PaddleOCR/deploy/fastdeploy/cpu-gpu/cpp/infer_rec.cc

84 lines
2.5 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.h"
#ifdef WIN32
const char sep = '\\';
#else
const char sep = '/';
#endif
void InitAndInfer(const std::string &rec_model_dir,
const std::string &rec_label_file,
const std::string &image_file,
const fastdeploy::RuntimeOption &option) {
auto rec_model_file = rec_model_dir + sep + "inference.pdmodel";
auto rec_params_file = rec_model_dir + sep + "inference.pdiparams";
auto rec_option = option;
auto rec_model = fastdeploy::vision::ocr::Recognizer(
rec_model_file, rec_params_file, rec_label_file, rec_option);
assert(rec_model.Initialized());
auto im = cv::imread(image_file);
auto im_bak = im.clone();
fastdeploy::vision::OCRResult result;
if (!rec_model.Predict(im, &result)) {
std::cerr << "Failed to predict." << std::endl;
return;
}
// User can infer a batch of images by following code.
// if (!rec_model.BatchPredict({im}, &result)) {
// std::cerr << "Failed to predict." << std::endl;
// return;
// }
std::cout << result.Str() << std::endl;
}
int main(int argc, char *argv[]) {
if (argc < 5) {
std::cout << "Usage: infer_demo"
"path/to/rec_model path/to/rec_label_file path/to/image "
"run_option, "
"e.g ./infer_demo "
"./ch_PP-OCRv3_rec_infer "
"./ppocr_keys_v1.txt ./12.jpg 0"
<< std::endl;
std::cout << "The data type of run_option is int, 0: run with cpu; 1: run "
"with gpu;"
<< std::endl;
return -1;
}
fastdeploy::RuntimeOption option;
int flag = std::atoi(argv[4]);
if (flag == 0) {
option.UseCpu();
} else if (flag == 1) {
option.UseGpu();
}
std::string rec_model_dir = argv[1];
std::string rec_label_file = argv[2];
std::string test_image = argv[3];
InitAndInfer(rec_model_dir, rec_label_file, test_image, option);
return 0;
}