mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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a51e5a6e55
* [Android] Add Android build docs and demo (#26) * [Backend] Add override flag to lite backend * [Docs] Add Android C++ SDK build docs * [Doc] fix android_build_docs typos * Update CMakeLists.txt * Update android.md * [Doc] Add PicoDet Android demo docs * [Doc] Update PicoDet Andorid demo docs * [Doc] Update PaddleClasModel Android demo docs * [Doc] Update fastdeploy android jni docs * [Doc] Update fastdeploy android jni usage docs * [Android] init fastdeploy android jar package * [Backend] support int8 option for lite backend * [Model] add Backend::Lite to paddle model * [Backend] use CopyFromCpu for lite backend. * [Android] package jni srcs and java api into aar * Update infer.cc * Update infer.cc * [Android] Update package build.gradle * [Android] Update android app examples * [Android] update android detection app
99 lines
3.2 KiB
C++
99 lines
3.2 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "fastdeploy/vision.h"
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#ifdef WIN32
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const char sep = '\\';
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#else
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const char sep = '/';
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#endif
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void CpuInfer(const std::string& model_dir, const std::string& image_file) {
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auto model_file = model_dir + sep + "model.pdmodel";
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auto params_file = model_dir + sep + "model.pdiparams";
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auto config_file = model_dir + sep + "infer_cfg.yml";
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auto option = fastdeploy::RuntimeOption();
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option.UseCpu();
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auto model = fastdeploy::vision::detection::FasterRCNN(
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model_file, params_file, config_file, option);
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if (!model.Initialized()) {
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std::cerr << "Failed to initialize." << std::endl;
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return;
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}
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auto im = cv::imread(image_file);
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auto im_bak = im.clone();
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fastdeploy::vision::DetectionResult res;
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if (!model.Predict(&im, &res)) {
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std::cerr << "Failed to predict." << std::endl;
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return;
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}
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std::cout << res.Str() << std::endl;
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auto vis_im = fastdeploy::vision::Visualize::VisDetection(im_bak, res, 0.5);
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cv::imwrite("vis_result.jpg", vis_im);
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std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
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}
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void GpuInfer(const std::string& model_dir, const std::string& image_file) {
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auto model_file = model_dir + sep + "model.pdmodel";
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auto params_file = model_dir + sep + "model.pdiparams";
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auto config_file = model_dir + sep + "infer_cfg.yml";
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auto option = fastdeploy::RuntimeOption();
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option.UseGpu();
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auto model = fastdeploy::vision::detection::FasterRCNN(
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model_file, params_file, config_file, option);
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if (!model.Initialized()) {
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std::cerr << "Failed to initialize." << std::endl;
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return;
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}
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auto im = cv::imread(image_file);
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auto im_bak = im.clone();
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fastdeploy::vision::DetectionResult res;
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if (!model.Predict(&im, &res)) {
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std::cerr << "Failed to predict." << std::endl;
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return;
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}
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std::cout << res.Str() << std::endl;
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auto vis_im = fastdeploy::vision::Visualize::VisDetection(im_bak, res, 0.5);
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cv::imwrite("vis_result.jpg", vis_im);
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std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
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}
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int main(int argc, char* argv[]) {
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if (argc < 4) {
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std::cout
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<< "Usage: infer_demo path/to/model_dir path/to/image run_option, "
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"e.g ./infer_model ./faster_rcnn_r50_vd_fpn_2x_coco ./test.jpeg 0"
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<< std::endl;
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std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
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"with gpu."
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<< std::endl;
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return -1;
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}
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if (std::atoi(argv[3]) == 0) {
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CpuInfer(argv[1], argv[2]);
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} else if (std::atoi(argv[3]) == 1) {
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GpuInfer(argv[1], argv[2]);
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}
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return 0;
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}
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