mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 03:46:40 +08:00
aa6931bee9
* add onnx_ort_runtime demo * rm in requirements * support batch eval * fixed MattingResults bug * move assignment for DetectionResult * integrated x2paddle * add model convert readme * update readme * re-lint * add processor api * Add MattingResult Free * change valid_cpu_backends order * add ppocr benchmark * mv bs from 64 to 32 * fixed quantize.md * fixed quantize bugs * Add Monitor for benchmark * update mem monitor * Set trt_max_batch_size default 1 * fixed ocr benchmark bug * support yolov5 in serving * Fixed yolov5 serving * Fixed postprocess * update yolov5 to 7.0 * add poros runtime demos * update readme * Support poros abi=1 * rm useless note * deal with comments * support pp_trt for ppseg * fixed symlink problem * Add is_mini_pad and stride for yolov5 * Add yolo series for paddle format * fixed bugs * fixed bug * support yolov5seg * fixed bug * refactor yolov5seg * fixed bug * mv Mask int32 to uint8 * add yolov5seg example * rm log info * fixed code style * add yolov5seg example in python * fixed dtype bug * update note * deal with comments * get sorted index * add yolov5seg test case * Add GPL-3.0 License * add round func * deal with comments * deal with commens Co-authored-by: Jason <jiangjiajun@baidu.com>
81 lines
2.7 KiB
C++
81 lines
2.7 KiB
C++
// 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/yolov5seg/yolov5seg.h"
|
|
|
|
namespace fastdeploy {
|
|
namespace vision {
|
|
namespace detection {
|
|
|
|
YOLOv5Seg::YOLOv5Seg(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::OPENVINO, Backend::ORT};
|
|
valid_gpu_backends = {Backend::ORT, Backend::TRT};
|
|
} else {
|
|
valid_cpu_backends = {Backend::PDINFER, Backend::ORT, Backend::LITE};
|
|
valid_gpu_backends = {Backend::PDINFER, Backend::ORT, Backend::TRT};
|
|
}
|
|
runtime_option = custom_option;
|
|
runtime_option.model_format = model_format;
|
|
runtime_option.model_file = model_file;
|
|
runtime_option.params_file = params_file;
|
|
initialized = Initialize();
|
|
}
|
|
|
|
bool YOLOv5Seg::Initialize() {
|
|
if (!InitRuntime()) {
|
|
FDERROR << "Failed to initialize fastdeploy backend." << std::endl;
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool YOLOv5Seg::Predict(const cv::Mat& im, DetectionResult* result) {
|
|
std::vector<DetectionResult> results;
|
|
if (!BatchPredict({im}, &results)) {
|
|
return false;
|
|
}
|
|
*result = std::move(results[0]);
|
|
return true;
|
|
}
|
|
|
|
bool YOLOv5Seg::BatchPredict(const std::vector<cv::Mat>& images, std::vector<DetectionResult>* results) {
|
|
std::vector<std::map<std::string, std::array<float, 2>>> ims_info;
|
|
std::vector<FDMat> fd_images = WrapMat(images);
|
|
|
|
if (!preprocessor_.Run(&fd_images, &reused_input_tensors_, &ims_info)) {
|
|
FDERROR << "Failed to preprocess the 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_, results, ims_info)) {
|
|
FDERROR << "Failed to postprocess the inference results by runtime." << std::endl;
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
} // namespace detection
|
|
} // namespace vision
|
|
} // namespace fastdeploy
|