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Yolov8s Valorant Detection
An object detection model based on YOLOv8, specifically designed to identify key elements in the game Valorant.
Downloads 209
Release Time : 1/28/2023
Model Overview
This model is trained using the YOLOv8 architecture, focusing on detecting critical elements in Valorant such as bombs, teammates, and enemy characters, suitable for game analysis and auxiliary tool development.
Model Features
High Precision Detection
Achieves 97.14% mAP@0.5 accuracy on the validation set, capable of accurately identifying key elements in the game.
Lightweight Model
Based on the YOLOv8s architecture, it maintains high performance while having a smaller model size and faster inference speed.
Specialized Game Detection
Optimized specifically for Valorant game scenarios, capable of recognizing game-specific elements such as bomb status, teammates, and enemies.
Model Capabilities
Game Scene Object Detection
Real-time Object Recognition
Bomb Status Recognition
Teammate/Enemy Differentiation
Use Cases
Game Analysis
Game Replay Analysis
Analyze bomb placements and character positions in game replays.
Can be used for tactical analysis and training improvements.
Real-time Game Assistance
Detect key elements in real-time during gameplay.
Provides visual feedback on game status.
Esports
Commentary Assistance
Automatically identify and annotate key events in matches.
Enhances viewer experience.
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