face_mask_detection

Dataset

The Face mask Dataset is collected and annotated by Self-Study-Camp team members on 22 November 2021. The dataset consists of 208 images splitted into 168 train, 40 test images in XML format.

Model

We will be using SSD-mobilenetv2 model from TensorFlow 2 Detection Model Zoo. They provide a collection of detection models pre-trained on the COCO 2017 dataset.

Model name	Speed (ms)	COCO mAP	Outputs
SSD MobileNet V2 FPNLite 640x640	39	28.2	Boxes

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Metrics

After training for 8000 steps:

{'Loss/classification_loss': 0.06144937,
 'Loss/localization_loss': 0.017765515,
 'Loss/regularization_loss': 0.12342198,
 'Loss/total_loss': 0.20263687,
 'learning_rate': 0.07603875}

Validation Detection Metrics:

Accumulating evaluation results...
DONE (t=0.06s).
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.343
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.698
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.399
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.700
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.515
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.313
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.348
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.449
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.552
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.700
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.693
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.511

Tensor Board Metrics

References

TensorFlow Object Detection API Tutorial
TensorFlow 2 Detection Model Zoo