# Google

Models are located at the [Google model zoo on the AI Hub](https://hub.degirum.com/public-models/degirum/google?utm_source=docs.degirum.com\&utm_medium=site\&utm_campaign=ai-hub-public-models-google).

## Models by DeGirum

### Edge TPU

**Age Estimation**

| Model Name                                              | Use Case       | MAE   | MSE    |
| ------------------------------------------------------- | -------------- | ----- | ------ |
| yolov8n\_relu6\_age--256x256\_quant\_tflite\_edgetpu\_1 | Age Estimation | 4.781 | 40.125 |

**Classification**

| Model Name                                                           | Use Case              | Top‑1 | Top‑5 |
| -------------------------------------------------------------------- | --------------------- | ----- | ----- |
| yolov8n\_relu6\_fairface\_gender--256x256\_quant\_tflite\_edgetpu\_1 | Gender Classification |       |       |
| yolov8s\_silu\_imagenet--224x224\_quant\_tflite\_edgetpu\_1          | Classification        |       |       |

**Detection**

| Model Name                                                          | Use Case                                      | mAP 50‑95 | mAP 50 |
| ------------------------------------------------------------------- | --------------------------------------------- | --------- | ------ |
| yolov8n\_relu6\_car--640x640\_quant\_tflite\_edgetpu\_1             | Car Detection                                 | 67.893    | 85.537 |
| yolov8n\_relu6\_coco--512x512\_quant\_tflite\_edgetpu\_1            | COCO Detection                                |           |        |
| yolov8n\_relu6\_coco\_pose--512x512\_quant\_tflite\_edgetpu\_1      | COCO Pose Keypoints                           |           |        |
| yolov8n\_relu6\_coco\_seg--512x512\_quant\_tflite\_edgetpu\_1       | COCO Instance Segmentation                    |           |        |
| yolov8n\_relu6\_face--640x640\_quant\_tflite\_edgetpu\_1            | Face Detection                                | 56.758    | 78.621 |
| yolov8n\_relu6\_fire\_smoke--640x640\_quant\_tflite\_edgetpu\_1     | Fire & Smoke Detection                        |           |        |
| yolov8n\_relu6\_hand--640x640\_quant\_tflite\_edgetpu\_1            | Hand Detection                                | 44.307    | 75.864 |
| yolov8n\_relu6\_human\_head--640x640\_quant\_tflite\_edgetpu\_1     | Human Head Detection                          |           |        |
| yolov8n\_relu6\_lp--640x640\_quant\_tflite\_edgetpu\_1              | License Plate Detection                       | 55.985    | 85.98  |
| yolov8n\_relu6\_person--640x640\_quant\_tflite\_edgetpu\_1          | Person Detection                              | 27.949    | 46.738 |
| yolov8n\_relu6\_ppe--640x640\_quant\_tflite\_edgetpu\_1             | Personal Protective Equipment (PPE) Detection | 36.274    | 68.036 |
| yolov8n\_relu6\_widerface\_kpts--640x640\_quant\_tflite\_edgetpu\_1 | Face Detection with Five Keypoints            |           |        |


---

# Agent Instructions: 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:

```
GET https://docs.degirum.com/ai-hub/public-models/google.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.