[Model] Support PP-ShiTuV2 models for PaddleClas (#1900)

* [cmake] add faiss.cmake -> pp-shituv2 * [PP-ShiTuV2] Support PP-ShituV2-Det model * [PP-ShiTuV2] Support PP-ShiTuV2-Det model * [PP-ShiTuV2] Add PPShiTuV2Recognizer c++&python support * [PP-ShiTuV2] Add PPShiTuV2Recognizer c++&python support * [Bug Fix] fix ppshitu_pybind error * [benchmark] Add ppshituv2-det c++ benchmark * [examples] Add PP-ShiTuV2 det & rec examples * [vision] Update vision classification result * [Bug Fix] fix trt shapes setting errors
2025-10-27 02:20:31 +08:00 · 2023-05-08 14:04:09 +08:00
parent df8dd3e3ac
commit 77cb9db6da
31 changed files with 1835 additions and 51 deletions
--- a/examples/vision/classification/ppshitu/cpu-gpu/cpp/infer_ppshituv2_det.cc
+++ b/examples/vision/classification/ppshitu/cpu-gpu/cpp/infer_ppshituv2_det.cc
@@ -0,0 +1,96 @@
+// 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 InitAndInfer(const std::string &model_dir, const std::string &image_file,
+                  const fastdeploy::RuntimeOption &option) {
+  auto model_file = model_dir + sep + "inference.pdmodel";
+  auto params_file = model_dir + sep + "inference.pdiparams";
+  auto config_file = model_dir + sep + "infer_cfg.yml";
+
+  auto model = fastdeploy::vision::classification::PPShiTuV2Detector(
+      model_file, params_file, config_file, option);
+  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;
+  }
+
+  // print res
+  std::cout << res.Str() << std::endl;
+  auto vis_im = fastdeploy::vision::VisDetection(im, res, 0.5);
+  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_demo "
+                 "./picodet_PPLCNet_x2_5_mainbody_lite_v1.0_infer ./test.jpeg 0"
+              << std::endl;
+    return -1;
+  }
+
+  fastdeploy::RuntimeOption option;
+  int flag = std::atoi(argv[3]);
+
+  if (flag == 0) {
+    option.UseCpu();
+    option.UsePaddleBackend();  // Paddle Inference
+  } else if (flag == 1) {
+    option.UseCpu();
+    option.UseOpenVINOBackend();  // OpenVINO
+  } else if (flag == 2) {
+    option.UseCpu();
+    option.UseOrtBackend();  // ONNX Runtime
+  } else if (flag == 3) {
+    option.UseCpu();
+    option.UseLiteBackend();  // Paddle Lite
+  } else if (flag == 4) {
+    option.UseGpu();
+    option.UsePaddleBackend();  // Paddle Inference
+  } else if (flag == 5) {
+    option.UseGpu();
+    option.UsePaddleInferBackend();
+    option.paddle_infer_option.enable_trt = true;
+    option.trt_option.SetShape("image", {1, 3, 640, 640}, {1, 3, 640, 640},
+                               {1, 3, 640, 640});
+    option.trt_option.SetShape("scale_factor", {1, 2}, {1, 2}, {1, 2});
+    option.trt_option.SetShape("im_shape", {1, 2}, {1, 2}, {1, 2});
+  } else if (flag == 6) {
+    option.UseGpu();
+    option.UseOrtBackend();  // ONNX Runtime
+  } else if (flag == 7) {
+    option.UseGpu();
+    option.UseTrtBackend();  // TensorRT
+  }
+
+  std::string model_dir = argv[1];
+  std::string image_dir = argv[2];
+  InitAndInfer(model_dir, image_dir, option);
+}