Weighted box fusion: The post-processing step is a trivial yet important component in object detection. In this article, we will demonstrate the significance of Weighted Boxes Fusion (WBF) as opposed ...
PaddlePaddle: Exploring Object Detection, Segmentation, and Keypoints
PaddlePaddle: Welcome to our guide of machine learning frameworks, where we'll examine PaddlePaddle, TensorFlow, and PyTorch. Recent benchmark tests have revealed PaddlePaddle as a potential ...
IoU Loss Functions for Faster & More Accurate Object Detection
Object detection is one of the most important challenges in computer vision. Deep learning-based solutions can solve it very effectively. To solve any problem using deep learning, first, we need to ...
Exploring SAHI: Slicing Aided Hyper Inference for Small Object Detection
Small object detection refers to the task of identifying and localizing objects that are relatively small in size within digital images. These objects typically have limited spatial extent and low ...
Train YOLO NAS on Custom Dataset
YOLO-NAS is currently the latest YOLO object detection model. From the outset, it beats all other YOLO models in terms of accuracy. The pretrained YOLO-NAS models detect more objects with better ...
Train YOLOv8 Instance Segmentation on Custom Data
Image segmentation is a core vision problem that can provide a solution for a large number of use cases. Starting from medical imaging to analyzing traffic, it has immense potential. Instance ...