[Hackthon_4th 242] Support en_ppstructure_mobile_v2.0_SLANet (#1816)

* first draft

* update api name

* fix bug

* fix bug and

* fix bug in c api

* fix bug in c_api

---------

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

fastdeploy/vision/ocr/ppocr/structurev2_table_preprocessor.cc

@@ -0,0 +1,105 @@
+// 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/ocr/ppocr/structurev2_table_preprocessor.h"
+
+#include "fastdeploy/function/concat.h"
+#include "fastdeploy/utils/perf.h"
+#include "fastdeploy/vision/ocr/ppocr/utils/ocr_utils.h"
+
+namespace fastdeploy {
+namespace vision {
+namespace ocr {
+
+StructureV2TablePreprocessor::StructureV2TablePreprocessor() {
+  resize_op_ = std::make_shared<Resize>(-1, -1);
+
+  std::vector<float> value = {0, 0, 0};
+  pad_op_ = std::make_shared<Pad>(0, 0, 0, 0, value);
+
+  std::vector<float> mean = {0.485f, 0.456f, 0.406f};
+  std::vector<float> std = {0.229f, 0.224f, 0.225f};
+  normalize_op_ = std::make_shared<Normalize>(mean, std, true);
+  hwc2chw_op_ = std::make_shared<HWC2CHW>();
+}
+
+void StructureV2TablePreprocessor::StructureV2TableResizeImage(FDMat* mat,
+                                                               int batch_idx) {
+  float img_h = float(rec_image_shape_[1]);
+  float img_w = float(rec_image_shape_[2]);
+  float width = float(mat->Width());
+  float height = float(mat->Height());
+  float ratio = max_len / (std::max(height, width) * 1.0);
+  int resize_h = int(height * ratio);
+  int resize_w = int(width * ratio);
+
+  resize_op_->SetWidthAndHeight(resize_w, resize_h);
+  (*resize_op_)(mat);
+
+  (*normalize_op_)(mat);
+  pad_op_->SetPaddingSize(0, int(max_len - resize_h), 0,
+                          int(max_len - resize_w));
+  (*pad_op_)(mat);
+
+  (*hwc2chw_op_)(mat);
+  batch_det_img_info_[batch_idx] = {int(width), int(height), resize_w,
+                                    resize_h};
+}
+
+bool StructureV2TablePreprocessor::Run(std::vector<FDMat>* images,
+                                       std::vector<FDTensor>* outputs,
+                                       size_t start_index, size_t end_index,
+                                       const std::vector<int>& indices) {
+  if (images->size() == 0 || end_index <= start_index ||
+      end_index > images->size()) {
+    FDERROR << "images->size() or index error. Correct is: 0 <= start_index < "
+               "end_index <= images->size()"
+            << std::endl;
+    return false;
+  }
+
+  std::vector<FDMat> mats(end_index - start_index);
+  for (size_t i = start_index; i < end_index; ++i) {
+    size_t real_index = i;
+    if (indices.size() != 0) {
+      real_index = indices[i];
+    }
+    mats[i - start_index] = images->at(real_index);
+  }
+  return Run(&mats, outputs);
+}
+
+bool StructureV2TablePreprocessor::Apply(FDMatBatch* image_batch,
+                                         std::vector<FDTensor>* outputs) {
+  batch_det_img_info_.clear();
+  batch_det_img_info_.resize(image_batch->mats->size());
+  for (size_t i = 0; i < image_batch->mats->size(); ++i) {
+    FDMat* mat = &(image_batch->mats->at(i));
+    StructureV2TableResizeImage(mat, i);
+  }
+
+  // Only have 1 output Tensor.
+  outputs->resize(1);
+  // Get the NCHW tensor
+  FDTensor* tensor = image_batch->Tensor();
+  (*outputs)[0].SetExternalData(tensor->Shape(), tensor->Dtype(),
+                                tensor->Data(), tensor->device,
+                                tensor->device_id);
+
+  return true;
+}
+
+}  // namespace ocr
+}  // namespace vision
+}  // namespace fastdeploy