The backbone of every computer vision application is the data used. The quality of data determines how good the final application will perform. It is needless to say that sometimes we need to collect ...
YOLOR – Paper Explanation & Inference – An In-Depth Analysis
In recent years, we have seen tremendous progress in the YOLO series, now hosting both anchor-free and anchor-based object detection models. Instead of focusing solely on architectural changes, YoloR ...
YOLOX Object Detector Paper Explanation and Custom Training
What is YOLOX? YOLOX is a single-stage real-time object detector. It was introduced in the paper YOLOX: Exceeding YOLO Series in 2021. The baseline model of YOLOX is YOLOv3 SPP with Darknet53 ...
Document Segmentation Using Deep Learning in PyTorch
Document Scanning is a background segmentation problem that can be solved using various methods. It is one of the extensively used applications of computer vision. In this article, we are considering ...
Fine Tuning YOLOv7 on Custom Dataset
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 ...
Center Stage for Zoom Calls Using MediaPipe
Today we are going to walk you through the implementation of Center Stage as seen in Apple iPads, iMacs, and MacBooks. We will be using the following: ✅ MediaPipe to track the person ✅ OpenCV for ...
