Yolov4

YOLO (You Only Look Once) is an object detection algorithm that can detect objects in images and videos in real time. It was first introduced in 2016 by Joseph Redmon et al. YOLO divides an image into a grid of cells and predicts bounding boxes and class probabilities for each…

Aerial images, taken from drones or planes, have a wide range of applications such as urban planning, disaster management, and wildlife conservation. However, analyzing these images can be a time-consuming task, especially when it comes to detecting specific objects such as buildings, cars, and people. …

“One Rotten Apple Spoils the Whole Barrel” Can one rotten apple really spoil the whole barrel? The answer is Yes. Once an apple is rotten or has physical damage, some chemical reactions will take place. In turn, it leads to a slightly increased internal temperature. Then a component of fiber, that cements the cell walls together, begins…

To set up and train a YOLO v5 object detection model, you will need to follow these steps: Install the necessary libraries and dependencies. This will typically include TensorFlow, NumPy, and OpenCV. You may also need to install additional libraries depending on your operating system and configuration. Download the YOLO…

AUTOMATIC LICENSE PLATE RECOGNITION FOR ETHIOPIAN ROADS USING YOLO

Hello folks, it’s been long when we last talked. I went afar from Machine Learning as my employer demanded and indulged myself into Full-stack development of web applications. But, that’s there. We will learn how to train a dataset using Darknet and OpenCV, on NVIDIA CUDA platform. I will assume…

In this article, we will learn to use EfficientDet Models in Android with images from a gallery or camera. So in the application 1: The user can choose images from the gallery 2: Or capture images using the camera 3: Then that image will be passed to our Efficientdet model …

Training TinyYOLOv4 using a Pot Hole Dataset Introduction In this note, we implement the tiny version of YOLOv4 for training our public [Pot Hole Dataset] which consists of 665 images(https://public.roboflow.com/object-detection/pothole), YOLOv4 tiny. We also recommend reading our blog post on Training YOLOv4 on custom data side by side. We will take the following steps to implement YOLOv4 on…

by Hans Sometimes math work is more important than code optimizaion. First thing is logic or math, code optimization is the last thing to do. There is a case here. Math problem explanation On an edge-AI SoC, it may come with a NPU or DLA core playing an important role in the system…