108 lines
3.5 KiB
C++
Executable file
108 lines
3.5 KiB
C++
Executable file
// -------------------------------------------------------------------------
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// Exposed Functions
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// -------------------------------------------------------------------------
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/*
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* Copyright (C) 2026 Amlogic, Inc. 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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*/
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#include "model_loader.h"
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#include <cstring>
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#include <iostream>
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#include <vector>
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#include <tuple>
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#define LOGE(...) do { fprintf(stderr, __VA_ARGS__); fprintf(stderr, "\n"); } while(0)
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void* init_network(const char* model_path) {
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void* qcontext = NULL;
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aml_config config;
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memset(&config, 0, sizeof(aml_config));
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config.modelType = ADLA_LOADABLE;
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config.typeSize = sizeof(aml_config);
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config.nbgType = NN_ADLA_FILE;
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config.path = model_path;
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/* set omp, If you are considering high CPU usage during operation,
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you can turn off this api, set_openmp_opt_flag = false */
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aml_openmp_opt_t openmp_opt[] =
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{
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{
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.operator_type = AML_Unknown,
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.enable_openmp = true,
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.involve_all_ops = true,
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.openmp_num = 2,
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},
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};
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config.forward_ctrl.softop_info.set_openmp_opt_flag = true;
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config.forward_ctrl.softop_info.openmp_opt_num = sizeof(openmp_opt) / sizeof(aml_openmp_opt_t);
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config.forward_ctrl.softop_info.openmp_opt = openmp_opt;
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/* set neon */
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aml_neon_opt_t neon_opt[] =
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{
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{
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.operator_type = AML_Unknown,
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.enable_neon = true,
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.involve_all_ops = true,
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},
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};
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config.forward_ctrl.softop_info.set_neon_opt_flag = true;
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config.forward_ctrl.softop_info.neon_opt_num = sizeof(neon_opt) / sizeof(aml_neon_opt_t);
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config.forward_ctrl.softop_info.neon_opt = neon_opt;
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qcontext = aml_module_create(&config);
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if (NULL == qcontext) {
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LOGE("aml_module_create fail for %s", model_path);
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return NULL;
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}
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return qcontext;
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}
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int uninit_network(void* qcontext) {
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int ret = aml_module_destroy(qcontext);
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if (ret) {
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LOGE("aml_module_destroy fail.");
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return -1;
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}
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return ret;
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}
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void* run_network(void* qcontext, std::vector<std::tuple<cv::Mat, float, std::tuple<int, int>>> input_tuples) {
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for (size_t i = 0; i < input_tuples.size(); ++i) {
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cv::Mat process_img = std::get<0>(input_tuples[i]);
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unsigned char* rawdata = process_img.data;
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nn_input inData;
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memset(&inData, 0, sizeof(nn_input));
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inData.input_type = BINARY_RAW_DATA;
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inData.input = rawdata;
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inData.input_index = i;
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inData.size = process_img.rows * process_img.cols * process_img.channels() * sizeof(float);
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int ret = aml_module_input_set(qcontext, &inData);
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if (ret) {
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LOGE("aml_module_input_set fail for index %zu. Ret=%d", i, ret);
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return NULL;
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}
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}
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aml_output_config_t outconfig;
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memset(&outconfig, 0, sizeof(aml_output_config_t));
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outconfig.typeSize = sizeof(aml_output_config_t);
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outconfig.format = AML_OUTDATA_FLOAT32;
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return aml_module_output_get(qcontext, outconfig);
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}
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