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Update README.md - voxel51 integration #1827

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41 changes: 40 additions & 1 deletion README.md
Original file line number Diff line number Diff line change
Expand Up @@ -489,7 +489,8 @@ train_params = { ... # training parameters
<details markdown="1">

<summary><h3> Integration to ClearML </h3></summary>



```python
from super_gradients import Trainer

Expand All @@ -508,7 +509,45 @@ train_params = { ... # training parameters
}
```


</details>
<details markdown="1">

<summary><h3> Integration to Voxel51 </h3></summary>

You can apply SuperGradients YOLO-NAS models directly to your FiftyOne dataset using the apply_model() method:

```python
import fiftyone as fo
import fiftyone.zoo as foz

from super_gradients.training import models

dataset = foz.load_zoo_dataset("quickstart", max_samples=25)
dataset.select_fields().keep_fields()

model = models.get("yolo_nas_m", pretrained_weights="coco")

dataset.apply_model(model, label_field="yolo_nas", confidence_thresh=0.7)

session = fo.launch_app(dataset)
```

The SuperGradients YOLO-NAS model can be accessed directly from the FiftyOne Model Zoo:

```python
import fiftyone as fo
import fiftyone.zoo as foz

model = foz.load_zoo_model("yolo-nas-torch")

dataset = foz.load_zoo_dataset("quickstart")
dataset.apply_model(model, label_field="yolo_nas")

session = fo.launch_app(dataset)
```

</details>


## Installation Methods
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