[Model] Support Paddle3D PETR v2 model (#1863)

* Support PETR v2

* make petrv2 precision equal with the origin repo

* delete extra func

* modify review problem

* delete visualize

* Update README_CN.md

* Update README.md

* Update README_CN.md

* fix build problem

* delete external variable and function

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Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>

examples/vision/perception/paddle3d/petr/python/README.md

@@ -0,0 +1,63 @@
+English | [简体中文](README_CN.md)
+# Petr Python Deployment Example
+
+Before deployment, the following two steps need to be confirmed
+
+- 1. The hardware and software environment meets the requirements, refer to [FastDeploy environment requirements](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)
+- 2. FastDeploy Python whl package installation, refer to [FastDeploy Python Installation](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
+
+This directory provides an example of `infer.py` to quickly complete the deployment of Petr on CPU/GPU. Execute the following script to complete
+
+```bash
+#Download deployment sample code
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd examples/vision/vision/paddle3d/petr/python
+
+wget https://bj.bcebos.com/fastdeploy/models/petr.tar.gz
+tar -xf petr.tar.gz
+wget https://bj.bcebos.com/fastdeploy/models/petr_test.png
+
+# CPU reasoning
+python infer.py --model petr --image petr_test.png --device cpu
+# GPU inference
+python infer.py --model petr --image petr_test.png --device gpu
+```
+
+## Petr Python interface
+
+```python
+fastdeploy.vision.detection.Petr(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
+```
+
+Petr model loading and initialization.
+
+**parameter**
+> * **model_file**(str): model file path
+> * **params_file**(str): parameter file path
+> * **config_file**(str): configuration file path
+> * **runtime_option**(RuntimeOption): Backend reasoning configuration, the default is None, that is, the default configuration is used
+> * **model_format**(ModelFormat): model format, the default is Paddle format
+
+### predict function
+
+> ```python
+> Petr. predict(image_data)
+> ```
+>
+> Model prediction interface, the input image directly outputs the detection result.
+>
+> **parameters**
+>
+> > * **image_data**(np.ndarray): input data, note that it must be in HWC, BGR format
+
+> **Back**
+>
+> > Return the `fastdeploy.vision.PerceptionResult` structure, structure description reference document [Vision Model Prediction Results](../../../../../docs/api/vision_results/)
+
+
+## Other documents
+
+- [Petr Model Introduction](..)
+- [Petr C++ deployment](../cpp)
+- [Description of model prediction results](../../../../../docs/api/vision_results/)
+- [How to switch model inference backend engine](../../../../../docs/en/faq/how_to_change_backend.md)