Kunpeng
4dee7f664d
- Track only trained best.pt under runs/*/weights; ignore epoch/last checkpoints, downloaded base weights, and server logs (.gitignore) - Move runs/detect/runs/detect/smoke_fire_yolo26n_v2-3 to runs/detect/smoke_fire_yolo26n_v2-3 and update docs/model_comparison.md - Replace the Git LFS claim with an accurate plain-file statement
38 lines
2.2 KiB
Markdown
38 lines
2.2 KiB
Markdown
# Model Training Comparison
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This repository includes the best available smoke and fire detection weights and the evaluation artifacts needed to inspect the completed run. Trained weights are committed as regular files (only `best.pt`, no checkpoints or pretrained base models).
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## Available runs
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| Model | Run | Best epoch | Precision | Recall | mAP50 | mAP50-95 | Best weight |
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| --- | --- | ---: | ---: | ---: | ---: | ---: | --- |
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| YOLO11s | `smoke_fire_yolo11s_v1-4` | 84 | 0.77349 | 0.72164 | 0.77499 | 0.45688 | `runs/detect/smoke_fire_yolo11s_v1-4/weights/best.pt` |
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| YOLO26n | `smoke_fire_yolo26n_v2-3` | Not available | Not available | Not available | Not available | Not available | `runs/detect/smoke_fire_yolo26n_v2-3/weights/best.pt` |
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The YOLO11s row uses epoch 84 from `results.csv`, selected by the highest `metrics/mAP50-95(B)`. Training completed 124 epochs before early stopping. The best observed mAP50 was 0.77720 at epoch 90, while the selected checkpoint maximizes mAP50-95.
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The YOLO26n directory currently contains only `best.pt`; its `args.yaml` and `results.csv` are unavailable. Its detection quality therefore cannot be compared fairly with YOLO11s yet. The weight is included as a deployment-size baseline only.
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## Included evidence
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The YOLO11s run includes:
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- Full epoch metrics in `results.csv`
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- Training and validation summary in `results.png`
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- Precision, recall, F1, and PR curves
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- Raw and normalized confusion matrices
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- Validation label and prediction previews
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- Effective training parameters in `args.yaml`
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- Best-checkpoint metadata in `best_point.json`
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Periodic `epoch*.pt` checkpoints, `last.pt`, training batch previews, runtime server logs, and manual audit preview images are intentionally excluded. They are either reproducible intermediates or unrelated to comparing the best models.
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## Reproducing evaluation
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Run validation against the configured smoke/fire dataset:
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```powershell
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uv run fire-yolo val --weights runs/detect/smoke_fire_yolo11s_v1-4/weights/best.pt
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```
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To complete the YOLO26n comparison, rerun validation with its best weight and retain the generated `args.yaml`, `results.csv`, plots, and confusion matrices beside the checkpoint. |