更换文档检测模型

paddle_detection/deploy/fastdeploy/ascend/python/README.md

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+[English](README.md) | 简体中文
+# PaddleDetection Ascend Python部署示例
+
+本目录下提供`infer.py`快速完成PPYOLOE在华为昇腾上部署的示例。
+
+## 1. 部署环境准备  
+在部署前，需自行编译基于华为昇腾NPU的FastDeploy python wheel包并安装，参考文档[华为昇腾NPU部署环境编译](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install#自行编译安装)
+
+## 2. 部署模型准备  
+在部署前，请准备好您所需要运行的推理模型，你可以选择使用[预导出的推理模型](../README.md)或者[自行导出PaddleDetection部署模型](../README.md)。  
+
+## 3. 运行部署示例
+```bash
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/PaddleDetection.git
+cd PaddleDetection/deploy/fastdeploy/ascend/python
+# 注意：如果当前分支找不到下面的fastdeploy测试代码，请切换到develop分支
+# git checkout develop
+
+# 下载模型文件和测试图片
+wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
+wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
+tar xvf ppyoloe_crn_l_300e_coco.tgz
+
+# 华为昇腾推理
+python infer.py --model_dir ppyoloe_crn_l_300e_coco --image_file 000000014439.jpg
+```
+
+运行完成可视化结果如下图所示
+<div  align="center">  
+<img src="https://user-images.githubusercontent.com/16222477/191712880-91ae128d-247a-43e0-b1e3-cafae78431e0.jpg", width=512px, height=256px />
+</div>
+
+## 4. 更多指南
+- [PaddleDetection Python API文档](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/python/html/object_detection.html)
+- [FastDeploy部署PaddleDetection模型概览](../../)
+- [C++部署](../cpp)
+
+## 5. 常见问题
+- [如何切换模型推理后端引擎](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/faq/how_to_change_backend.md)
+- [Intel GPU(独立显卡/集成显卡)的使用](https://github.com/PaddlePaddle/FastDeploy/blob/develop/tutorials/intel_gpu/README.md)
+- [编译CPU部署库](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install/cpu.md)
+- [编译GPU部署库](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install/gpu.md)
+- [编译Jetson部署库](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install/jetson.md)

paddle_detection/deploy/fastdeploy/ascend/python/infer.py

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+import cv2
+import os
+
+import fastdeploy as fd
+
+
+def parse_arguments():
+    import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model_dir", required=True, help="Path of PaddleDetection model.")
+    parser.add_argument(
+        "--image_file", type=str, required=True, help="Path of test image file.")
+    return parser.parse_args()
+
+args = parse_arguments()
+
+runtime_option = fd.RuntimeOption()
+runtime_option.use_ascend()
+
+if args.model_dir is None:
+    model_dir = fd.download_model(name='ppyoloe_crn_l_300e_coco')
+else:
+    model_dir = args.model_dir
+
+model_file = os.path.join(model_dir, "model.pdmodel")
+params_file = os.path.join(model_dir, "model.pdiparams")
+config_file = os.path.join(model_dir, "infer_cfg.yml")
+
+# settting for runtime
+model = fd.vision.detection.PPYOLOE(
+    model_file, params_file, config_file, runtime_option=runtime_option)
+
+# predict
+if args.image_file is None:
+    image_file = fd.utils.get_detection_test_image()
+else:
+    image_file = args.image_file
+im = cv2.imread(image_file)
+result = model.predict(im)
+print(result)
+
+# visualize
+vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
+cv2.imwrite("visualized_result.jpg", vis_im)
+print("Visualized result save in ./visualized_result.jpg")