
| `GET /api/machinecode`   | Machine code `FPMC1.…`            |
| `GET /api/licenseStatus` | License status                    |
| `GET /api/backend`       | `"cpu"`                           |
| `POST /api/activate`     | Activate and `init_sdk()`         |
| `POST /api/detect`       | Detect faces                      |
| `POST /api/quality`      | Quality checks                    |
| `POST /api/feature`      | Extract template                  |
| `POST /api/match`        | Compare two photos                |
| `POST /api/similarity`   | Compare two templates             |

There is **no** `POST /api/identify`.

Python: `sdk.detect`, `sdk.quality`, `sdk.feature`, `sdk.match`, `sdk.similarity`.

### Try it

```bash
curl -s http://127.0.0.1:8083/api/health
IMG=$(base64 -w0 face.jpg)

curl -s -X POST http://127.0.0.1:8083/api/detect \
  -H 'Content-Type: application/json' \
  -d "{\"image\":\"$IMG\"}"
```

**Postman:** import `postman/FaceRecognition-API.postman_collection.json` from the repo. **Gradio (host only):** `DEMO_PORT=9003 API_BASE=http://127.0.0.1:8083 python demo.py`.

Control routes return a JSON **envelope**. Process POSTs return **engine JSON**. There is **no** `POST /api/identify` (no server-side 1:N gallery). Store templates in **your** database and call `/api/similarity`.

[Request a License & Support](/request-a-license-and-support.md) · [Contact US](/contact-us.md)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://doc.faceplugin.com/face-recognition-sdk/face-recognition-windows-sdk.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.