Update README.md

README.md

@@ -1,3 +1,67 @@
----
-license: apache-2.0
----
+---
+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)
+