| # YOLOv9s Beverage Detection - Competition Model |
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| **Competition:** TurboVision Subnet 44 - Beverage Detection |
| **Element ID:** manak0/Detect-beverage-detect |
| **Deployed:** 2026-04-30 |
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| ## Performance Metrics |
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| **Validation:** |
| - mAP50: 89.59% |
| - mAP50-95: 68.77% |
| - Model Size: 28MB |
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| **Test Results (11 images):** |
| - Average Detections: 12.6 per image |
| - Can Detection: 100% (45/45 cans) |
| - Bottles: Detected |
| - Cups: Detected |
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| ## Competition Targets |
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| - Baseline: 5.9% mAP50 |
| - Target: 90% mAP50 |
| - **Our Model: 89.59%** ✅ |
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| ## Classes |
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| 1. **cup** - Cups, mugs, beer glasses |
| 2. **bottle** - Various bottle types |
| 3. **can** - Beverage cans |
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| 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 |
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| Deployed via ScoreVision CLI: |
| ```bash |
| 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 |
| |
