MdJafirAshraf/Object_detection_yolo_vs_mobilenet
Object detection is detecting and recognizing the object. It is one of the common applications in computer vision problems (like traffic signals, people tracking, vehicle detection, etc...). In this repo, I develop real-time object detection with pre-trained models. These are YOLO version 3 and SSD MobileNet version 3. And I used coco large dataset for detecting labels, which are a total of 80 labels.
This project helps operations engineers and anyone monitoring real-world environments by detecting and recognizing objects in live video feeds. It takes video input and outputs a video stream with identified objects (like people, vehicles, or traffic signals) highlighted and labeled in real-time. This is ideal for applications like tracking traffic or monitoring crowded spaces.
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Use this if you need to identify and track common objects in a live video feed, especially for safety, surveillance, or traffic management.
Not ideal if you need to detect highly specific or uncommon objects not included in a general dataset of 80 labels, or if you require extremely high precision for very small or complex objects.
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Dec 10, 2021
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