Mehmet OKUYAR
@MehmetOKUYARI'm working about - Artificial inteligence researcher - Computer vision - Deep learning MSc Computer Engineering
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Erdal Özbademci
@eozbademci
Ömer Said Yilmaz
@omersaidylmz
Muhammad Rizwan Munawar
@RizwanMunawar
Furkan Taha Bademci
@FurkanTahaBademci
Kadir Nar
@kadirnar
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if you have a zed camera you can easily find the distance of the objects you have detected
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.
YoloV7 model on traffic sign detection has been developed with the dataset set we have created
A model on lane detection has been developed with the data set we have created.
This developed algorithm transforms mask labels used in previous segmentation tasks into a format compatible with YOLO's label requirements. As a result, pre-prepared datasets can be used with YOLO-like detection-focused architectures.
yapay zeka eğitimleri için gerkli kütüphanelerin kurulumları
You can increase your data size and training accuracy by cropping your labeled images to the model input size for large object detection.
Augmentation yolo format txt and images
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