---
license: mit
tags:
- object-detection
- yolov8
- yolov11
- rf-detr
- pothole-detection
- road-defects
---

# SadakVision Weights

Trained weights for Indian road defect + garbage detection (crack / garbage / manhole / pothole).

Dataset: [Merged_Final_Data (Roboflow)](https://app.roboflow.com/ai-lisrp/merged_final_data/train) — YOLO format, train/valid/test.

## Files

| File | Source | Size |
|---|---|---|
| `yolov8m_100e_best.pt` | `yolov8m_res_100/train/weights/best.pt` | 49.6 MB |
| `yolov8m_runs_best.pt` | `yolov8m_runs/pothole_yolov8m/weights/best.pt` | 49.6 MB |
| `yolo26m_best.pt` | `yolo26_results/yolo26m_runs/weights/best.pt` | 42 MB |
| `yolov11n_best.pt` | `yolov11n_res/runs_yolov11n/weights/best.pt` | 5.2 MB |
| `rfdetr_best.pth` | `rfdetr/checkpoint_best_total.pth` | 127.6 MB |

## Results (validation split)

| Model | mAP50 | mAP50-95 | Precision | Recall |
|---|---|---|---|---|
| YOLOv8m (100e, imgsz 640, batch 32) | **0.773** | **0.489** | 0.858 | 0.736 |
| YOLOv26m (100e, batch 16) | 0.757 | 0.386 | 0.824 | 0.737 |
| YOLOv11n (100e, imgsz 512, batch 64) | 0.633 | 0.294 | 0.721 | 0.594 |
| RF-DETR (medium) | **0.796** | **0.550** | 0.881 | 0.768 |

RF-DETR val also: F1 0.817, mAP75 0.586, mAR 0.660. Per-class AP: crack 0.730, manhole 0.686, pothole 0.525, garbage 0.259 — garbage hardest.

Test: YOLOv8m mAP50 0.742, YOLOv26m 0.741, YOLOv11n 0.644.

## Usage

```bash
pip install ultralytics
yolo detect predict model=yolov8m_100e_best.pt source=your_image.jpg save=True
```

RF-DETR `.pth` is the `checkpoint_best_total.pth` (no optimizer state).