mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-11-01 04:12:58 +08:00
45865c8724
* [FlyCV] Bump up FlyCV -> official release 1.0.0 * XPU to KunlunXin * update * update model link * update doc * update device * update code * useless code Co-authored-by: DefTruth <qiustudent_r@163.com> Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
90 lines
3.1 KiB
C++
Executable File
90 lines
3.1 KiB
C++
Executable File
// 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/dbdetector.h"
|
|
#include "fastdeploy/utils/perf.h"
|
|
#include "fastdeploy/vision/ocr/ppocr/utils/ocr_utils.h"
|
|
|
|
namespace fastdeploy {
|
|
namespace vision {
|
|
namespace ocr {
|
|
|
|
DBDetector::DBDetector() {}
|
|
DBDetector::DBDetector(const std::string& model_file,
|
|
const std::string& params_file,
|
|
const RuntimeOption& custom_option,
|
|
const ModelFormat& model_format) {
|
|
if (model_format == ModelFormat::ONNX) {
|
|
valid_cpu_backends = {Backend::ORT,
|
|
Backend::OPENVINO};
|
|
valid_gpu_backends = {Backend::ORT, Backend::TRT};
|
|
} else {
|
|
valid_cpu_backends = {Backend::PDINFER, Backend::ORT, Backend::OPENVINO, Backend::LITE};
|
|
valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT};
|
|
valid_kunlunxin_backends = {Backend::LITE};
|
|
valid_ascend_backends = {Backend::LITE};
|
|
}
|
|
|
|
runtime_option = custom_option;
|
|
runtime_option.model_format = model_format;
|
|
runtime_option.model_file = model_file;
|
|
runtime_option.params_file = params_file;
|
|
initialized = Initialize();
|
|
}
|
|
|
|
// Init
|
|
bool DBDetector::Initialize() {
|
|
if (!InitRuntime()) {
|
|
FDERROR << "Failed to initialize fastdeploy backend." << std::endl;
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool DBDetector::Predict(const cv::Mat& img,
|
|
std::vector<std::array<int, 8>>* boxes_result) {
|
|
std::vector<std::vector<std::array<int, 8>>> det_results;
|
|
if (!BatchPredict({img}, &det_results)) {
|
|
return false;
|
|
}
|
|
*boxes_result = std::move(det_results[0]);
|
|
return true;
|
|
}
|
|
|
|
bool DBDetector::BatchPredict(const std::vector<cv::Mat>& images,
|
|
std::vector<std::vector<std::array<int, 8>>>* det_results) {
|
|
std::vector<FDMat> fd_images = WrapMat(images);
|
|
std::vector<std::array<int, 4>> batch_det_img_info;
|
|
if (!preprocessor_.Run(&fd_images, &reused_input_tensors_, &batch_det_img_info)) {
|
|
FDERROR << "Failed to preprocess input image." << std::endl;
|
|
return false;
|
|
}
|
|
|
|
reused_input_tensors_[0].name = InputInfoOfRuntime(0).name;
|
|
if (!Infer(reused_input_tensors_, &reused_output_tensors_)) {
|
|
FDERROR << "Failed to inference by runtime." << std::endl;
|
|
return false;
|
|
}
|
|
|
|
if (!postprocessor_.Run(reused_output_tensors_, det_results, batch_det_img_info)) {
|
|
FDERROR << "Failed to postprocess the inference cls_results by runtime." << std::endl;
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
} // namesapce ocr
|
|
} // namespace vision
|
|
} // namespace fastdeploy
|