POTHOLE DETECTOR (YOLOV4)

Brief Introduction

This model expects as input an image of a road, on which it detects potholes.

Business case

This model allows you to determine the number and size of potholes on a given section of road, so you can measure road quality.

I created this model back in 2021, so it's not a cutting-edge solution. Also, because it's an older model, it's large in size and not suitable for running a demo in a browser, so there isn't a demo available for it. 

Number of classes

1 class: (pothole)

Metrics

detections_count = 952, unique_truth_count = 359

class_id = 0, name = Pothole, ap = 76.50% (TP = 258, FP = 68)

for conf_thresh = 0.25, precision = 0.79, recall = 0.72, F1-score = 0.75

for conf_thresh = 0.25, TP = 258, FP = 68, FN = 101, average IoU = 61.88 %

IoU threshold = 50 %, used Area-Under-Curve for each unique Recall

mean average precision (mAP@0.50) = 0.764998, or 76.50 %

License

By purchasing or downloading any project, you agree to the full license terms, which you can view here: LINK