From the course: Deep Learning and Computer Vision: Object Detection with PyTorch
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Real-time object detection - PyTorch Tutorial
From the course: Deep Learning and Computer Vision: Object Detection with PyTorch
Real-time object detection
- [Instructor] Welcome back. In this video, we are going to explore how to implement realtime object detection using PyTorch. Realtime detection is crucial for applications like self-driving cars, surveillance systems, and robotics, where fast and accurate decisions are essential. Realtime object detection refers to the ability of a system to detect and localize objects in video streams or live camera feeds at a high speed, typically measured in frames per second. The goal is to achieve a balance between accuracy and speed, ensuring that the model detects objects correctly without introducing delays. Let's say in autonomous vehicles, real-time detection helps identify pedestrians, other vehicles and obstacles, allowing the vehicle to react quickly to change in the environment. Not all object detection models are designed for real-time performance models, like YOLO, You Only Look Once, SSD, Single Shot Detector and MobileNet SSD are optimized for speed, making them ideal for real time…
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