---
license: apache-2.0
---


For details about the models, please see: https://github.com/roboflow/rf-detr


The models have been exported to executorch without lowering.

To run:

```python

from PIL import Image, ImageDraw

from executorch.runtime import Runtime
import torch
import torch.nn.functional as F
from torchvision import transforms


IMG_SIZE = (512, 512) 
# change to (384, 384) for RFDETRNano
# change to (512, 512) for RFDETRSmall
# change to (576, 576) for RFDETRMedium
# change to (704, 704) for RFDETRLarge


def visualize_output(image, output):
    draw = ImageDraw.Draw(image)

    for box,logits in zip(output[0][0], output[1][0]):
        probs = F.softmax(logits, dim=0) 
        pred_class = torch.argmax(probs, dim=0) 

        if probs[pred_class] > 0.7:  # only draw if confidence is greater than 0.7
            cx, cy, w, h = box
            x1 = int((cx - w / 2) * img.width)
            y1 = int((cy - h / 2) * img.height)
            x2 = int((cx + w / 2) * img.width)
            y2 = int((cy + h / 2) * img.height) 
                
            draw.rectangle([(x1, y1), (x2, y2)], fill=None, outline="black", width=3)

img = Image.open("./cats_coco.jpg").convert("RGB")
transform = transforms.Compose([
    transforms.Resize(IMG_SIZE),
    transforms.ToTensor(),
])

tensor = transform(img)
tensor = tensor.unsqueeze(0)


runtime = Runtime.get()
method = runtime.load_program("model_small.pte").load_method("forward")
outputs = method.execute([tensor])

visualize_output(img, outputs)
img.save("output.png")
img.show()
```

Example output:
![Example output](./output.png)