[SOPHGO] Add PaddleDetection YOLOv8 example (#1165)

sophon yolov8s example

Co-authored-by: Jason <jiangjiajun@baidu.com>

examples/vision/detection/paddledetection/sophgo/README.md

@@ -5,8 +5,9 @@
 目前SOPHGO支持如下模型的部署
 - [PP-YOLOE系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/ppyoloe)
 - [PicoDet系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet)
+- [YOLOV8系列模型](https://github.com/PaddlePaddle/PaddleDetection/tree/)
 
-## 准备PP-YOLOE或者PicoDet部署模型以及转换模型
+## 准备PP-YOLOE YOLOV8或者PicoDet部署模型以及转换模型
 
 SOPHGO-TPU部署模型前需要将Paddle模型转换成bmodel模型，具体步骤如下:
 - Paddle动态图模型转换为ONNX模型，请参考[PaddleDetection导出模型](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/deploy/EXPORT_MODEL.md).
@@ -14,7 +15,7 @@ SOPHGO-TPU部署模型前需要将Paddle模型转换成bmodel模型，具体步
 
 ## 模型转换example
 
-PP-YOLOE和PicoDet模型转换过程类似，下面以ppyoloe_crn_s_300e_coco为例子,教大家如何转换Paddle模型到SOPHGO-TPU模型
+PP-YOLOE YOLOV8和PicoDet模型转换过程类似，下面以ppyoloe_crn_s_300e_coco为例子,教大家如何转换Paddle模型到SOPHGO-TPU模型
 
 ### 导出ONNX模型
 ```shell

examples/vision/detection/paddledetection/sophgo/cpp/CMakeLists.txt

@@ -14,6 +14,8 @@ include_directories(${FastDeploy_INCLUDE_DIRS})
 
 add_executable(infer_ppyoloe ${PROJECT_SOURCE_DIR}/infer_ppyoloe.cc)
 add_executable(infer_picodet ${PROJECT_SOURCE_DIR}/infer_picodet.cc)
+add_executable(infer_yolov8 ${PROJECT_SOURCE_DIR}/infer_yolov8.cc)
 # 添加FastDeploy库依赖
 target_link_libraries(infer_ppyoloe ${FASTDEPLOY_LIBS})
 target_link_libraries(infer_picodet ${FASTDEPLOY_LIBS})
+target_link_libraries(infer_yolov8 ${FASTDEPLOY_LIBS})

examples/vision/detection/paddledetection/sophgo/cpp/README.md

@@ -1,6 +1,6 @@
 # PaddleDetection C++部署示例
 
-本目录下提供`infer_ppyoloe.cc`和`infer_picodet.cc`快速完成PP-YOLOE模型和PicoDet模型在SOPHGO BM1684x板子上加速部署的示例。
+本目录下提供`infer_ppyoloe.cc`,`infer_yolov8.cc`和`infer_picodet.cc`快速完成PP-YOLOE模型,YOLOV8模型和PicoDet模型在SOPHGO BM1684x板子上加速部署的示例。
 
 在部署前，需确认以下两个步骤:
 
@@ -19,6 +19,7 @@
 ├── image  # 存放图片的文件夹
 ├── infer_ppyoloe.cc
 ├── infer_picodet.cc
+├── infer_yolov8.cc
 └── model  # 存放模型文件的文件夹
 ```
 

examples/vision/detection/paddledetection/sophgo/cpp/infer_yolov8.cc

@@ -0,0 +1,59 @@
+// 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.
+#include <sys/time.h>
+
+#include <iostream>
+#include <string>
+
+#include "fastdeploy/vision.h"
+
+void SophgoInfer(const std::string& model_dir, const std::string& image_file) {
+  auto model_file = model_dir + "/compilation.bmodel";
+  auto params_file = "";
+  auto config_file = model_dir + "/infer_cfg.yml";
+
+  auto option = fastdeploy::RuntimeOption();
+  option.UseSophgo();
+
+  auto format = fastdeploy::ModelFormat::SOPHGO;
+  
+  auto model = fastdeploy::vision::detection::PaddleYOLOv8(model_file, params_file, config_file, option, format);
+
+  model.GetPostprocessor().ApplyDecodeAndNMS();
+
+  auto im = cv::imread(image_file);
+
+  fastdeploy::vision::DetectionResult res;
+  if (!model.Predict(im, &res)) {
+    std::cerr << "Failed to predict." << std::endl;
+    return;
+  }
+
+  std::cout << res.Str() << std::endl;
+  auto vis_im = fastdeploy::vision::VisDetection(im, res);
+  cv::imwrite("infer_sophgo.jpg", vis_im);
+  std::cout << "Visualized result saved in ./infer_sophgo.jpg" << std::endl;
+}
+
+int main(int argc, char* argv[]) {
+  if (argc < 3) {
+    std::cout
+        << "Usage: infer_demo path/to/model_dir path/to/image run_option, "
+           "e.g ./infer_model ./yolov8_model_dir ./test.jpeg"
+        << std::endl;
+    return -1;
+  }
+  SophgoInfer(argv[1], argv[2]);
+  return 0;
+}

examples/vision/detection/paddledetection/sophgo/python/README.md

@@ -4,7 +4,7 @@
 
 - 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../../docs/cn/build_and_install/sophgo.md)
 
-本目录下提供`infer_ppyoloe.py`和`infer_picodet.py`快速完成 PP-YOLOE 和 PicoDet 在SOPHGO TPU上部署的示例。执行如下脚本即可完成
+本目录下提供`infer_ppyoloe.py`,`infer_yolov8.py`和`infer_picodet.py`快速完成 PP-YOLOE ,PP-YOLOV8和 PicoDet 在SOPHGO TPU上部署的示例。执行如下脚本即可完成
 
 ```bash
 # 下载部署示例代码
@@ -21,6 +21,8 @@ python3 infer_ppyoloe.py --model_file model/ppyoloe_crn_s_300e_coco_1684x_f32.bm
 #picodet推理示例
 python3 infer_picodet.py --model_file model/picodet_s_416_coco_lcnet_1684x_f32.bmodel --config_file model/infer_cfg.yml --image ./000000014439.jpg
 
+#yolov8推理示例
+python3 infer_yolov8.py --model_file model/yolov8s_s_300e_coco_1684x_f32.bmodel --config_file model/infer_cfg.yml --image ./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
 ```
@@ -28,5 +30,7 @@ python3 infer_picodet.py --model_file model/picodet_s_416_coco_lcnet_1684x_f32.b
 ## 其它文档
 - [PP-YOLOE C++部署](../cpp)
 - [PicoDet C++部署](../cpp)
+- [YOLOV8 C++部署](../cpp)
 - [转换PicoDet SOPHGO模型文档](../README.md)
 - [转换PP-YOLOE SOPHGO模型文档](../README.md)
+- [转换YOLOV8 SOPHGO模型文档](../README.md)

examples/vision/detection/paddledetection/sophgo/python/infer_yolov8.py

@@ -0,0 +1,59 @@
+# 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", 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
+
+    # 配置runtime，加载模型
+    runtime_option = fd.RuntimeOption()
+    runtime_option.use_sophgo()
+
+    model = fd.vision.detection.PaddleYOLOv8(
+        model_file,
+        params_file,
+        config_file,
+        runtime_option=runtime_option,
+        model_format=fd.ModelFormat.SOPHGO)
+
+    model.postprocessor.apply_decode_and_nms()
+
+    # 预测图片分割结果
+    im = cv2.imread(args.image)
+    result = model.predict(im)
+    print(result)
+
+    # 可视化结果
+    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")

fastdeploy/vision/detection/ppdet/model.h

@@ -260,6 +260,7 @@ class FASTDEPLOY_DECL PaddleYOLOv8 : public PPDetBase {
     valid_kunlunxin_backends = {Backend::LITE};
     valid_rknpu_backends = {Backend::RKNPU2};
     valid_ascend_backends = {Backend::LITE};
+    valid_sophgonpu_backends = {Backend::SOPHGOTPU};
     initialized = Initialize();
   }
 

python/fastdeploy/vision/detection/ppdet/__init__.py

@@ -519,7 +519,6 @@ class PaddleYOLOv8(PPYOLOE):
 
         super(PPYOLOE, self).__init__(runtime_option)
 
-        assert model_format == ModelFormat.PADDLE, "PaddleYOLOv8 model only support model format of ModelFormat.Paddle now."
         self._model = C.vision.detection.PaddleYOLOv8(
             model_file, params_file, config_file, self._runtime_option,
             model_format)