What is YOLOv7? YOLOv7 is a single-stage real-time object detector. It was introduced to the YOLO family in July'22. According to the YOLOv7 paper, it is the fastest and most accurate real-time ...
Since its inception, the YOLO family of object detection models has come a long way. YOLOv7 is the most recent addition to this famous anchor-based single-shot family of object detectors. It comes ...
In this blog post, we are fine tuning YOLOv5 models for custom object detection training and inference. Introduction The field of deep learning started taking off in 2012. Around that time, ...
In this blog post, we will be training YOLOv4 object detection model on a pothole detection dataset using the Darknet framework. Before we move further, let’s have an overview of the models that ...
Mean Average Precision (mAP) is a performance metric used for evaluating machine learning models. It is the most popular metric that is used by benchmark challenges such as PASCAL VOC, COCO, ImageNET ...
YOLOv3 is one of the most popular real-time object detectors in Computer Vision. In our previous post, we shared how to use YOLOv3 in an OpenCV application. It was very well received, and many ...
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In 2007, right after finishing my Ph.D., I co-founded TAAZ Inc. with my advisor Dr. David Kriegman and Kevin Barnes. The scalability, and robustness of our computer vision and machine learning algorithms have been put to rigorous test by more than 100M users who have tried our products.
