What did you personally accomplish this week on the project? Give files or photos that demonstrate your progress.
This week we collectively focused on the integration of the system and our final presentation. Some of the larger tasks involve setting up the ssh server within the Jetson Nano, configuring the requirements for PyTorch on the Jetson Nano, and attempting to run some rough tests on the KLT using images of animals.
Is your progress on schedule or behind? If you are behind, what actions will be taken to catch up to the project schedule?
My progress is behind, as I would have liked to have tested more videos on the tracker of animals at different distances from the camera , but it seems I could not get the dependencies correct under ffmpeg for using skvideo. With this I could convert regular mp4 videos to npy arrays that are usable for our KLT. Catching up would require getting skvideo to work, recording videos of animals at different distances and making sure the tracker works at an appropriate speed. If not, our plan B would be to use the base KLT offered by openCV. Perhaps there is another way of converting regular videos to npy without skvideo?
What deliverables do you hope to complete in the next week?
In the next week, I’d like to have a fully integrated tracker.