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Sids Status Report for April 30th
What did you personally accomplish this week on the project?
This week I focussed most of my work on working on finishing the integration of the system and beginning to procedures needed for testing.
On the integration side, we are debugging the PyTorch and Cuda versions on the Jetson since there was some compatibility issue that arose when we tried running the script that had the detection integrated with the camera simple search. Justin is currently taking a look at this and as soon as that is done we move on to testing the system implementation with our one camera approach we had discussed in the last meeting with Professor Savvides.
On the testing end, I looked through the WCS Camera Traps Dataset once more and this time looked for images that were not in our dataset and had pictures of different animals in a variety of orientations (all photographed well).
Some of these are attached below:
Once I finish printing out the pictures I can get the cut-outs and find a way to mount and place them so we can place them around the setup for testing. To test out different lighting conditions, I found a place we can use where we can control the light exposure and hence test at different distances and in different light conditions that simulate the real environment.
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 on the project is a little behind because I was unwell this last week. In the meantime, I made progress with Integration and Testing as described above and to get back on schedule I am going to focus all my effort on finishing the project in the coming few days. Once we finish debugging, I can spend time on testing and refining the system as needed which should be something that can be accomplished with repeated testing and tweaking of the system.
What deliverables do you hope to complete in the next week?
Finish testing and refining the system as much as we can in order to have a smooth and well-functioning demo
In the meantime, I will finish the deliverables as needed i.e. the poster, report and video.
Sids Status Report for April 23rd
What did you personally accomplish this week on the project?
The majority of my work this week involved finishing the process of training the detection model properly and ensuring that this was done properly.
I faced many problems with this process; first, our setup on Colab did not work in time either due to high latency during the scanning of the dataset files from google drive. Following this, I decided to use my teammate’s old desktop for training the model since it had a GPU. After managing to transfer all the files to the desktop using the public sharing URL provided by google drive.
I set up the environment needed for training the neural net on the desktop and this took much longer than I had expected. We ran into many problems and with my team’s help, I was able to modify the Python and CUDA versions on the desktop to be compatible with each other and YOLOv5. We also had to make changes to the CUDA and PyTorch versions that were running on the JESON Nano based on the changes we made.
While the model was training, we worked on the search algorithm for the camera on the JETSON. Once the model was trained we got statistics regarding the recall and accuracy which we were happy with.
Recall ~ 93%
Acuraccy ~ 92.8%
After adding code to the scripts on the JETSON, the detection model can be integrated into the algorithm. We move the trained best weights and call the predict function for every frame the camera sees until the detection model tells us to transfer control to track.
We planned out the testing process and I picked images we are going to print to test the project in the coming days.
Is your progress on schedule or behind? If you are behind, what actions will be taken to catch up to the project schedule?
The progress is slightly behind due to all the problems faced while training the detection model and the fact that errors would show up hours into running the training script.
To make up for this, my team helped me with implementing a basic simple search algorithm with the camera for now and we plan to speed up our plans for testing which would put us back on track.
What deliverables do you hope to complete in the next week?
Test results for the detection and integrated system.
Fernando Paulino’s Status Report for February 19
What did you personally accomplish this week on your project?
This week I focused on familiarizing myself with our cameras’ SDK and zoom, focus, and autofocus functionality. I also worked on the tracking algorithm. Thus far, we have an LKT for simple translation transformations of our target.
Is your progress on schedule or behind? If you are behind, what actions will be taken to catch up to the project schedule?
After settling into our schedule and more concrete individual tasks, I believe we are on schedule. With Sid making progress on the detection section, I shifted my focus to mostly tracking for now. We will be ready to start testing the baseline tracking algorithm by next week as planned.
What deliverables do you hope to complete in the next week?
By next week, the baseline tracking algorithm, an LKT for full affine transformations, will be ready for testing. I would also like to implement some code for synchronizing the camera with the tracker.
Justin’s Status Report for February 19
What did you personally accomplish this week on the project? Give files or photos that demonstrate your progress?
I began the week researching photo editing from a user stand point. I watched multiple tutorials on properly editing pictures. From this study I selected which image editing algorithms would be necessary for our project.
Afterward, I researched the implementation of these editing algorithms. This part was difficult, because editing softwares do not share their source code, and there is not a universal definition for these algorithms. I used my best judgement to find the approaches which were simple and best fit our use case. I then implemented these algorithms.
Is your progress on schedule or behind? If you are behind, what actions will be taken to catch up to the project schedule?
I finished my assigned task for this week and am currently on schedule.
What deliverables do you hope to complete in the next week?
Next week I hope to have a finalized physical setup for our stand+cameras. Our parts have arrived, so we are doing setup tasks next week.