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YOLO (You Only Look Once)

Rating:

4.8 / 5.0

Tags

Computer Vision, Object Detection, Real-time, Deep Learning, Algorithm, Open Source

Categories:
Computer visionMachine learning and neural networks
Creator Различные исследователи
Date 2016-05-09
Platforms Frameworks
Status Active (Development)
Website github.com
Price Model Free (model)
Sections:
DL FrameworksImage AnalysisImage SegmentationObject DetectionObject RecognitionVideo Analysis

Pricing Details

Free (open source). Costs may apply when using third-party platforms or cloud services that provide access to YOLO models.

Features

Real-time object detection, high speed, single-pass detection, bounding box prediction, multiple versions, open-source.

Integrations

Integrates as a model or library into projects in Python, C++, and other languages using frameworks (TensorFlow, PyTorch, Darknet).

Preview

YOLO (You Only Look Once) is one of the most well-known and widely used algorithms for real-time object detection. It is characterized by its high speed, processing images or video streams in a single pass. YOLO predicts bounding boxes and class probabilities for objects simultaneously across the entire image. There are several versions of YOLO (v1, v2, v3, v4, v5, YOLO-NAS, YOLOv7, YOLOv8, etc.), each improving speed and accuracy over its predecessors. YOLO is open-source and is actively used in various computer vision applications where fast and efficient object detection is required.