fixed missing trt_backend option & remove un-need data layout check i…

…n Cast (#14)

* update .gitignore

* Added checking for cmake include dir

* fixed missing trt_backend option bug when init from trt

* remove un-need data layout and add pre-check for dtype

* changed RGB2BRG to BGR2RGB in ppcls model

* Update CMakeLists.txt

.gitignore

@@ -1 +1,12 @@
 fastdeploy/libs/lib*
+build
+cmake-build-debug
+cmake-build-release
+.vscode
+FastDeploy.cmake
+fastdeploy/core/config.h
+build-debug.sh
+*dist
+fastdeploy.egg-info
+.setuptools-cmake-build
+fastdeploy/version.py

fastdeploy/backends/tensorrt/trt_backend.cc

@@ -52,7 +52,8 @@ std::vector<int> toVec(const nvinfer1::Dims& dim) {
   return out;
 }
 
-bool TrtBackend::InitFromTrt(const std::string& trt_engine_file) {
+bool TrtBackend::InitFromTrt(const std::string& trt_engine_file, 
+                             const TrtBackendOption& option) {
   if (initialized_) {
     FDERROR << "TrtBackend is already initlized, cannot initialize again."
             << std::endl;

fastdeploy/backends/tensorrt/trt_backend.h

@@ -69,7 +69,8 @@ class TrtBackend : public BaseBackend {
   bool InitFromOnnx(const std::string& model_file,
                     const TrtBackendOption& option = TrtBackendOption(),
                     bool from_memory_buffer = false);
-  bool InitFromTrt(const std::string& trt_engine_file);
+  bool InitFromTrt(const std::string& trt_engine_file, 
+                   const TrtBackendOption& option = TrtBackendOption());
 
   bool Infer(std::vector<FDTensor>& inputs, std::vector<FDTensor>* outputs);
 

fastdeploy/vision/common/processors/cast.cc

@@ -18,30 +18,40 @@ namespace fastdeploy {
 namespace vision {
 
 bool Cast::CpuRun(Mat* mat) {
-  if (mat->layout != Layout::CHW) {
-    FDERROR << "Cast: The input data must be Layout::HWC format!" << std::endl;
-    return false;
-  }
   cv::Mat* im = mat->GetCpuMat();
+  int c = im->channels();
   if (dtype_ == "float") {
-    im->convertTo(*im, CV_32FC(im->channels()));
+    if (im->type() != CV_32FC(c)) {
+      im->convertTo(*im, CV_32FC(c));
+    }
   } else if (dtype_ == "double") {
-    im->convertTo(*im, CV_64FC(im->channels()));
+    if (im->type() != CV_64FC(c)) {
+      im->convertTo(*im, CV_64FC(c));
+    }
+  } else {
+    FDLogger() << "[WARN] Cast not support for " << dtype_ 
+               << " now! will skip this operation."
+               << std::endl;
   }
   return true;
 }
 
 #ifdef ENABLE_OPENCV_CUDA
 bool Cast::GpuRun(Mat* mat) {
-  if (mat->layout != Layout::CHW) {
-    FDERROR << "Cast: The input data must be Layout::HWC format!" << std::endl;
-    return false;
-  }
   cv::cuda::GpuMat* im = mat->GetGpuMat();
+  int c = im->channels();
   if (dtype_ == "float") {
-    im->convertTo(*im, CV_32FC(im->channels()));
+    if (im->type() != CV_32FC(c)) {
+      im->convertTo(*im, CV_32FC(c));
+    }
   } else if (dtype_ == "double") {
-    im->convertTo(*im, CV_64FC(im->channels()));
+    if (im->type() != CV_64FC(c)) {
+      im->convertTo(*im, CV_64FC(c));
+    }
+  } else {
+    FDLogger() << "[WARN] Cast not support for " << dtype_ 
+               << " now! will skip this operation."
+               << std::endl;
   }
   return true;
 }

fastdeploy/vision/ppcls/model.cc

@@ -44,7 +44,7 @@ bool Model::BuildPreprocessPipelineFromConfig() {
     return false;
   }
   auto preprocess_cfg = cfg["PreProcess"]["transform_ops"];
-  processors_.push_back(std::make_shared<RGB2BGR>());
+  processors_.push_back(std::make_shared<BGR2RGB>());
   for (const auto& op : preprocess_cfg) {
     FDASSERT(op.IsMap(),
              "Require the transform information in yaml be Map type.");