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https://github.com/PaddlePaddle/FastDeploy.git
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[Other] Change all XPU to KunlunXin (#973)
* [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>
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@@ -48,12 +48,12 @@ void CpuInfer(const std::string& model_dir, const std::string& image_file) {
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std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
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}
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void XpuInfer(const std::string& model_dir, const std::string& image_file) {
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void KunlunXinInfer(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 + "deploy.yaml";
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auto option = fastdeploy::RuntimeOption();
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option.UseXpu();
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option.UseKunlunXin();
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auto model = fastdeploy::vision::segmentation::PaddleSegModel(
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model_file, params_file, config_file, option);
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@@ -142,7 +142,7 @@ int main(int argc, char* argv[]) {
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"e.g ./infer_model ./ppseg_model_dir ./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; 2: run with gpu and use tensorrt backend; 3: run with xpu."
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"with gpu; 2: run with gpu and use tensorrt backend; 3: run with kunlunxin."
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<< std::endl;
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return -1;
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}
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@@ -154,7 +154,7 @@ int main(int argc, char* argv[]) {
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} else if (std::atoi(argv[3]) == 2) {
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TrtInfer(argv[1], argv[2]);
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} else if (std::atoi(argv[3]) == 3) {
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XpuInfer(argv[1], argv[2]);
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KunlunXinInfer(argv[1], argv[2]);
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}
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return 0;
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}
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