{"id":109,"date":"2024-03-17T03:20:35","date_gmt":"2024-03-17T03:20:35","guid":{"rendered":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/?p=109"},"modified":"2024-03-17T03:20:35","modified_gmt":"2024-03-17T03:20:35","slug":"bhavyas-status-report-for-3-16-24","status":"publish","type":"post","link":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/2024\/03\/17\/bhavyas-status-report-for-3-16-24\/","title":{"rendered":"Bhavya’s Status Report for 3\/16\/24"},"content":{"rendered":"

I finished creating the detection algorithm. Instead of using the yOLOv4, I used the R-CNN instead. R-CNN typically provides better accuracy by employing region-based convolutional neural networks, which allow for more precise localization of objects in images, albeit at the cost of increased computational complexity during inference. The bounding boxes I was able to create were highly accurate but took a long time to be produced.\u00a0<\/em>Ran tests for the detection using static images of the slot car from various angles and distances. Then I integrated the pre-processing, detection, and tracking. Ran tests on a video of the slot car. Currently, the detection algorithm might be too slow, and the preprocessing needs to be tuned after testing which configuration works best for latency. I also have actual footage of the toy car on the track that I will be testing my algorithm on now.<\/p>\n

For next week, I will be integrating the code with the live stream offered by our cameras and relaying panning instructions to the motors. Further testing on what type of tracker\/detection will be best for our use case will be required.<\/p>\n

Given the amount of fine-tuning our system will require for the live stream to be watchable I think we are slightly behind schedule. Sufficient testing in the following week should help put us back on track<\/p>\n","protected":false},"excerpt":{"rendered":"

I finished creating the detection algorithm. Instead of using the yOLOv4, I used the R-CNN instead. R-CNN typically provides better accuracy by employing region-based convolutional neural networks, which allow for more precise localization of objects in images, albeit at the cost of increased computational complexity during inference. The bounding boxes I was able to create … <\/p>\n

Continue reading “Bhavya’s Status Report for 3\/16\/24”<\/span><\/a><\/p>\n","protected":false},"author":901,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[8],"tags":[],"_links":{"self":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/wp-json\/wp\/v2\/posts\/109"}],"collection":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/wp-json\/wp\/v2\/users\/901"}],"replies":[{"embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/wp-json\/wp\/v2\/comments?post=109"}],"version-history":[{"count":1,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/wp-json\/wp\/v2\/posts\/109\/revisions"}],"predecessor-version":[{"id":110,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/wp-json\/wp\/v2\/posts\/109\/revisions\/110"}],"wp:attachment":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/wp-json\/wp\/v2\/media?parent=109"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/wp-json\/wp\/v2\/categories?post=109"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamc6\/wp-json\/wp\/v2\/tags?post=109"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}