更换文档检测模型

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

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+# PaddleDetection Python部署示例
+
+## 1. 部署环境准备
+
+在部署前，需自行编译基于算能硬件的FastDeploy python wheel包并安装，参考文档[算能硬件部署环境](https://github.com/PaddlePaddle/FastDeploy/blob/develop/docs/cn/build_and_install#算能硬件部署环境)
+
+本目录下提供`infer.py`, 快速完成 PP-YOLOE ,在SOPHGO TPU上部署的示例，执行如下脚本即可完成。PP-YOLOV8和 PicoDet的部署逻辑类似，只需要切换模型即可。 
+
+## 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)。
+
+```bash
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/PaddleDetection.git
+cd PaddleDetection/deploy/fastdeploy/sophgo/python
+
+# 下载图片
+wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
+
+# 推理
+#ppyoloe推理示例
+python3 infer.py --model_file model/ppyoloe_crn_s_300e_coco_1684x_f32.bmodel --config_file model/infer_cfg.yml --image_file ./000000014439.jpg
+
+# 运行完成后返回结果如下所示
+可视化结果存储在sophgo_result.jpg中
+```
+
+## 3. 更多指南
+- [C++部署](../cpp)
+- [转换PP-YOLOE SOPHGO模型文档](../README.md)

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

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+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import fastdeploy as fd
+import cv2
+import os
+
+
+def parse_arguments():
+    import argparse
+    import ast
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model_file", required=True, help="Path of sophgo model.")
+    parser.add_argument("--config_file", required=True, help="Path of config.")
+    parser.add_argument(
+        "--image_file", type=str, required=True, help="Path of test image file.")
+    return parser.parse_args()
+
+
+if __name__ == "__main__":
+    args = parse_arguments()
+
+    model_file = args.model_file
+    params_file = ""
+    config_file = args.config_file
+
+    # setup runtime
+    runtime_option = fd.RuntimeOption()
+    runtime_option.use_sophgo()
+
+    model = fd.vision.detection.PPYOLOE(
+        model_file,
+        params_file,
+        config_file,
+        runtime_option=runtime_option,
+        model_format=fd.ModelFormat.SOPHGO)
+
+    model.postprocessor.apply_nms()
+
+    # predict
+    im = cv2.imread(args.image_file)
+    result = model.predict(im)
+    print(result)
+
+    # visualize
+    vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
+    cv2.imwrite("sophgo_result.jpg", vis_im)
+    print("Visualized result save in ./sophgo_result.jpg")