MehmetOKUYAR

Augmentation_for_Yolo_labeling

Augmentation yolo format txt and images

Auto_video_label

Data is a huge factor in deep learning algorithms. The larger our data size, the better our model can generalize and learn. However, data preparation is a very laborious and time-consuming process. That's why I wanted to develop an application that I thought would make this stage easier. By using image processing techniques, it can track an object of your choice to a certain extent and saves the image and .txt file to the folder during tracking. Currently, it only works for one class and you can only label one object.

Convert-Mask-to-json-to-mask

If you are developing a segmentation model, you may need to convert your tags from json format to mask format. Thanks to the interface we have developed, you will be able to easily turn your labels into masks. Also, if you have masks and want to convert them to json format, you can easily do this with our application. This conversion comes to you in Mask R-CNN format, so if you have mask photos, you can easily convert them to .json files suitable for Mask R-CNN format. This convenience will allow you to convert the labels you have as you wish, even if they do not fit your format.

lane_segmentation

A model on lane detection has been developed with the data set we have created.

ubuntu-libs-kurulum

yapay zeka eğitimleri için gerkli kütüphanelerin kurulumları

Vehicles-Counting--Tracking-and-Speed-Estimation-with-YOLOv7-DeepSORT-Object-Tracking-and-Zone-Count

VideoSlicing

Data is a huge factor in deep learning algorithms. The larger the data, the better the model can learn. Thanks to this application, you can create a data set by dividing the videos you have taken into frames.

Yolo-Object-Detection-and-Distance-Measurement-with-Zed-camera

if you have a zed camera you can easily find the distance of the objects you have detected

yolov7_tensorrt_test

YoloV7 model on traffic sign detection has been developed with the dataset set we have created

Yolov8_Region_Create_and_Move_Count

MehmetOKUYAR/Vehicles-Counting--Tracking-and-Speed-Estimation-with-YOLOv7-DeepSORT-Object-Tracking-and-Zone-Count

MehmetOKUYAR/Yolo-Object-Detection-and-Distance-Measurement-with-Zed-camera

if you have a zed camera you can easily find the distance of the objects you have detected

MehmetOKUYAR/Auto_video_label

Data is a huge factor in deep learning algorithms. The larger our data size, the better our model can generalize and learn. However, data preparation is a very laborious and time-consuming process. That's why I wanted to develop an application that I thought would make this stage easier. By using image processing techniques, it can track an object of your choice to a certain extent and saves the image and .txt file to the folder during tracking. Currently, it only works for one class and you can only label one object.

MehmetOKUYAR/yolov7_tensorrt_test

YoloV7 model on traffic sign detection has been developed with the dataset set we have created

MehmetOKUYAR/lane_segmentation

A model on lane detection has been developed with the data set we have created.

MehmetOKUYAR/Yolov8_Region_Create_and_Move_Count

MehmetOKUYAR/Augmentation_for_Yolo_labeling

Augmentation yolo format txt and images

MehmetOKUYAR/ubuntu-libs-kurulum

yapay zeka eğitimleri için gerkli kütüphanelerin kurulumları

MehmetOKUYAR/VideoSlicing

Data is a huge factor in deep learning algorithms. The larger the data, the better the model can learn. Thanks to this application, you can create a data set by dividing the videos you have taken into frames.

MehmetOKUYAR/Convert-Mask-to-json-to-mask

If you are developing a segmentation model, you may need to convert your tags from json format to mask format. Thanks to the interface we have developed, you will be able to easily turn your labels into masks. Also, if you have masks and want to convert them to json format, you can easily do this with our application. This conversion comes to you in Mask R-CNN format, so if you have mask photos, you can easily convert them to .json files suitable for Mask R-CNN format. This convenience will allow you to convert the labels you have as you wish, even if they do not fit your format.

MehmetOKUYAR/convert_dcim2png

You can use dcim images to convert them to png format

MehmetOKUYAR/yolobbox2polygon

this is a dataset converter that takes YOLO bbox data and makes polygons using SAM-HQ!

MehmetOKUYAR/Auto-labeling-on-the-pre-trained-model

This function I wrote performs the image and txt saving process. You can also use this function on a model you have trained before. If your model works well enough, it will easily detect the images and record the labels. You can edit the recorded data and train with your new data quickly.

MehmetOKUYAR/crowd-analysis-from-istanbul-city-surveillance-cameras

MehmetOKUYAR/hifi3dface

Code and data for our paper "High-Fidelity 3D Digital Human Creation from RGB-D Selfies".

MehmetOKUYAR/labeling_images_with_trained_yolo_weight

MehmetOKUYAR/MehmetOKUYAR

My personal repository

MehmetOKUYAR/SplattingAvatar

[CVPR2024] Official implementation of SplattingAvatar.

MehmetOKUYAR/Train_Test_Split_txt

You can separate the images in your file as a train test txt file in the yolo format.

MehmetOKUYAR/Basler_VideoRecord

MehmetOKUYAR/darknet

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

MehmetOKUYAR/OOTDiffusion

Official implementation of OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-on

MehmetOKUYAR/RandomUserGenerator

Easy to generate user data

MehmetOKUYAR/sahi

A lightweight vision library for performing large scale object detection/ instance segmentation.

MehmetOKUYAR/segment-anything-annotator

We developed a python UI based on labelme and segment-anything for pixel-level annotation. It support multiple masks generation by SAM(box/point prompt), efficient polygon modification and category record. We will add more features (such as incorporating CLIP-based methods for category proposal and VOS methods for video datasets

MehmetOKUYAR/Semantic-Segmentation-Architecture

A repository contains the code for various semantic segmentation in TensorFlow and PyTorch framework.

MehmetOKUYAR/TTVS

Türkiye Trafik İşaretleri Veriseti - Turkish Traffic Sign Dataset

MehmetOKUYAR/yoloair

🔥🔥🔥YOLOv5, YOLOv6, YOLOv7, YOLOv8, PPYOLOE, YOLOX, YOLOR, YOLOv4, YOLOv3, Transformer, Attention, TOOD and Improved-YOLOv5-YOLOv7... Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀

MehmetOKUYAR/yoloair2

☁️💡🎈YOLOAir2 is the second version of the YOLOAir series, The framework is based on YOLOv7, including YOLOv7, YOLOv8, YOLOv6, YOLOv5, YOLOX, YOLOR, YOLOv4, YOLOv3, Transformer, Attention and Improved-YOLOv7... Support to improve Backbone, Neck, Head, Loss, IoU, NMS and other modules

MehmetOKUYAR/Yolov7-with-attention-modules

This project implement yolov7 from wongkinkiu with attention modules added