[Backend]Add stable_diffusion and detection models support for KunlunXin XPU (#954)

* [FlyCV] Bump up FlyCV -> official release 1.0.0

* add valid_xpu for detection

* add paddledetection model support for xpu

* support all detection model in c++ and python

* fix code

* add python stable_diffusion support

Co-authored-by: DefTruth <qiustudent_r@163.com>
Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>

examples/vision/detection/yolov6/cpp/CMakeLists.txt

@@ -12,3 +12,7 @@ include_directories(${FASTDEPLOY_INCS})
 add_executable(infer_demo ${PROJECT_SOURCE_DIR}/infer.cc)
 # 添加FastDeploy库依赖
 target_link_libraries(infer_demo ${FASTDEPLOY_LIBS})
+
+add_executable(infer_paddle_demo ${PROJECT_SOURCE_DIR}/infer_paddle_model.cc)
+# 添加FastDeploy库依赖
+target_link_libraries(infer_paddle_demo ${FASTDEPLOY_LIBS})

examples/vision/detection/yolov6/cpp/README.md

@@ -18,10 +18,24 @@ tar xvf fastdeploy-linux-x64-x.x.x.tgz
 cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x
 make -j
 
-#下载官方转换好的YOLOv6模型文件和测试图片
-wget https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s.onnx
+#下载Paddle模型文件和测试图片
+https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s_infer.tar
+tar -xf yolov6s_infer.tar
 wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
 
+# CPU推理
+./infer_paddle_demo ./../yolov6s_infer 000000014439.jpg 0
+# GPU推理
+./infer_paddle_demo ./../yolov6s_infer 000000014439.jpg 1
+# XPU推理
+./infer_paddle_demo ./../yolov6s_infer 000000014439.jpg 2
+```
+
+如果想要验证ONNX模型的推理，可以参考如下命令：
+```bash
+#下载官方转换好的YOLOv6 ONNX模型文件和测试图片
+wget https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s.onnx
+wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
 
 # CPU推理
 ./infer_demo yolov6s.onnx 000000014439.jpg 0

examples/vision/detection/yolov6/cpp/infer_paddle_model.cc

@@ -0,0 +1,119 @@
+// 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 "fastdeploy/vision.h"
+#ifdef WIN32
+const char sep = '\\';
+#else
+const char sep = '/';
+#endif
+
+void CpuInfer(const std::string& model_dir, const std::string& image_file) {
+  fastdeploy::RuntimeOption option;
+  option.UseCpu();
+  option.UseOrtBackend();
+  auto model_file = model_dir + sep + "model.pdmodel";
+  auto params_file = model_dir + sep + "model.pdiparams";
+  auto model = fastdeploy::vision::detection::YOLOv6(model_file, params_file, option, fastdeploy::ModelFormat::PADDLE);
+  if (!model.Initialized()) {
+    std::cerr << "Failed to initialize." << std::endl;
+    return;
+  }
+
+  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("vis_result.jpg", vis_im);
+  std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
+}
+
+void XpuInfer(const std::string& model_dir, const std::string& image_file) {
+  fastdeploy::RuntimeOption option;
+  option.UseXpu();
+  auto model_file = model_dir + sep + "model.pdmodel";
+  auto params_file = model_dir + sep + "model.pdiparams";
+  auto model = fastdeploy::vision::detection::YOLOv6(model_file, params_file, option, fastdeploy::ModelFormat::PADDLE);
+  if (!model.Initialized()) {
+    std::cerr << "Failed to initialize." << std::endl;
+    return;
+  }
+
+  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("vis_result.jpg", vis_im);
+  std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
+}
+
+void GpuInfer(const std::string& model_dir, const std::string& image_file) {
+  fastdeploy::RuntimeOption option;
+  option.UseGpu();
+  option.UseTrtBackend();
+  auto model_file = model_dir + sep + "model.pdmodel";
+  auto params_file = model_dir + sep + "model.pdiparams";
+  auto model = fastdeploy::vision::detection::YOLOv6(model_file, params_file, option, fastdeploy::ModelFormat::PADDLE);
+  if (!model.Initialized()) {
+    std::cerr << "Failed to initialize." << std::endl;
+    return;
+  }
+
+  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("vis_result.jpg", vis_im);
+  std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
+}
+
+
+int main(int argc, char* argv[]) {
+  if (argc < 4) {
+    std::cout << "Usage: infer_demo path/to/model path/to/image run_option, "
+                 "e.g ./infer_model ./yolov6s_infer ./test.jpeg 0"
+              << std::endl;
+    std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
+                 "with gpu; 2: run with xpu."
+              << std::endl;
+    return -1;
+  }
+
+  if (std::atoi(argv[3]) == 0) {
+    CpuInfer(argv[1], argv[2]);
+  } else if (std::atoi(argv[3]) == 1) {
+    GpuInfer(argv[1], argv[2]);
+  } else if (std::atoi(argv[3]) == 2) {
+    XpuInfer(argv[1], argv[2]);
+  }
+  return 0;
+}