---
language:
- en
library_name: ultralytics
pipeline_tag: image-classification
tags:
- fer2013
---

## How to Use

To use this model in your project, follow the steps below:

### 1. Installation

Ensure you have the `ultralytics` library installed, which is used for YOLO models:

```bash
pip install ultralytics
```
```text
# classs
angry
disgusted
fearful
happy
neutral
sad
surprised
```
### 2. Load the Model

You can load the model and perform detection on an image as follows:
```python
from ultralytics import YOLO

# Load the model
model = YOLO("./feryolo-11x-64.pt")

# Perform detection on an image
results = model("image.png")

# Display or process the results
results.show()  # This will display the image with detected objects
```

### 3. Model Inference
The results object contains bounding boxes, labels (e.g., numbers or operators), and confidence scores for each detected object.

Access them like this:

```python
# View results
for r in results:
    print(r.probs)  # print the Probs object containing the detected class probabilities
```

![](result.png)