universax

FString AFDVActor::GetSequenceFilePath()
{
	FString output = "";
	FString AppName = FApp::GetProjectName();
	// Content Dir path
	FString ContentDir = FPaths::ProjectContentDir();
	UE_LOG(LogTemp, Log, TEXT("TAG: Content: %s"), *ContentDir);

	// Target path
	TArray<FString> tmpParsed;

universax

TArray<FString> GetAllFilesInDirectory(const FString directory, const bool fullPath, const bool withoutExtention, const FString onlyFilesStartingWith, const FString onlyFilesWithExtension)
{
	// Get all files in directory
	TArray<FString> directoriesToSkip;
	IPlatformFile& PlatformFile = FPlatformFileManager::Get().GetPlatformFile();
	FLocalTimestampDirectoryVisitor Visitor(PlatformFile, directoriesToSkip, directoriesToSkip, false);
	PlatformFile.IterateDirectory(*directory, Visitor);
	TArray<FString> files;
	for (TMap<FString, FDateTime>::TIterator TimestampIt(Visitor.FileTimes); TimestampIt; ++TimestampIt)
	{

universax

		// Write to file
		std::string rec_filename = "C:/Users/unive/Develop/kinect_data/depth/depth_" + std::to_string(framecount) + ".png";
		cv::imwrite(rec_filename, depth_mat, std::vector<int>(0));
		framecount++;
		printf("frame: %d\n", framecount);

universax

//---------------------------------
//	OSC
//---------------------------------
#include "OscReceivedElements.h"
#include "OscPacketListener.h"
#include "OscOutboundPacketStream.h"
#include "UdpSocket.h"
#include "IpEndpointName.h"

void sendOSCMessage(int id, float x, float y, float z)

universax

//
//  ViewController.m
//  VLC_Test
//
//  Created by YOHEI KAJIWARA on 2019/06/15.
//  Copyright © 2019 YOHEI KAJIWARA. All rights reserved.
//

#import "ViewController.h"
#import "MobileVLCKit/MobileVLCKit.h"

universax

#UINT8
tflite_convert \
--output_file="/home/user_name/output/mobilenet_v1_mymodel_frozen.tflite" \
--graph_def_file="/home/user_name/output/mobilenet_v1_mymodel_frozen.pb" \
--input_arrays=input \
--output_arrays=MobilenetV1/Predictions/Reshape_1 \
--default_ranges_min=0 \
--default_ranges_max=255 \
--inference_type=QUANTIZED_UINT8 \
--mean_values=128 \

universax

freeze_graph \
--input_graph="/home/user_name/output/mobilenet_v1_mymodel.pb" \
--input_binary=true \
--input_checkpoint="/home/user_name/train/model.ckpt-1000" \
--output_graph="/home/user_name/output/mobilenet_v1_mymodel_frozen.pb" \
--output_node_names=MobilenetV1/Predictions/Reshape_1

universax

python export_inference_graph.py \
--alsologtostderr \
--model_name=mobilenet_v1 \
--output_file="/home/user_name/output/mobilenet_v1_mymodel.pb" \
--dataset_name=mymodel

universax

# tensorflow/models/research/slim
# datasets needs to be converted to tfrecord format.
python train_image_classifier.py \
--train_dir "/home/user_name/train" \
--dataset_dir "/home/user_name/dataset" \
--model_name "mobilenet_v1" \
--dataset_name=mymodel \
--dataset_split_name=train \
--checkpoint_path "/home/user_name/mobilenet/mobilenet_v1_1.0_224.ckpt" \
--train_image_size=224 \

universax

find . -name '.DS_Store' -type f -ls -delete