Add RKYOLOv5 RKYOLOX RKYOLOV7 (#709)

* 更正代码格式

* 更正代码格式

* 修复语法错误

* fix rk error

* update

* update

* update

* update

* update

* update

* update

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

fastdeploy/vision/detection/contrib/rknpu2/preprocessor.cc

@@ -0,0 +1,127 @@
+// 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/detection/contrib/rknpu2/preprocessor.h"
+#include "fastdeploy/function/concat.h"
+
+namespace fastdeploy {
+namespace vision {
+namespace detection {
+
+RKYOLOPreprocessor::RKYOLOPreprocessor() {
+  size_ = {640, 640};
+  padding_value_ = {114.0, 114.0, 114.0};
+  is_mini_pad_ = false;
+  is_no_pad_ = false;
+  is_scale_up_ = true;
+  stride_ = 32;
+  max_wh_ = 7680.0;
+}
+
+void RKYOLOPreprocessor::LetterBox(FDMat* mat) {
+  std::cout << "mat->Height() = " << mat->Height() << std::endl;
+  std::cout << "mat->Width() = " << mat->Width() << std::endl;
+
+  float scale =
+      std::min(size_[1] * 1.0 / mat->Height(), size_[0] * 1.0 / mat->Width());
+  std::cout << "RKYOLOPreprocessor scale_ = " << scale << std::endl;
+  if (!is_scale_up_) {
+    scale = std::min(scale, 1.0f);
+  }
+  std::cout << "RKYOLOPreprocessor scale_ = " << scale << std::endl;
+  scale_.push_back(scale);
+
+  int resize_h = int(round(mat->Height() * scale));
+  int resize_w = int(round(mat->Width() * scale));
+
+  int pad_w = size_[0] - resize_w;
+  int pad_h = size_[1] - resize_h;
+  if (is_mini_pad_) {
+    pad_h = pad_h % stride_;
+    pad_w = pad_w % stride_;
+  } else if (is_no_pad_) {
+    pad_h = 0;
+    pad_w = 0;
+    resize_h = size_[1];
+    resize_w = size_[0];
+  }
+
+  pad_hw_values_.push_back({pad_h,pad_w});
+
+  if (std::fabs(scale - 1.0f) > 1e-06) {
+    Resize::Run(mat, resize_w, resize_h);
+  }
+  if (pad_h > 0 || pad_w > 0) {
+    float half_h = pad_h * 1.0 / 2;
+    int top = int(round(half_h - 0.1));
+    int bottom = int(round(half_h + 0.1));
+    float half_w = pad_w * 1.0 / 2;
+    int left = int(round(half_w - 0.1));
+    int right = int(round(half_w + 0.1));
+    Pad::Run(mat, top, bottom, left, right, padding_value_);
+  }
+}
+
+bool RKYOLOPreprocessor::Preprocess(FDMat* mat, FDTensor* output) {
+  // process after image load
+//  float ratio = std::min(size_[1] * 1.0f / static_cast<float>(mat->Height()),
+//                         size_[0] * 1.0f / static_cast<float>(mat->Width()));
+//  if (std::fabs(ratio - 1.0f) > 1e-06) {
+//    int interp = cv::INTER_AREA;
+//    if (ratio > 1.0) {
+//      interp = cv::INTER_LINEAR;
+//    }
+//    int resize_h = int(mat->Height() * ratio);
+//    int resize_w = int(mat->Width() * ratio);
+//    Resize::Run(mat, resize_w, resize_h, -1, -1, interp);
+//  }
+
+  // RKYOLO's preprocess steps
+  // 1. letterbox
+  // 2. convert_and_permute(swap_rb=true)
+  LetterBox(mat);
+  BGR2RGB::Run(mat);
+  mat->ShareWithTensor(output);
+  output->ExpandDim(0); // reshape to n, h, w, c
+  return true;
+}
+
+bool RKYOLOPreprocessor::Run(std::vector<FDMat>* images,
+                             std::vector<FDTensor>* outputs) {
+  if (images->size() == 0) {
+    FDERROR << "The size of input images should be greater than 0."
+            << std::endl;
+    return false;
+  }
+  outputs->resize(1);
+  // Concat all the preprocessed data to a batch tensor
+  std::vector<FDTensor> tensors(images->size());
+  for (size_t i = 0; i < images->size(); ++i) {
+    if (!Preprocess(&(*images)[i], &tensors[i])) {
+      FDERROR << "Failed to preprocess input image." << std::endl;
+      return false;
+    }
+  }
+
+  if (tensors.size() == 1) {
+    (*outputs)[0] = std::move(tensors[0]);
+  } else {
+    function::Concat(tensors, &((*outputs)[0]), 0);
+  }
+  return true;
+}
+
+} // namespace detection
+} // namespace vision
+} // namespace fastdeploy