Yolov8m Valorant Detection
An object detection model based on YOLOv8, specifically designed to detect key objects in the Valorant game.
Downloads 423
Release Time : 1/28/2023
Model Overview
This model is trained using the YOLOv8 architecture, specifically designed to detect key objects in the Valorant game, including dropped bombs, enemies, planted bombs, and teammates.
Model Features
High Precision Detection
Achieves 96.466% mAP@0.5(box) accuracy on the validation set.
Game-Specific Optimization
Specially optimized for Valorant game scenarios.
Multi-Class Detection
Capable of detecting 4 different types of game objects simultaneously.
Model Capabilities
Real-time Object Detection
Game Scene Analysis
Multi-Object Recognition
Use Cases
Game Assistance
Game State Monitoring
Real-time detection of key object positions in the game.
Helps players better understand the game situation.
Game Data Analysis
Analyze object distribution and movement in game replays.
Used for tactical analysis and improvement.
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