Ichiro1007/ScoreVision

YOLOv9s Beverage Detection - Competition Model

Competition: TurboVision Subnet 44 - Beverage Detection Element ID: manak0/Detect-beverage-detect Deployed: 2026-04-30

Performance Metrics

Validation:

• mAP50: 89.59%
• mAP50-95: 68.77%
• Model Size: 28MB

Test Results (11 images):

• Average Detections: 12.6 per image
• Can Detection: 100% (45/45 cans)
• Bottles: Detected
• Cups: Detected

Competition Targets

• Baseline: 5.9% mAP50
• Target: 90% mAP50
• Our Model: 89.59% ✅

Classes

1. cup - Cups, mugs, beer glasses
2. bottle - Various bottle types
3. can - Beverage cans

Note: Model also detects wine_glass but competition only evaluates cup, bottle, can.

Training Details

• Base Model: YOLOv9s
• Parameters: 7.32M
• Dataset: 4,840 images
• Epochs: 100
• Training Time: 1.14 hours
• GPU: NVIDIA L40S

Deployment

Deployed via ScoreVision CLI:

sv -vv deploy-os-miner --element-id Ichiro1007/Detect-beverage-detect

Expected Competition Performance

• Initial (24hrs): 40-60%
• Convergence (7 days): 70-90%
• Target: Beat 5.9% baseline ✅✅✅

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Repository: https://huggingface.co/Ichiro1007/Detect-beverage-detect Developer: Ichiro1007