Updated README.md

README.md

@@ -24,6 +24,8 @@ The repository is organized into two main folders:
 
 ### 2. **Models**
    This folder contains complete models built with Kornia and exported to ONNX format. These models are designed for various computer vision tasks such as image processing, stereo vision, and more. Each model is accompanied by a detailed description of its purpose and how to use it.
+   > [!Note]
+   > The detection models exported in this repo do not include a postprocessor, you may need to do it yourself or re-export the model by setting `confidence_filtering=True`. For example, `RTDETRDetectorBuilder.to_onnx(confidence_threshold=0.5, confidence_filtering=True)`.
 
 ## Getting Started
 
@@ -41,7 +43,7 @@ from kornia.onnx import ONNXSequential
 onnx_seq = ONNXSequential(
     "hf://operators/kornia.color.gray.RgbToGrayscale",
     "hf://operators/kornia.geometry.transform.affwarp.Resize_512x512",
-    "YOUR_OWN_MODEL.onnx"
+    "hf://models/kornia.models.detection.rtdetr_r18vd_640x640",  # Or you may use "YOUR_OWN_MODEL.onnx"
 )
 # Prepare some input data
 input_data = np.random.randn(1, 3, 384, 512).astype(np.float32)