Not sure if insightface is using CPU or GPU?

Hi, all:

I can run my `test.py` (using insightface) for real-time face swapping. However:

- the swapping for camera streaming is extremly slow. It cannot even see my mouth **open and close**
- I **ONLY** installed `onnxruntime-gpu`
- But when I run my code, I got `Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}`

as follows:

```console
➜ python test.py
~/.local/lib/python3.10/site-packages/numpy/core/getlimits.py:518: UserWarning: The value of the smallest subnormal for type is zero.
setattr(self, word, getattr(machar, word).flat[0])
~/.local/lib/python3.10/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero.
return self._float_to_str(self.smallest_subnormal)
~/.local/lib/python3.10/site-packages/numpy/core/getlimits.py:518: UserWarning: The value of the smallest subnormal for type is zero.
setattr(self, word, getattr(machar, word).flat[0])
~/.local/lib/python3.10/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero.
return self._float_to_str(self.smallest_subnormal)
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ~/.insightface/models/buffalo_l/1k3d68.onnx landmark_3d_68 ['None', 3, 192, 192] 0.0 1.0
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ~/.insightface/models/buffalo_l/2d106det.onnx landmark_2d_106 ['None', 3, 192, 192] 0.0 1.0
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ~/.insightface/models/buffalo_l/det_10g.onnx detection [1, 3, '?', '?'] 127.5 128.0
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ~/.insightface/models/buffalo_l/genderage.onnx genderage ['None', 3, 96, 96] 0.0 1.0
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
find model: ~/.insightface/models/buffalo_l/w600k_r50.onnx recognition ['None', 3, 112, 112] 127.5 127.5
set det-size: (640, 640)
Applied providers: ['CPUExecutionProvider'], with options: {'CPUExecutionProvider': {}}
inswapper-shape: [1, 3, 128, 128]
~/.local/lib/python3.10/site-packages/insightface/utils/transform.py:68: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
P = np.linalg.lstsq(X_homo, Y)[0].T # Affine matrix. 3 x 4
[ WARN:0@5.312] global cap_gstreamer.cpp:1728 open OpenCV | GStreamer warning: Cannot query video position: status=0, value=-1, duration=-1
QFactoryLoader::QFactoryLoader() checking directory path "/usr/lib/x86_64-linux-gnu/qt6/plugins/platforms" ...
QFactoryLoader::QFactoryLoader() looking at "/usr/lib/x86_64-linux-gnu/qt6/plugins/platforms/libqeglfs.so"
Found metadata in lib /usr/lib/x86_64-linux-gnu/qt6/plugins/platforms/libqeglfs.so, metadata=
{
"IID": "org.qt-project.Qt.QPA.QPlatformIntegrationFactoryInterface.5.3",
"MetaData": {
"Keys": [
"eglfs"
]
},
"archreq": 0,
"className": "QEglFSIntegrationPlugin",
"debug": false,
"version": 393728
}
......
```

I think the **Applied providers** should be one of `TensorrtExecutionProvider` or `CUDAExecutionProvider`, for I got so many providers.

```python
['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'MIGraphXExecutionProvider', 'ROCMExecutionProvider', 'OpenVINOExecutionProvider', 'DnnlExecutionProvider', 'TvmExecutionProvider', 'VitisAIExecutionProvider', 'QNNExecutionProvider', 'NnapiExecutionProvider', 'JsExecutionProvider', 'CoreMLExecutionProvider', 'ArmNNExecutionProvider', 'ACLExecutionProvider', 'DmlExecutionProvider', 'RknpuExecutionProvider', 'XnnpackExecutionProvider', 'CANNExecutionProvider', 'AzureExecutionProvider', 'CPUExecutionProvider']
```

Why the actual provider I obtained is `CPUExecutionProvider` ?? Is this the reason that makes my `test.py` very slow???

Cheers