Object detection using YOLO v4 and pre trained model | Deep Learning Tutorial 32 (Tensorflow)

In this video we will use YOLO V4 and use pretrained weights to detect object boundaries in an image. The model was trained on COCO dataset using YOLO V4.

Watch this to understand how yolo algorithm works: https://www.youtube.com/watch?v=ag3DLKsl2vk

Windows setup instructions: https://github.com/AlexeyAB/darknet#how-to-compile-on-windows-using-cmake

Above, I was getting errors when I used .\build.ps1 command but using following command instead worked:
powershell -ExecutionPolicy Bypass -File .\build.ps1

Make sure you are installing a compatible version of CUDA. For me it was CUDA 10.1, when I installed 11.x version I was getting all kind of errors so had to downgrade it to 10.1 Based on your system you might have to use a different version

download yolov4.weights from https://github.com/AlexeyAB/darknet#how-to-evaluate-ap-of-yolov4-on-the-ms-coco-evaluation-server

COCO labels:
https://tech.amikelive.com/node-718/what-object-categories-labels-are-in-coco-dataset/

YOLO research papers

YOLO v1: https://arxiv.org/abs/1506.02640
YOLO v2: https://arxiv.org/abs/1612.08242
YOLO v3: https://arxiv.org/abs/1804.02767

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#objectdetectionusingyolo #yoloobjectdetection #yolov4objectdetection #yoloalgorithm #yolov4 #yolodeeplearning

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Видео Object detection using YOLO v4 and pre trained model | Deep Learning Tutorial 32 (Tensorflow) канала codebasics