{"id":106,"date":"2022-10-22T20:17:33","date_gmt":"2022-10-22T20:17:33","guid":{"rendered":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/?p=106"},"modified":"2022-10-22T20:17:33","modified_gmt":"2022-10-22T20:17:33","slug":"kevins-status-report-for-10-22-2022","status":"publish","type":"post","link":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/2022\/10\/22\/kevins-status-report-for-10-22-2022\/","title":{"rendered":"Kevin’s Status Report for 10\/22\/2022"},"content":{"rendered":"

Note: This weekly status report covers any work performed during the week of 10\/15 as well as Fall Break.<\/em><\/p>\n

This past week (10\/15), the team spent the majority of their time developing the design report, for which I spent some time performing an experiment to measure the performance of the pre-trained model we are measuring. To do this, I first had to download an offline copy of the labeled dataset made available by aeye-alliance<\/a>. Then, I relabeled the dataset with braille unicode characters rather than English translations. I also manually scanned through each labeled image to make sure they were labeled correctly. Of the more than 20,000 images downloaded from online containers, I only found 16 mislabeled images and 2 that I deemed too unclear to use.<\/p>\n

\"\"
An example of mislabeled data within the “\u2803” dataset.<\/figcaption><\/figure>\n

Attribution of training data will be difficult to maintain if required. We can refer to the labeled data csv files from aeye-allliance, which includes a list of the sources of all images, but we will not be able to specifically pinpoint the source of any single image.<\/p>\n

Once I had the correct data in each folder, I wrote a python script which loaded the pre-trained model and crawls through the training dataset, making a prediction for each image. The result would be noted down in a csv containing the correct value, the prediction, and the measured inference time. Using pandas and seaborn, I was able to visualize the resulting data as a confusion matrix. I found that the resulting confusion matrix did not quite reach the requirements that we put forth for ourselves. There are also a number of imperfections with this experiment, which have been described in the design report.<\/p>\n

\"\"
Confusion matrix generated by experiment<\/figcaption><\/figure>\n

The rest of my time was spent writing my share of the content of the design report. The following week being Fall Break, I did not do as much work as described in our Gantt chart. I looked into how to use Amazon Sagemaker to train a new ML model and setup an AWS account. I am still in alignment with my scheduled tasks, having built a large dataset and measured existing solutions in order to complete the design report. Next week, I hope to use this knowledge to quickly setup a Sagemaker workflow to train and iterate on a model customized for our pre-processing pipeline.<\/p>\n","protected":false},"excerpt":{"rendered":"

Note: This weekly status report covers any work performed during the week of 10\/15 as well as Fall Break. This past week (10\/15), the team spent the majority of their time developing the design report, for which I spent some time performing an experiment to measure the performance of the pre-trained model we are measuring. … <\/p>\n

Continue reading “Kevin’s Status Report for 10\/22\/2022”<\/span><\/a><\/p>\n","protected":false},"author":645,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[4],"tags":[6],"_links":{"self":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/wp-json\/wp\/v2\/posts\/106"}],"collection":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/wp-json\/wp\/v2\/users\/645"}],"replies":[{"embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/wp-json\/wp\/v2\/comments?post=106"}],"version-history":[{"count":2,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/wp-json\/wp\/v2\/posts\/106\/revisions"}],"predecessor-version":[{"id":115,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/wp-json\/wp\/v2\/posts\/106\/revisions\/115"}],"wp:attachment":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/wp-json\/wp\/v2\/media?parent=106"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/wp-json\/wp\/v2\/categories?post=106"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/f22-teamb1\/wp-json\/wp\/v2\/tags?post=106"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}