# Tool usage instructions of caffe2onnx

This chapter introduces the AX version of the caffe2onnx conversion tool, which is used to convert Caffe floating-point models into ONNX floating-point models.

:::{note}
The model semantics below are all floating point models.
:::

## Convert Caffe model to ONNX model

We provide command line tools to convert Caffe models to ONNX models. On X86 platforms, you can pass a folder to convert all Caffe models in it:

```bash
caffe2onnx --convert --checkpoint_path /path/to/your/model/zoo
```

This will recursively find all files with the suffix ".caffemodel" and their corresponding ".prototxt" files in the specified folder. This is a Caffe model, convert it to an ONNX model, and save it with the suffix ".onnx" using the Caffe model's prefix.

On the ARM platform, the interface is as follows:

```bash
caffe2onnx_cli --convert --checkpoint_path /path/to/your/model/zoo
```

:::{note}
The ".prototxt" and ".caffemodel" files corresponding to the Caffe model need to be in the same folder and share a prefix.
:::

## Validate the converted ONNX model

On the X86 platform, you can use the following command line tool to split the original Caffe model and the converted ONNX model:

```bash
caffe2onnx --validate --checkpoint_path /path/to/your/model/zoo
```

First, this will recursively find all files with the ".onnx" suffix in the specified folder, then match the corresponding ".prototxt" and ".caffemodel" files according to their prefixes, generate a random dataset, use ONNXRuntime and Caffe inference tools for inference, and calculate the "Correlation", "Standard Deviation", "Cosine Similarity", "Normalized Relative Error", "Max Difference" and "Mean Difference" of the two.

:::{note}
".prototxt" and ".caffemodel" corresponding to the Caffe model
The file and the converted ".onnx" file need to be in the same folder and share a prefix.
:::

:::{note}
This step requires caffe to be installed.
:::

:::{note}
Since the compatibility of Caffe ARM platform is not very good, this function is not currently supported on ARM platform.
:::