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Bringing object detection from YouTube video into focus Object detection from youtube video is all about teaching your code to “see” what is happening inside an online video stream.Instead of manually downloading a file and running offline analysis, you connect directly to a YouTube URL, grab each frame in real time, and let a deep […]
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Getting started with YOLOv8 dental object detection In modern dentistry, X-rays are no longer just static images on a screen. With yolov8 dental object detection, those images can be transformed into structured data that highlights teeth, restorations, lesions, and other findings automatically. Instead of manually scanning every millimeter of a radiograph, a trained YOLOv8 model
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Understanding EigenCAM in Deep Learning EigenCAM is a visualization technique that helps you see where a neural network is focusing when it makes a decision. Instead of treating a deep model as a black box, EigenCAM uses the internal activations of a convolutional neural network (CNN) to create a heatmap that highlights the most influential
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Getting Ready to Train YOLOv5 on a Custom Dataset Training YOLOv5 on a custom dataset is one of the most powerful ways to move from “toy examples” to real-world computer vision solutions. Instead of relying only on generic datasets like COCO, you can train yolov5 on a custom dataset that reflects your exact problem: boats
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Getting to know YOLOX for modern object detection YOLOX is a high-performance object detection model that builds on the YOLO family while rethinking some of its core design choices. Instead of relying on predefined anchor boxes, YOLOX uses an anchor-free approach, which simplifies the detection head and makes training and deployment easier in real-world projects.
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Getting to know Detr for smarter object detection Detr (DEtection TRansformer) is a modern approach to object detection that replaces many of the hand-crafted tricks in classic detectors with a clean, transformer-based design. Instead of relying on anchors, custom assignment rules, and complex post-processing, Detr treats detection as a direct set prediction problem: given an
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Getting started with Detectron2 custom dataset training When you move beyond simple demos and pre-trained models, detectron2 custom dataset training is what turns object detection into a real-world tool. Instead of relying only on COCO classes, you teach Detectron2 to recognize the exact objects that matter to your project – fruits on a conveyor belt,
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Getting comfortable with a Detectron2 object detection tutorial A detectron2 object detection tutorial is all about turning raw images into meaningful, labeled scenes using one of Facebook AI’s most powerful computer vision libraries.Instead of hand-writing complex neural networks from scratch, you stand on the shoulders of pre-trained models like Faster R-CNN and ResNet, and focus
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Introduction If you’re looking for a practical way to get started with modern deep learning–based object detection, SSD MobileNet v3 object detection is one of the best places to begin.It’s lightweight, fast, and works great even on standard laptops, which makes it perfect for real-world projects, demos, and tutorials. In this post, we’ll walk through
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Introduction to Pixelib Pixelib is a lightweight, open-source Python library that makes image and video segmentation simple, fast, and practical—even if you’re just getting started.In this tutorial, you’ll learn how to use Pixelib to run state-of-the-art segmentation with just a few lines of code, apply pre-trained models, and adapt workflows for real projects like background
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