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/*
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* Programming introduction with the SOD Embedded RealNets Model Training API.
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* Training must be enabled via the compile-time directive SOD_ENABLE_NET_TRAIN.
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*
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* Copyright (C) PixLab | Symisc Systems, https://sod.pixlab.io
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*/
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/*
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* Compile this file together with the SOD embedded source code to generate
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* the executable. For example:
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*
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* gcc sod.c realnet_train_model.c -D SOD_ENABLE_NET_TRAIN -lm -Ofast -march=native -Wall -std=c99 -o sod_realnet_train_intro
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*
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* Under Microsoft Visual Studio (>= 2015), just drop `sod.c` and its accompanying
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* header files on your source tree and you're done. If you have any trouble
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* integrating SOD in your project, please submit a support request at:
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* https://sod.pixlab.io/support.html
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*/
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/*
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* This simple program is a quick introduction on how to embed and start
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* experimenting with SOD without having to do a lot of tedious
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* reading and configuration.
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*
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* Make sure you have the latest release of SOD from:
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* https://pixlab.io/downloads
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* The SOD Embedded C/C++ documentation is available at:
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* https://sod.pixlab.io/api.html
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*/
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#include <stdio.h>
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#include "sod.h"
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/*
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* Training log consumer callback that should be called
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* by the Realnet trainer to report training progress.
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*/
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void log_consumer_callback(const char *zText, size_t text_len, void *pUserdata)
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{
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/* Simply redirect to stdout */
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puts(zText);
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}
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int main(int argc, char *argv[])
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{
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/* Training instructions (i.e. where positive and negative samples
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* are located, tree minimal depth, max trees, model copyright notice and so on).
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* Pass a path or download one from https://pixlab.io/downloads
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*/
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const char *zTrainFile = argc > 1 ? argv[1] : "train.txt";
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/*
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* Relanet trainer handle
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*/
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sod_realnet_trainer *pNet;
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int rc;
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/* Allocate a new Realnet Trainer handle */
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rc = sod_realnet_train_init(&pNet);
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if (rc != SOD_OK) return rc;
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/*
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* Install our training progress log consumer callback.
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*/
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rc = sod_realnet_train_config(pNet, SOD_REALNET_TR_LOG_CALLBACK, log_consumer_callback, 0);
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if (rc != SOD_OK) return rc;
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/*
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* Where to store the output model.
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*/
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rc = sod_realnet_train_config(pNet, SOD_REALNET_TR_OUTPUT_MODEL, "./pedestrian_detetcor.realnet");
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if (rc != SOD_OK) return rc;
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/*
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* Start the heavy training process on your CPU driven by
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* the Realnet instructions found on `zTrainFile`.
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*/
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rc = sod_realnet_train_start(pNet, zTrainFile);
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/* Wait some days...*/
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sod_realnet_train_release(pNet);
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/* check the progress log and you should find
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* a working model on the path you specified earlier.
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*/
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return rc;
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}
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