YOLO: Real-Time Object Detection

🔍🚀Discover YOLO: Real-Time Object Detection! 🤖⏰Known for its speed & accuracy, #YOLOv3 processes images 4 times faster than others, making predictions swiftly with a single network evaluation. 🌐🔥 #AI #ObjectDetection #RealTime #Tech

YOLO (You Only Look Once) is a real-time object detection system known for its speed and accuracy.
YOLOv3 is about 4 times faster in processing images compared to other detectors like Focal Loss.
YOLO applies a single neural network to the entire image, making predictions with a single network evaluation.
YOLOv3 offers multi-scale predictions and uses a better backbone classifier to enhance training and performance.
Darknet is used to run YOLO and can be installed by following simple commands for detection tasks.
YOLO allows you to change the speed and accuracy tradeoff by adjusting the model size without retraining.
YOLOv3-tiny is a smaller model suitable for resource-constrained environments.
To run YOLO in real-time, a webcam connected to the system is required along with CUDA and OpenCV for compilation.
YOLO can be trained on datasets like VOC or COCO for customized object detection tasks.
The model cfg files need to be adjusted for training on different datasets.
Running YOLO on COCO dataset involves obtaining the dataset, modifying cfg files, and initiating training.