I’m working on object detection using frame difference. Usually, when talking about object detection, CNNs, such as SSD, RCNN, and YOLO, are used and they return accuracies and positions (x,y,w,h). However I cannot run those models due to the hardware limitation (Jetson nano and in real-time) and also find them a bit unnecessary.
(I am aware of TensorRT optimization and its benchmark)
What I want to do is,
Frame difference ->
cv2.findContours() or available contour algorithms -> detection by using sliding window + classification (ResNet50 in TensorRT) on each contour
I managed to write my code using
cv2.cuda for frame difference part, but
cv2.cuda doesn’t have
Is there any alternative for
Also, I want to hear some other approaches than sliding window technique.
I want to exploit every resource of Jetson Nano.