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common/model_loader.cpp

@@ -0,0 +1,92 @@
+// -------------------------------------------------------------------------
+// Exposed Functions
+// -------------------------------------------------------------------------
+
+#include "model_loader.h"
+#include <cstring>
+#include <iostream>
+#include <vector>
+#include <tuple>
+
+#define LOGE(...) do { fprintf(stderr, __VA_ARGS__); fprintf(stderr, "\n"); } while(0)
+
+void* init_network(const char* model_path) {
+    void* qcontext = NULL;
+    aml_config config;
+    memset(&config, 0, sizeof(aml_config));
+    config.modelType = ADLA_LOADABLE;
+    config.typeSize = sizeof(aml_config);
+    config.nbgType = NN_ADLA_FILE;
+    config.path = model_path;
+
+      /* set omp, If you are considering high CPU usage during operation,
+       you can turn off this api, set_openmp_opt_flag = false */
+    aml_openmp_opt_t openmp_opt[] =
+    {
+        {
+           .operator_type = AML_Unknown,
+           .enable_openmp = true,
+           .involve_all_ops = true,
+           .openmp_num = 2,
+        },
+    };
+    config.forward_ctrl.softop_info.set_openmp_opt_flag = true;
+    config.forward_ctrl.softop_info.openmp_opt_num = sizeof(openmp_opt) / sizeof(aml_openmp_opt_t);
+    config.forward_ctrl.softop_info.openmp_opt = openmp_opt;
+ 
+    /* set neon */
+    aml_neon_opt_t neon_opt[] =
+    {
+        {
+           .operator_type = AML_Unknown,
+           .enable_neon = true,
+           .involve_all_ops = true,
+        },
+ 
+    };
+    config.forward_ctrl.softop_info.set_neon_opt_flag = true;
+    config.forward_ctrl.softop_info.neon_opt_num = sizeof(neon_opt) / sizeof(aml_neon_opt_t);
+    config.forward_ctrl.softop_info.neon_opt = neon_opt;
+    
+    qcontext = aml_module_create(&config);
+    if (NULL == qcontext) {
+        LOGE("aml_module_create fail for %s", model_path);
+        return NULL;
+    }
+    return qcontext;
+}
+
+int uninit_network(void* qcontext) {
+    int ret = aml_module_destroy(qcontext);
+    if (ret) {
+        LOGE("aml_module_destroy fail.");
+        return -1;
+    }   
+    return ret;
+}
+
+void* run_network(void* qcontext, std::vector<std::tuple<cv::Mat, float, std::tuple<int, int>>> input_tuples) {
+    for (size_t i = 0; i < input_tuples.size(); ++i) {
+        cv::Mat process_img = std::get<0>(input_tuples[i]);
+        unsigned char* rawdata = process_img.data;
+
+        nn_input inData;
+        memset(&inData, 0, sizeof(nn_input));
+        inData.input_type = BINARY_RAW_DATA;
+        inData.input = rawdata;
+        inData.input_index = i;
+        inData.size = process_img.rows * process_img.cols * process_img.channels() * sizeof(float);
+
+        int ret = aml_module_input_set(qcontext, &inData);
+        if (ret) {
+            LOGE("aml_module_input_set fail for index %zu. Ret=%d", i, ret);
+            return NULL;
+        }
+    }
+
+    aml_output_config_t outconfig;
+    memset(&outconfig, 0, sizeof(aml_output_config_t));
+    outconfig.typeSize = sizeof(aml_output_config_t);
+    outconfig.format = AML_OUTDATA_FLOAT32;
+    return aml_module_output_get(qcontext, outconfig);
+}