Pedestrian and vehicle detection network based on MobileNet v1.0 + SSD.
| Metric | Value |
|---|---|
| AP for pedestrians | 88% |
| AP for vehicles | 90% |
| Target pedestrian size | 60x120 pixels |
| Target vehicle size | 40x30 pixels |
| GFLOPS | 3.974 |
| MParams | 1.650 |
| Source framework | Caffe* |
Average Precision (AP) metric is described in: Mark Everingham et al. “The PASCAL Visual Object Classes (VOC) Challenge”.
Tested on challenging internal datasets with 1001 pedestrian and 12585 vehicles to detect.
image_id, label, conf, x_min, y_min, x_max, y_max]image_id - ID of the image in the batchlabel - predicted class IDconf - confidence for the predicted classx_min, y_min) - coordinates of the top left bounding box cornerx_max, y_max) - coordinates of the bottom right bounding box corner.[*] Other names and brands may be claimed as the property of others.