Accomplishment:
For this week, I have successfully implemented the Yolov5 OR model + DE feature. I used classes for the easier extraction of the reference images and filtered the detected objects so that it only outputs several indoor objects, such as a couch, person, mobile phone, and chair. I took several reference images from my laptop camera from a known distance and compared them with the images from online pairwise to determine whether the OR model successfully recognizes specific indoor objects and outputs relative distance from one another (which object is closer to the camera). After several instances of successful output, I used the image captured from the Jetson camera and ran it in my model. The following has the image taken and the output from the model.
As shown in the image, it successfully outputs several chairs and their distances from the camera. However, although the order of distance from the camera makes sense, the numerical value of the estimation is too high. This is because the chair from the reference image has a different width from the chair from the test image. To resolve this problem, I am planning on taking the reference images of the objects that will be used in the test environment to increase the precision of the DE feature.
Progress
I have successfully added relevant objects (coach, chair) to the DE feature and had some testing done. However, it is also important to test the OR model with more images from the Jetson camera to ensure the accuracy. I will need to do more testing with images and videos taken from a Jetson camera.
Projected Deliverables
For next week, I will finish deploying the OR model to Jetson. At the same time, I will include more relevant objects, such as a table, to ensure sufficient range of indoor objects. The test results with Jetson camera will be documented for the final report.