# cv2.error: OpenCV(4.9.0) ../modules/dnn/src/onnx/onnx_importer.cpp:1122: error: (-2:Unspecified error) in function 'importNode': OpenCV does not support ONNX operator 'ScatterND'

- **ID:** `opencv/dnn-readnet-from-onnx-unsupported-op`
- **Domain:** opencv
- **Category:** module_error
- **Error Code:** `-2`
- **Verification:** ai_generated
- **Fix Rate:** 80%

## Root Cause

The ONNX model uses an operator (e.g., ScatterND, NonMaxSuppression) that is not implemented in OpenCV's DNN module.

## Version Compatibility

| Version | Status | Introduced | Deprecated |
|---------|--------|------------|------------|
| 4.8.0 | active | — | — |
| 4.9.0 | active | — | — |
| 4.10.0 | active | — | — |

## Workarounds

1. **Export the ONNX model from PyTorch/TensorFlow with opset version 10 or lower, avoiding newer operators: torch.onnx.export(model, dummy_input, 'model.onnx', opset_version=10)** (70% success)
   ```
   Export the ONNX model from PyTorch/TensorFlow with opset version 10 or lower, avoiding newer operators: torch.onnx.export(model, dummy_input, 'model.onnx', opset_version=10)
   ```
2. **Use a different inference backend like ONNX Runtime instead of OpenCV DNN: import onnxruntime; session = onnxruntime.InferenceSession('model.onnx')** (95% success)
   ```
   Use a different inference backend like ONNX Runtime instead of OpenCV DNN: import onnxruntime; session = onnxruntime.InferenceSession('model.onnx')
   ```

## Dead Ends

- **** — OpenCV's DNN backend has limited ONNX operator coverage; many ops remain unimplemented across versions. (60% fail)
- **** — Conversion tools often map unsupported ops to other unsupported ops or fail entirely. (80% fail)