The YOLOv7 is making big waves in the computer vision and also the machine learning communities.This new YOLOv7 algorithm has a very fast CNN (convolutional Neural Network) surpasses all previous object detection models and YOLO versions in both speed,FPS and Acuraccy.This neural network are trained much faster on small datasets without any pretrained weights. 2. YOLO FOR REAL-TIME OBJECT DETECTION: Real Time object detection is very important in computer vision and aslo a very important task that is often a key component in computer vision systems.Video analysis use real time object detection , robotics , autonomous vehicles,multi-object tracking and object counting etc.Object detector is an object detection algorithm that performs image recognition tasks by taking an image as input and predicting the boundary boxes and also classes for each object in the image.Most algorithm used are CNN(Convolutional Neural Network) to extract features from the image to predict the probablility of learned classes.The video below show YOLOv7 algoritm deployed on a life video of a highway in Lagos,Nigeria.The algorithm is able to detect objects found in the video.
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