| --- |
| 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). |
|
|
