• Hardware Platform (Jetson / GPU) T4 GPU
• DeepStream Version 5.0
• TensorRT Version 7.0
• NVIDIA GPU Driver Version (valid for GPU only) 10.2
I am building a pipeline that has a people detection model - tracker - secondary model for face mask detection.
I am facing a lot of false negatives for the secondary model. However, upon training, the model achieved a good validation score. I cropped the images detected by the primary model and passed them manually to the face-mask model (without a pipeline). The model could detect most of the masks with a very high probability (98%).
The face mask model is FasterRCNN resnet18. It detects 2 classes: face mask and human face
The configuration file is attached.
config_infer_secondary_face_mask_detection.txt (2.7 KB)
What can I do to increase the detection accuracy of the secondary model in the pipeline?