Object detection on thermal images(FLIR dataset)
Object detection on thermal images
Average Precision (AP) @[ IoU=0.50:0.50 | area= all | maxDets=100 ] = 0.714
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = -1.000
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = -1.000
Average Precision (AP) @[ IoU=0.50:0.50 | area= small | maxDets=100 ] = 0.576
Average Precision (AP) @[ IoU=0.50:0.50 | area=medium | maxDets=100 ] = 0.819
Average Precision (AP) @[ IoU=0.50:0.50 | area= large | maxDets=100 ] = 0.906
Average Recall (AR) @[ IoU=0.50:0.50 | area= all | maxDets= 1 ] = 0.348
Average Recall (AR) @[ IoU=0.50:0.50 | area= all | maxDets= 10 ] = 0.781
Average Recall (AR) @[ IoU=0.50:0.50 | area= all | maxDets=100 ] = 0.787
Average Recall (AR) @[ IoU=0.50:0.50 | area= small | maxDets=100 ] = 0.719
Average Recall (AR) @[ IoU=0.50:0.50 | area=medium | maxDets=100 ] = 0.834
Average Recall (AR) @[ IoU=0.50:0.50 | area= large | maxDets=100 ] = 0.918
Baseline result: mAP IoU(0.5) of 0.587
You can download the dataset from here
You can find the blog post published on Medium.
Pretrained weights: thermal